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Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 853 p. 361 illus.)
Disciplina 006.6
006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10590-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Organization -- Table of Contents -- Tracking and Activity Recognition -- Visual Tracking by Sampling Tree-Structured Graphical Models -- 1 Introduction -- 2 Related Work -- 3 Main Framework -- 3.1 Learning Tree Structure by MCMC -- 3.2 Tracking on Tree Structure -- 4 Hierarchical Construction of Tree Structure -- 4.1 Tree Construction on Key Frames -- 4.2 Tree Extension by Manifold Alignment -- 5 Experiments -- 5.1 Datasets -- 5.2 Identified Tree Structure -- 5.3 Quantitative and Qualitative Performance -- 6 Conclusion -- References -- Tracking Interacting Objects Optimally Using Integer Programming -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Bayesian Inference -- 3.2 Flow Constraints -- 3.3 Mixed Integer Programming -- 3.4 Graph Size Reduction -- 4 Estimating Probabilities of Occupancy -- 4.1 Oriented Objects -- 4.2 Objects Off the Ground Plane -- 5 Experiments -- 5.1 Test Sequences -- 5.2 Parameters and Baselines -- 5.3 Results -- 6 Conclusion -- References -- Learning Latent Constituents for Recognition of Group Activities in Video -- 1 Introduction -- 2 Related Work -- 3 Learning Functional Constituents of Group Activities -- 3.1 Functional Grouping of Part Instances -- 3.2 From Constituent Classifiers to Activity Classification -- 3.3 Inference in Novel Query Scenes -- 3.4 Joint Learning of Group Activity and Constituent Classifiers -- 4 Experimental Results -- 4.1 Experimental Protocol -- 4.2 Group Activity Recognition -- 5 Conclusion -- References -- Recognition -- Large-Scale Object Classification Using Label Relation Graphs -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Hierarchy and Exclusion (HEX) Graphs -- 3.2 Classification Model -- 3.3 Efficient Inference -- 4 Experiments -- 4.1 Implementation -- 4.2 Object Classification on ImageNet.
4.3 Zero-Shot Recognition on Animals with Attributes -- 4.4 Efficiency of Inference -- 5 Discussions and Conclusions -- References -- 30Hz Object Detection with DPM V5 -- 1 Introduction -- 1.1 Prior Work -- 2 Pyramid of Features vs. Pyramid of Templates -- 3 Hierarchical Vector Quantization -- 4 Object Proposal Using Hash Table -- 4.1 Hash Codes -- 4.2 Priority Lists -- 4.3 Hash Table Initialization -- 5 Object Scoring -- 6 Experimental Results -- 7 Discussion -- References -- Knowing a Good HOG Filter When You See It: Efficient Selection of Filters for Detection -- 1 Introduction -- 1.1 Related Work -- 2 Background -- 2.1 An Overview of Poselets for Object Detection -- 2.2 An Overview of Exemplar SVMs for Object Detection -- 3 Ranking and Diversity -- 3.1 Learning to Rank Parts -- 3.2 Selecting a Diverse Set of Parts -- 3.3 Features for Part Ranking -- 3.4 The LDA Acceleration -- 4 Experiments with Poselets -- 4.1 Training the Ranking Algorithm -- 4.2 Training the Diversity Model -- 4.3 Selection Methods Considered -- 4.4 Ranking Results -- 4.5 PASCAL VOC Detection Results -- 5 Experiments with Exemplar SVMs -- 5.1 PASCAL VOC Detection Results -- 5.2 An Analysis of Bicycle HOG Filters -- 6 Conclusion -- References -- Linking People in Videos with "Their" Names Using Coreference Resolution -- 1 Introduction -- 2 Related Work -- 3 Problem Setup -- 4 Our Model -- 4.1 Regression-Based Clustering -- 4.2 Name Assignment to Tracks -- 4.3 Name Assignment to Mentions and Coreference Resolution -- 4.4 Alignment between Tracks and Mentions -- 5 Optimization -- 6 Experiments -- 6.1 Name Assignment to Tracks in Video -- 6.2 Name Assignment to Mentions -- 7 Conclusion -- References -- Poster Session 1 -- Optimal Essential Matrix Estimation via Inlier-Set Maximization -- 1 Introduction -- 1.1 Related Work -- 2 Essential Manifold Parametrization.
3 Optimization Criteria -- 4 Branch and Bound over D2 π × B3 π -- 4.1 Lower-Bound Computation -- 4.2 Upper-Bound Computation via Relaxation -- 4.3 Efficient Bounding with Closed-Form Feasibility Test -- 4.4 The Main Algorithm -- 5 Experiment Results -- 5.1 Synthetic Scene Test: Normal Cases -- 5.2 Synthetic Scene Test: Special Cases -- 5.3 Real Image Test -- 6 Conclusion and Future Work -- References -- UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability -- 1 Introduction -- 1.1 Related Work -- 2 Theory -- 2.1 Geometry of the Absolute Pose Problem -- 2.2 Derivation of the Objective Function -- 2.3 Universal, Closed-Form Least-Squares Solution -- 2.4 Comparison to a Lagrangian Formulation -- 2.5 Elimination of Two-Fold Symmetry -- 2.6 Second-Order Optimality and Root Polishing -- 3 Experimental Evaluation -- 3.1 The Central Case -- 3.2 The Non-central Case -- 3.3 Computational Efficiency -- 3.4 Results on Real Data -- 4 Conclusion -- References -- 3D Reconstruction of Dynamic Textures in Crowd Sourced Data -- 1 Introduction -- 2 Related Work -- 3 Initial Model Generation -- 3.1 Static Reconstruction from Photo Collections -- 3.2 Coarse Dynamic Textures Priors from Video -- 3.3 Coarse Static Background Priors from Video Frames -- 3.4 Graph-Cut Based Dynamic Texture Refinement -- 3.5 Shape from Silhouettes -- 4 Closed Loop 3D Shape Refinement -- 4.1 Geometry Based Video to Image Label Transfer -- 4.2 Mitigating Dynamic Texture in SfM Estimates -- 4.3 Building a Static Background Prior for Single Images -- 4.4 Mitigating of Non-uniform Spatial Sampling -- 5 Experiments -- 6 Conclusion -- References -- 3D Interest Point Detection via Discriminative Learning -- 1 Introduction -- 2 Related Work -- 3 Attributes and Learning -- 3.1 Basic Attributes -- 3.2 DoG Attributes -- 3.3 Random Forest -- 3.4 Imbalanced Classes.
4 Ground Truth and Experiments -- 4.1 Ground Truth -- 4.2 Experiments -- 4.3 Training and Predicting -- 4.4 Evaluation Criteria -- 4.5 Results -- 5 Conclusions -- References -- Pose Locality Constrained Representation for 3D Human Pose Reconstruction -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Problem Description -- 3.2 Hierarchical Pose Tree -- 3.3 Pose Locality for Reconstruction -- 3.4 Algorithm Summary -- 4 Experiments -- 4.1 Quantitative Results -- 4.2 Qualitative Evaluation -- 4.3 The Selection of Parameters dM and E -- 4.4 Distribution of Anchor-Node Depth -- 5 Conclusions -- References -- Synchronization of Two Independently Moving Cameras without Feature Correspondences -- 1 Introduction -- 1.1 Previous Work -- 1.2 Contributions -- 1.3 Notation and Paper Organization -- 2 Static and Jointly Moving Cameras -- 2.1 Video Synchronization -- 2.2 Uniqueness of Solution -- 3 Independently Moving Cameras -- 3.1 Video Synchronization -- 4 Object Motion Recovery -- 5 Experimental Results -- 6 Conclusions -- References -- Multi Focus Structured Light for Recovering Scene Shape and Global Illumination -- 1 Introduction -- 1.1 Related Work -- 2 Modeling Image Formation and Illumination -- 3 Illumination Control and Image Acquisition -- 4 Recovering Shape with Defocused Light Patterns -- 5 Recovering Direct and Global Illumination Components -- 6 Results -- 6.1 Depth Recovery -- 6.2 Recovering Direct and Global Illumination -- 7 Discussion -- References -- Coplanar Common Points in Non-centric Cameras -- 1 Introduction -- 2 Ray Space Analysis -- 2.1 CCPs in General Linear Cameras -- 2.2 Concentric Mosaics -- 3 CCPs in Catadioptric Mirrors -- 3.1 Ray Space vs. Caustics -- 3.2 Rotationally Symmetric Mirrors -- 3.3 Cylinder Mirrors -- 4 Experiments -- 4.1 Synthetic Experiment -- 4.2 Real Experiment -- 5 Conclusions and Discussions.
References -- SRA: Fast Removal of General Multipath for ToF Sensors -- 1 Introduction -- 1.1 Contributions -- 2 Prior Work -- 3 Sparse Reflections Analysis -- 3.1 The Multipath Representation -- 3.2 The SRA Algorithm -- 4 Fast Computation -- 5 Experiments -- 5.1 Running Time -- 5.2 General Multipath: Examples -- 5.3 Comprehensive Two-Path Evaluation -- 5.4 Real Images -- 6 Conclusions -- References -- Sub-pixel Layout for Super-Resolution with Images in the Octic Group -- 1 Introduction -- 1.1 Contributions -- 1.2 Related Work -- 2 Good Sub-pixel Layout for Super-Resolution -- 2.1 Single Image Case -- 2.2 Multiple Images in the Octic Group -- 2.3 Good Sub-pixel Layout -- 3 Reconstruction Algorithm -- 4 Performance Evaluation -- 4.1 Synthetic Test -- 4.2 Real Data Test -- 5 Discussion -- 6 Conclusion -- References -- Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 SFDL -- 3.2 Identification -- 3.3 Verification -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Experimental Settings -- 4.3 Results and Analysis -- 5 Conclusion and Future Work -- References -- Read My Lips: Continuous Signer Independent Weakly Supervised Viseme Recognition -- 1 Introduction -- 2 Mouthings in Sign Language, Challenging? -- 3 State of the Art -- 4 Corpora -- 5 Mouthing Features -- 6 Weakly Supervised Mouthing Recognition -- 6.1 Overview -- 6.2 Reordering Sentence Structure -- 6.3 Pronunciation Lexicon and Viseme Mapping -- 6.4 Training Viseme Models -- 6.5 Context-Dependent Visemes with a Visemic Classification and Regression Tree -- 6.6 Linear Discriminant Analysis -- 7 Results -- 8 Conclusions -- References -- Multilinear Wavelets: A Statistical Shape Space for Human Faces -- 1 Introduction -- 2 Related Work -- 3 Multilinear Wavelet Model.
3.1 Second Generation Spherical Wavelets.
Record Nr. UNINA-9910481956703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part IV / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part IV / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 848 p. 340 illus.)
Disciplina 006.6
006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10593-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Organization -- Table of Contents -- Poster Session 4 (continued) -- Schwarps: Locally Projective Image Warps Based on 2D Schwarzian Derivatives -- 1 Introduction -- 2 Background on Projective Differential Invariants -- 2.1 The Cross-Ratio -- 2.2 The 1D Schwarzian Derivative -- 2.3 Multidimensional Schwarzian Derivatives (MSDs) -- 3 Schwarzian Equations in Two Dimensions -- 3.1 The 1D Schwarzian Derivative -- 3.2 2D Schwarzian Equations -- 4 Modeling the Projection of Deforming Surfaces -- 4.1 The Schwarp -- 5 Experimental Results -- 5.1 Implementation Details -- 5.2 Synthetic Data -- 5.3 Real Data -- 6 Conclusion -- References -- gDLS: A Scalable Solution to the Generalized Pose and Scale Problem -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Solution Method -- 4.1 A New Least Squares Cost Function -- 4.2 Macaulay Matrix Solution -- 5 Experiments -- 5.1 Numerical Stability -- 5.2 Simulations with Noisy Synthetic Data -- 5.3 SLAM Registration with Real Images -- 5.4 Runtime Analysis -- 6 Conclusion -- Appendix -- References -- Generalized Connectivity Constraints for Spatio-temporal 3D Reconstruction -- 1 Introduction -- 1.1 Contributions -- 1.2 Related Work -- 2 3D Reconstruction with Connectivity Constraints -- 2.1 Spatio-temporal Multi-view Reconstruction -- 2.2 Connectivity Constraints via Directed Graphs -- 3 Generalized Connectivity Constraints for Objects of Arbitrary Genus -- 3.1 Handle and Tunnel Loops -- 3.2 Loop Connectivity Constraints -- 4 Numerical Optimization -- 5 Experiments -- 6 Conclusion -- References -- Passive Tomography of Turbulence Strength -- 1 The Need to Recover Turbulence Strength -- 2 Theoretical Background -- 2.1 Turbulence Statistics and Refraction -- 2.2 Linear Tomography -- 3 Principle of C2n Tomography -- 3.1 Numeric Tomographic Recovery of C2n -- 4 Simulation.
5 Experiments -- 5.1 Laboratory -- 5.2 Outdoors -- 6 Discussion -- References -- A Non-local Method for Robust Noisy Image Completion -- 1 Introduction -- 2 Related Works -- 3 The Proposed Algorithm -- 3.1 Overview -- 3.2 Robust Patch Matching and Grouping -- 3.3 Collaborative Filtering Using Low-Rank Matrix Completion -- 4 Implementation Details and Experiments -- 4.1 Implementation Details -- 4.2 Results and Comparisons -- 5 Conclusions and Future Works -- References -- Improved Motion Invariant Deblurring through Motion Estimation -- 1 Introduction -- 2 Previous Work -- 3 Motion Invariant Capture -- 3.1 Motion Invariance Artifacts -- 4 Artifact-Based Motion Estimation -- 5 Experiments -- 5.1 Synthetic Data -- 5.2 Real Camera Images -- 6 Limitations -- 7 Multiple Moving Objects -- 8 Conclusion -- References -- Consistent Matting for Light Field Images -- 1 Introduction -- 2 Related Works -- 3 EPI in Light Field Images -- 3.1 The EPI Constraint -- 3.2 Color Sample Correspondences in EPI -- 4 Consistent Matting for Light Field Images -- 4.1 Pre-processing: Color Samples Collection -- 4.2 EPI Estimation and Propagation -- 4.3 Color Sample Selection -- 4.4 Consistent Matting with the EPI Smoothness Term -- 5 Experimental Results -- 5.1 Light Field Matting Dataset -- 5.2 Evaluations -- 5.3 Comparisons -- 6 Limitation and Discussion -- 7 Conclusion -- References -- Consensus of Regression for Occlusion-Robust Facial Feature Localization -- 1 Introduction -- 2 Related Work -- 3 Localization through Occlusion-Robust Regression -- 3.1 Occlusion-Specific Regressors -- 3.2 Consensus of Regression on Local Response Maps -- 3.3 Occlusion Inference -- 4 Results and Discussions -- 4.1 Experimental Setup -- 4.2 Evaluation on Facial Feature Localization -- 4.3 Evaluation on CoR Framework -- 4.4 Evaluation on Occlusion Detection -- 5 Conclusions -- References.
Learning the Face Prior for Bayesian Face Recognition -- 1 Introduction -- 2 Related Work -- 3 Learning Identity Subspace -- 3.1 Notation -- 3.2 The Extended Model of MRD -- 3.3 The Construction of Identity Subspace -- 3.4 The Construction of Training Set for Bayesian Face -- 4 Learning the Distributions of Identity -- 4.1 Review of GPs and GPR -- 4.2 Gaussian Mixture Modeling with GPR -- 4.3 The Leave-Set-Out Method -- 4.4 Bayesian Face Recognition Using the Face Prior -- 4.5 Discussion -- 5 Experimental Results -- 5.1 Datasets -- 5.2 Parameter Setting -- 5.3 Performance Analysis of the Proposed Approach -- 5.4 Comparison with Other Bayesian Face Methods -- 5.5 Handling Large Poses -- 5.6 Handling Large Occlusions -- 5.7 Comparison with the State-of-Art Methods -- 6 Conclusions -- References -- Spatio-temporal Event Classification Using Time-Series Kernel Based Structured Sparsity -- 1 Introduction -- 2 Methods -- 2.1 Facial Feature Point Localization -- 2.2 Global Alignment Kernel -- 2.3 Time-series Classification using SVM -- 2.4 Multi-class Classification of Time Series Using Structured Sparsity -- 3 Experiments -- 3.1 Datasets -- 3.2 Time-Series Dictionary Building -- 3.3 Gesture Classification on 6DMG -- 3.4 Emotional Expression Classification on CK+ -- 3.5 Action Unit Onset Classification on GFT50 -- 4 Conclusions -- References -- Feature Disentangling Machine - A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 A Brief Review on Sparse Support Vector Machine -- 3.2 Formulation for the FDM -- 3.3 Algorithm for Solving Feature Disentangling Machine -- 3.4 Computational Complexity -- 4 Experimental Results -- 4.1 Experiments on the CK+ Database -- 4.2 Experiments on the JAFFE Database -- 5 Conclusion and Future Work -- References.
Joint Unsupervised Face Alignment and Behaviour Analysis -- 1 Introduction -- 2 Method -- 2.1 Definitions and Prerequisites -- 2.2 Autoregressive Component Analysis with Spatial Alignment -- 3 Comparison with State-of-the-Art Component Analysis Techniques -- 4 Experiments -- 4.1 Spatio-temporal Behaviour Analysis Results in MMI Database -- 4.2 Behaviour Analysis of Spontaneous Smiles in UVS Database -- 4.3 Landmark Points Localization Results -- 5 Conclusions -- References -- Learning a Deep Convolutional Network for Image Super-Resolution -- 1 Introduction -- 2 Related Work -- 3 Convolutional Neural Networks for Super-Resolution -- 3.1 Formulation -- 3.2 Relationship to Sparse-Coding-Based Methods -- 3.3 Loss Function -- 4 Experiments -- 4.1 Quantitative Evaluation -- 4.2 Running Time -- 5 Further Analyses -- 5.1 Learned Filters for Super-Resolution -- 5.2 Learning Super-Resolution from ImageNet -- 5.3 Filter Number -- 5.4 Filter Size -- 6 Conclusion -- References -- Discriminative Indexing for Probabilistic Image Patch Priors -- 1 Introduction -- 2 Observations and Our General Framework -- 2.1 Background and Notations -- 2.2 Observations and Our Approach -- 3 Index-Assisted Patch Prior Optimization -- 4 Prior Index Construction -- 5 Experiments -- 5.1 Evaluation on Non-blind Image Deblurring -- 5.2 Evaluation on Prior Indexing and Parameter Tuning -- 5.3 Deblurring High-Resolution Photos from Real Life -- 5.4 Evaluation on Image Denoising -- 6 Conclusion -- References -- Modeling Video Dynamics with Deep Dynencoder -- 1 Introduction -- 2 Model Description -- 2.1 Dynencoder -- 2.2 Deep Dynencoder -- 2.3 Discussion -- 3 Vision Applications of Deep Dynencoder -- 3.1 DT Synthesis -- 3.2 Video Classification -- 3.3 Video Segmentation -- 4 Experiments -- 4.1 DT Synthesis -- 4.2 Traffic Scene Classification -- 4.3 Motion Segmentation.
5 Conclusion and Discussion -- References -- Good Image Priors for Non-blind Deconvolution: -- 1 Introduction -- 2 Overview -- 3 Patch-Pyramid Prior -- 3.1 Optimization -- 3.2 Z-Step -- 3.3 X-Step -- 4 Locally Adapted Priors -- 5 How Do Example Images Help? -- 6 Comparison to Leading Methods -- 6.1 Synthetically Blurred Images -- 6.2 Real Photos with Unknown Blur -- 6.3 Limitations -- 7 Conclusion -- References -- Image Deconvolution Ringing Artifact Detection and Removal via PSF Frequency Analysis -- 1 Introduction -- 2 Ringing Artifact Detection -- 2.1 Using Gabor Filters -- 2.2 Artifact Detection Algorithm -- 3 Ringing Artifact Removal -- 3.1 f Sub-problem -- 3.2 u Sub-problem -- 3.3 Summary of the Artifact Removal Algorithm -- 4 Experimental Results -- 5 Conclusions -- References -- View-Consistent 3D Scene Flow Estimation over Multiple Frames -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 View-Consistent Data Term -- 3.2 Shape and Motion Regularization -- 3.3 Spatial Segmentation Regularization -- 3.4 Multiple Frame Extension -- 3.5 Optimization and Proposal Generation -- 4 Evaluation -- 4.1 Qualitative Evaluation -- 4.2 KITTI Benchmark -- 5 Conclusion -- References -- Hand Waving Away Scale -- 1 Introduction -- 2 Related Work -- 2.1 Non-IMU Methods -- 2.2 IMU Methods -- 3 Recovery of Scale -- 3.1 In One Dimension -- 3.2 In Three Dimensions -- 3.3 Temporal Alignment -- 3.4 Gravity as a Friend -- 3.5 Classifying Useful Data -- 4 Experiments -- 4.1 Chessboard Experiments -- 4.2 Measuring Pupil Distance -- 4.3 3D Scanning -- 5 Conclusion -- References -- A Non-Linear Filter for Gyroscope-Based Video Stabilization -- 1 Introduction -- 2 Background and Prior Work -- 3 Algorithm Description -- 3.1 Camera Tracking Using the Gyroscope -- 3.2 Motion Model and Smoothing Algorithm -- 3.3 Output Synthesis and Rolling-Shutter Correction.
3.4 Parameter Selection.
Record Nr. UNINA-9910483311703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 854 p. 357 illus.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10605-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Organization -- Table of Contents -- Learning and Inference (continued) -- Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment -- 1 Introduction -- 2 Related Works -- 2.1 Local Models with Regression Fitting -- 2.2 Deep Models -- 3 Coarse-to-Fine Auto-Encoder Networks -- 3.1 Method Overview -- 3.2 Global SAN -- 3.3 Local SANs -- 3.4 Discussions -- 4 Implementation Details -- 5 Experiments -- 5.1 Datasets and Methods for Comparison -- 5.2 Investigation of Each SAN in CFAN -- 5.3 Comparison on XM2VTS Dataset -- 5.4 Comparison on LFPW Dataset -- 5.5 Comparison on Helen Dataset -- 6 Conclusions and Future Works -- References -- From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices -- 1 Introduction -- 2 Related Work -- 3 Riemannian Geometry of SPD Manifolds -- 4 Geometry-Aware Dimensionality Reduction -- 4.1 Optimization on Grassmann Manifolds -- 4.2 Designing the Affinity Matrix -- 4.3 Discussion in Relation to Region Covariance Descriptors -- 5 Empirical Evaluation -- 5.1 Material Categorization -- 5.2 Action Recognition from Motion Capture Data -- 5.3 Face Recognition -- 6 Conclusions and Future Work -- References -- Pose Machines: Articulated Pose Estimation via Inference Machines -- 1 Introduction -- 2 Related Work -- 3 Pose Inference Machines -- 3.1 Background -- 3.2 Incorporating a Hierarchy -- 3.3 Context Features -- 3.4 Training -- 3.5 Stacking -- 3.6 Inference -- 3.7 Implementation -- 4 Evaluation -- 5 Discussion -- References -- Poster Session 2 -- Piecewise-Planar StereoScan: Structure and Motion from Plane Primitives -- 1 Introduction -- 1.1 Related Work -- 2 Background -- 2.1 Energy-Based Multi-Model Fitting -- 2.2 Semi-dense Piecewise Planar Stereo Reconstruction -- 3 Overview of the Approach -- 3.1 Semi-dense PPR from a Single Stereo Pair.
3.2 PPR from a Stereo Sequence -- 4 Relative Pose Estimation -- 4.1 Relative Pose from 3 Plane Correspondences -- 4.2 Relative Pose Estimation in Case Ni Has Rank 2 -- 4.3 Relative Pose Estimation in Case Ni Has Rank 1 -- 4.4 Robust Algorithm for Computing the Relative Pose -- 5 Discrete-Continuous Bundle Adjustment -- 6 Experimental Results -- 7 Conclusions -- References -- Nonrigid Surface Registration and Completion from RGBD Images -- 1 Introduction -- 2 Related Work -- 3 Nonrigid Surface Registration and Completion -- 3.1 Nonrigid Patch-Based Surface Model -- 3.2 Nonrigid Registration as Inference in a CRF -- 3.3 Incorporating New Patches -- 4 Experimental Results -- 4.1 Comparison with the Baselines -- 4.2 Missing Data and Occlusions -- 4.3 Incorporating New Patches -- 4.4 Video Editing -- 5 Conclusion -- References -- Unsupervised Dense Object Discovery, Detection, Tracking and Reconstruction -- 1 Introduction -- 2 Overview -- 3 Discovery and Detection -- 4 Tracking and Reconstruction -- 4.1 Tracking -- 4.2 Reconstruction -- 4.3 Tracking and Reconstruction Interaction -- 5 System Integration -- 6 Results and Discussion -- 7 Failure Cases and Future Work -- 8 Conclusions -- References -- Know Your Limits: Accuracy of Long Range Stereoscopic Object Measurements in Practice -- 1 Introduction -- 2 Related Work -- 3 Long Range Object Stereo: Algorithm Overview -- 3.1 Local Differential Matching (LDM) -- 3.2 Joint Matching and Segmentation (SEG) -- 3.3 Total Variation Stereo (TV) -- 3.4 Semi-Global Matching (SGM) -- 4 Evaluation -- 4.1 Dataset -- 4.2 Performance Measures -- 5 Results and Analysis -- 6 Conclusions -- References -- As-Rigid-As-Possible Stereo under Second Order Smoothness Priors -- 1 Introduction -- 1.1 Background -- 1.2 Contribution -- 2 As-Rigid-As-Possible Stereo -- 2.1 Second-Order Smoothness Priors.
2.2 As-Rigid-As-Possible Smoothness and Data Cost -- 2.3 Overall Energy -- 2.4 Interactions between the Two Priors -- 2.5 Optimization -- 3 Implementation -- 3.1 Initialize -- 3.2 Optimize ED -- 3.3 Optimize ES -- 3.4 Post-process -- 4 Experiments -- 4.1 Comparisons of Results -- 4.2 Running Time -- 5 Conclusion -- References -- Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional -- 1 Introduction -- 1.1 The Mumford-Shah Problem -- 1.2 Related Work -- 1.3 Contribution -- 2 Proposed Finite-Difference Discretization -- 3 Minimization Algorithm -- 3.1 Algorithm for Convex Regularizers R -- 3.2 Proposed Algorithm for the MS-Energy -- 4 Experiments -- 4.1 Energy in One-Dimensional Case -- 4.2 Comparison with Convex Relaxation -- 4.3 Comparison with Ambrosio-Tortorelli -- 4.4 Comparison with L0-Smoothing -- 4.5 Real-Time Unsupervised Image Segmentation -- 4.6 Real-Time Video Cartooning -- 5 Conclusion -- References -- A MAP-Estimation Framework for Blind Deblurring Using High-Level Edge Priors -- 1 Introduction -- 2 Our Blind Deconvolution Approach -- 2.1 Data Term Edata(k, x|I) -- 2.2 Blur Kernel Prior Term Ekernel(k) -- 2.3 Image Prior Term Eimg(x|e) -- 2.4 Edge Prior Term Eedge(e|x) -- 3 Geometric Parsing Prior for Blind Deconvolution -- 4 MAP-Estimation Inference -- 4.1 Optimizing over the Kernel k -- 4.2 Optimizing over the Latent Image -- 4.3 Optimizing over the Edge-Related Variables e -- 4.4 Multi-resolution Inference -- 5 Experimental Results -- 6 Conclusions -- References -- Efficient Color Constancy with Local Surface Reflectance Statistics -- 1 Introduction -- 2 Color Constancy with Local Surface Reflectance Estimation -- 2.1 Surface Reflectance Estimation in Local Region -- 2.2 Illuminant Estimation -- 3 Experimental Results -- 3.1 Real-World Image Set -- 3.2 An Indoor Image Dataset in Laboratory.
3.3 SFU Grey Ball Image Datasets -- 3.4 SFU HDR Dataset -- 4 Discussion and Conclusion -- 5 Appendix -- References -- A Contrast Enhancement Framework with JPEG Artifacts Suppression -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Structure-Texture Decomposition -- 3.2 Reducing Artifacts in the Texture Layer -- 3.3 Layer Recomposition -- 4 Results -- 5 Discussion and Conclusion -- References -- Radial Bright Channel Prior for Single Image Vignetting Correction -- 1 Introduction -- 2 Related Work -- 3 Radial Bright Channel Prior -- 4 Vignetting Correction Using RBC Prior -- 4.1 Simple Estimation of the Vignetting Function -- 4.2 Model-Based Vignetting Estimation with Outlier Handling -- 4.3 Restoring the Vignetting-Free Image -- 5 Results -- 5.1 Synthetic Examples -- 5.2 Real Examples -- 5.3 Computation Time -- 6 Discussion and Future Work -- References -- Tubular Structure Filtering by Ranking Orientation Responses of Path Operators -- 1 Introduction -- 2 Related Works -- 2.1 Differential Filters -- 2.2 Non-linear Filters -- 3 General Strategy -- 4 Ranking Orientation Responses of Path Operators -- 4.1 Path Operators -- 4.2 RPO-Based Filtering -- 4.3 Orientation Space Sampling -- 4.4 Cone-Oriented Robust Path Opening -- 4.5 Pointwise Rank Filtering -- 4.6 RORPO: A Filter Based on Ranking Orientations Responses Path Operator -- 4.7 Suppressing Artifacts Generated by Limit Cases -- 5 Experiments and Results -- 5.1 ComparedMethods and Quality Scores -- 5.2 Synthetic Images -- 5.3 Real Images -- 6 Discussion and Conclusion -- References -- Optimization-Based Artifact Correction for Electron Microscopy Image Stacks -- 1 Introduction -- 2 Artifact Correction Algorithm -- 2.1 Problem Formulation -- 2.2 Coarse-to-Fine Procedure -- 2.3 Removing the Blocking Effects -- 2.4 Parallelization -- 3 Evaluation on Electron Microscopy Data.
3.1 Image Quality Evaluation -- 3.2 Segmentation Accuracy Evaluation -- 4 Electron Microscopy Results -- 4.1 Comparison of NIQE Scores -- 4.2 Comparison of Segmentation Accuracy -- 5 Lighting Correction of Time-Lapse Photography -- 6 Discussion -- References -- Metric-Based Pairwise and Multiple Image Registration -- 1 Introduction -- 1.1 Desired Properties in an Objective Function -- 1.2 Past and Current Literature -- 2 Metric-BasedImage Registration -- 2.1 Image Representation and Pairwise Registration -- 2.2 Gradient Method for Optimization Over Γ -- 2.3 Distance in the Quotient Space -- 3 Experiments -- 3.1 Pairwise Image Registration -- 3.2 Registering Multiple Images -- 3.3 Image Classification -- 4 Conclusion -- References -- Canonical Correlation Analysis on Riemannian Manifolds and Its Applications -- 1 Introduction -- 2 Canonical Correlation in Euclidean Space -- 3 Mathematical Preliminaries -- 4 A Model for CCA on Riemannian Manifolds -- 5 Optimization Schemes -- 5.1 An Augmented Lagrangian Method -- 5.2 Extensions to the Product Riemannian Manifold -- 6 Experiments -- 6.1 CCA on SPD Manifolds -- 6.2 Synthetic Experiments -- 6.3 CCA for Multi-modal Risk Analysis -- 7 Conclusion -- References -- Scalable 6-DOF Localization on Mobile Devices -- 1 Introduction -- 2 Overall Approach -- 3 Local and Global Pose Estimation -- 3.1 Local Pose Tracking Using SLAM -- 3.2 Server-Based Global Localization -- 4 Aligning the Local Map Globally -- 5 Experimental Evaluation -- 5.1 Comparison of the Proposed Alignment Strategies -- 5.2 Accuracy, Efficiency and Scalability of Pose Estimation -- 6 Conclusion and Future Work -- References -- On Mean Pose and Variability of 3D Deformable Models -- 1 Introduction -- 2 Related Work -- 3 Mean Pose Inference Model -- 3.1 Shape Space Parameterization -- 3.2 Mean Pose -- 3.3 Generative Model.
3.4 Expectation-Maximization Inference.
Record Nr. UNINA-9910484526003321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 853 p. 379 illus.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10602-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Video Registration to SfM Models -- Soft Cost Aggregation with Multi-resolution Fusion -- Inverse Kernels for Fast Spatial Deconvolution -- Deep Network Cascade for Image Super-resolution -- Spectral Edge Image Fusion: Theory and Applications -- Spatio-chromatic Opponent Features -- Modeling Perceptual Color Differences by Local Metric Learning -- Online Graph-Based Tracking -- Fast Visual Tracking via Dense Spatio-temporal Context Learning -- Extended Lucas-Kanade Tracking -- Appearances Can Be Deceiving: Learning Visual Tracking from Few Trajectory Annotations -- Generalized Background Subtraction Using Superpixels with Label Integrated Motion Estimation -- Spectra Estimation of Fluorescent and Reflective Scenes by Using Ordinary Illuminants -- Interreflection Removal Using Fluorescence -- Intrinsic Face Image Decomposition with Human Face Priors -- Recovering Scene Geometry under Wavy Fluid via Distortion and Defocus Analysis -- Human Detection Using Learned Part Alphabet and Pose Dictionary -- SPADE: Scalar Product Accelerator by Integer Decomposition for Object Detection -- Detecting Snap Points in Egocentric Video with a Web Photo Prior -- Towards Unified Object Detection and Semantic Segmentation -- Foreground Consistent Human Pose Estimation Using Branch and Bound -- Human Pose Estimation with Fields of Parts.-Unsupervised Video Adaptation for Parsing Human Motion -- Training Object Class Detectors from Eye Tracking Data -- Symmetric Objects -- Edge Boxes: Locating Object Proposals from Edges -- Training Deformable Object Models for Human Detection Based on Alignment and Clustering -- Predicting Actions from Static Scenes -- Exploiting Privileged Information from Web Data for Image Categorization -- Multi-modal Unsupervised Feature Learning for RGB-D Scene Labeling -- Discriminatively Trained Dense Surface Normal Estimation -- Numerical Inversion of SRNFs for Efficient Elastic Shape Analysis of Star-Shaped Objects Classification -- Learning Where to Classify in Multi-view Semantic Segmentation -- Semantics: A Medium-Level Model for Real-Time Semantic Scene Understanding -- Sparse Dictionaries for Semantic Segmentation -- Video Action Detection with Relational Dynamic-Poselets -- Action Recognition with Stacked Fisher Vectors -- A Discriminative Model with Multiple Temporal Scales for Action Prediction -- Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions -- Weakly Supervised Action Labeling in Videos under Ordering Constraints -- Active Random Forests: An Application to Autonomous Unfolding of Clothes -- Model-Free Segmentation and Grasp Selection of Unknown Stacked Objects -- Convexity Shape Prior for Segmentation -- Pseudo-bound Optimization for Binary Energies -- A Closer Look at Context: From Coxels to the Contextual Emergence of Object Saliency -- Geodesic Object Proposals -- Microsoft COCO: Common Objects in Context -- Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation -- Robust Bundle Adjustment Revisited -- Accurate Intrinsic Calibration of Depth Camera with Cuboids -- Statistical Pose Averaging with Non-isotropic and Incomplete Relative Measurements -- A Pot of Gold: Rainbows as a Calibration Cue -- Let There Be Color! Large-Scale Texturing of 3D Reconstructions.
Record Nr. UNINA-9910484799603321
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Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VII / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VII / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVI, 632 p. 261 illus.)
Disciplina 006.6
006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10584-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Person Re-Identification Using Kernel-Based Metric Learning Methods -- Saliency in Crowd -- Webpage Saliency -- Deblurring Face Images with Exemplars -- Sparse Spatio-spectral Representation for Hyperspectral Image Super-resolution -- Hybrid Image Deblurring by Fusing Edge and Power Spectrum Information -- Affine Subspace Representation for Feature Description -- A Generative Model for the Joint Registration of Multiple Point Sets -- Change Detection in the Presence of Motion Blur and Rolling Shutter Effect -- An Analysis of Errors in Graph-Based Keypoint Matching and Proposed Solutions -- OpenDR: An Approximate Differentiable Renderer -- A Superior Tracking Approach: Building a Strong Tracker through Fusion -- Training-Based Spectral Reconstruction from a Single RGB Image -- On Shape and Material Recovery from Motion -- Intrinsic Image Decomposition Using Structure-Texture Separation and Surface Normals -- Multi-level Adaptive Active Learning for Scene Classification -- Graph Cuts for Supervised Binary Coding -- Planar Structure Matching under Projective Uncertainty for Geolocation -- Active Deformable Part Models Inference -- Simultaneous Detection and Segmentation -- Learning Graphs to Model Visual Objects across Different Depictive Styles -- Analyzing the Performance of Multilayer Neural Networks for Object Recognition -- Learning Rich Features from RGB-D Images for Object Detection and Segmentation -- Scene Classification via Hypergraph-Based Semantic Attributes Subnetworks Identification -- OTC: A Novel Local Descriptor for Scene Classification -- Multi-scale Orderless Pooling of Deep Convolutional Activation Features -- Expanding the Family of Grassmannian Kernels: An Embedding Perspective -- Image Tag Completion by Noisy Matrix Recovery -- ConceptMap: Mining Noisy Web Data for Concept Learning -- Shrinkage Expansion Adaptive Metric Learning -- Salient Montages from Unconstrained Videos -- Action-Reaction: Forecasting the Dynamics of Human Interaction -- Creating Summaries from User Videos -- Spatiotemporal Background Subtraction Using Minimum Spanning Tree and Optical Flow -- Robust Foreground Detection Using Smoothness and Arbitrariness Constraints -- Video Object Co-segmentation by Regulated Maximum Weight Cliques -- Dense Semi-rigid Scene Flow Estimation from RGBD Images -- Video Pop-up: Monocular 3D Reconstruction of Dynamic Scenes -- Joint Object Class Sequencing and Trajectory Triangulation (JOST) -- Scene Chronology.
Record Nr. UNINA-9910481953703321
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Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part IV / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part IV / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 848 p. 340 illus.)
Disciplina 006.6
006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10593-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Organization -- Table of Contents -- Poster Session 4 (continued) -- Schwarps: Locally Projective Image Warps Based on 2D Schwarzian Derivatives -- 1 Introduction -- 2 Background on Projective Differential Invariants -- 2.1 The Cross-Ratio -- 2.2 The 1D Schwarzian Derivative -- 2.3 Multidimensional Schwarzian Derivatives (MSDs) -- 3 Schwarzian Equations in Two Dimensions -- 3.1 The 1D Schwarzian Derivative -- 3.2 2D Schwarzian Equations -- 4 Modeling the Projection of Deforming Surfaces -- 4.1 The Schwarp -- 5 Experimental Results -- 5.1 Implementation Details -- 5.2 Synthetic Data -- 5.3 Real Data -- 6 Conclusion -- References -- gDLS: A Scalable Solution to the Generalized Pose and Scale Problem -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Solution Method -- 4.1 A New Least Squares Cost Function -- 4.2 Macaulay Matrix Solution -- 5 Experiments -- 5.1 Numerical Stability -- 5.2 Simulations with Noisy Synthetic Data -- 5.3 SLAM Registration with Real Images -- 5.4 Runtime Analysis -- 6 Conclusion -- Appendix -- References -- Generalized Connectivity Constraints for Spatio-temporal 3D Reconstruction -- 1 Introduction -- 1.1 Contributions -- 1.2 Related Work -- 2 3D Reconstruction with Connectivity Constraints -- 2.1 Spatio-temporal Multi-view Reconstruction -- 2.2 Connectivity Constraints via Directed Graphs -- 3 Generalized Connectivity Constraints for Objects of Arbitrary Genus -- 3.1 Handle and Tunnel Loops -- 3.2 Loop Connectivity Constraints -- 4 Numerical Optimization -- 5 Experiments -- 6 Conclusion -- References -- Passive Tomography of Turbulence Strength -- 1 The Need to Recover Turbulence Strength -- 2 Theoretical Background -- 2.1 Turbulence Statistics and Refraction -- 2.2 Linear Tomography -- 3 Principle of C2n Tomography -- 3.1 Numeric Tomographic Recovery of C2n -- 4 Simulation.
5 Experiments -- 5.1 Laboratory -- 5.2 Outdoors -- 6 Discussion -- References -- A Non-local Method for Robust Noisy Image Completion -- 1 Introduction -- 2 Related Works -- 3 The Proposed Algorithm -- 3.1 Overview -- 3.2 Robust Patch Matching and Grouping -- 3.3 Collaborative Filtering Using Low-Rank Matrix Completion -- 4 Implementation Details and Experiments -- 4.1 Implementation Details -- 4.2 Results and Comparisons -- 5 Conclusions and Future Works -- References -- Improved Motion Invariant Deblurring through Motion Estimation -- 1 Introduction -- 2 Previous Work -- 3 Motion Invariant Capture -- 3.1 Motion Invariance Artifacts -- 4 Artifact-Based Motion Estimation -- 5 Experiments -- 5.1 Synthetic Data -- 5.2 Real Camera Images -- 6 Limitations -- 7 Multiple Moving Objects -- 8 Conclusion -- References -- Consistent Matting for Light Field Images -- 1 Introduction -- 2 Related Works -- 3 EPI in Light Field Images -- 3.1 The EPI Constraint -- 3.2 Color Sample Correspondences in EPI -- 4 Consistent Matting for Light Field Images -- 4.1 Pre-processing: Color Samples Collection -- 4.2 EPI Estimation and Propagation -- 4.3 Color Sample Selection -- 4.4 Consistent Matting with the EPI Smoothness Term -- 5 Experimental Results -- 5.1 Light Field Matting Dataset -- 5.2 Evaluations -- 5.3 Comparisons -- 6 Limitation and Discussion -- 7 Conclusion -- References -- Consensus of Regression for Occlusion-Robust Facial Feature Localization -- 1 Introduction -- 2 Related Work -- 3 Localization through Occlusion-Robust Regression -- 3.1 Occlusion-Specific Regressors -- 3.2 Consensus of Regression on Local Response Maps -- 3.3 Occlusion Inference -- 4 Results and Discussions -- 4.1 Experimental Setup -- 4.2 Evaluation on Facial Feature Localization -- 4.3 Evaluation on CoR Framework -- 4.4 Evaluation on Occlusion Detection -- 5 Conclusions -- References.
Learning the Face Prior for Bayesian Face Recognition -- 1 Introduction -- 2 Related Work -- 3 Learning Identity Subspace -- 3.1 Notation -- 3.2 The Extended Model of MRD -- 3.3 The Construction of Identity Subspace -- 3.4 The Construction of Training Set for Bayesian Face -- 4 Learning the Distributions of Identity -- 4.1 Review of GPs and GPR -- 4.2 Gaussian Mixture Modeling with GPR -- 4.3 The Leave-Set-Out Method -- 4.4 Bayesian Face Recognition Using the Face Prior -- 4.5 Discussion -- 5 Experimental Results -- 5.1 Datasets -- 5.2 Parameter Setting -- 5.3 Performance Analysis of the Proposed Approach -- 5.4 Comparison with Other Bayesian Face Methods -- 5.5 Handling Large Poses -- 5.6 Handling Large Occlusions -- 5.7 Comparison with the State-of-Art Methods -- 6 Conclusions -- References -- Spatio-temporal Event Classification Using Time-Series Kernel Based Structured Sparsity -- 1 Introduction -- 2 Methods -- 2.1 Facial Feature Point Localization -- 2.2 Global Alignment Kernel -- 2.3 Time-series Classification using SVM -- 2.4 Multi-class Classification of Time Series Using Structured Sparsity -- 3 Experiments -- 3.1 Datasets -- 3.2 Time-Series Dictionary Building -- 3.3 Gesture Classification on 6DMG -- 3.4 Emotional Expression Classification on CK+ -- 3.5 Action Unit Onset Classification on GFT50 -- 4 Conclusions -- References -- Feature Disentangling Machine - A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 A Brief Review on Sparse Support Vector Machine -- 3.2 Formulation for the FDM -- 3.3 Algorithm for Solving Feature Disentangling Machine -- 3.4 Computational Complexity -- 4 Experimental Results -- 4.1 Experiments on the CK+ Database -- 4.2 Experiments on the JAFFE Database -- 5 Conclusion and Future Work -- References.
Joint Unsupervised Face Alignment and Behaviour Analysis -- 1 Introduction -- 2 Method -- 2.1 Definitions and Prerequisites -- 2.2 Autoregressive Component Analysis with Spatial Alignment -- 3 Comparison with State-of-the-Art Component Analysis Techniques -- 4 Experiments -- 4.1 Spatio-temporal Behaviour Analysis Results in MMI Database -- 4.2 Behaviour Analysis of Spontaneous Smiles in UVS Database -- 4.3 Landmark Points Localization Results -- 5 Conclusions -- References -- Learning a Deep Convolutional Network for Image Super-Resolution -- 1 Introduction -- 2 Related Work -- 3 Convolutional Neural Networks for Super-Resolution -- 3.1 Formulation -- 3.2 Relationship to Sparse-Coding-Based Methods -- 3.3 Loss Function -- 4 Experiments -- 4.1 Quantitative Evaluation -- 4.2 Running Time -- 5 Further Analyses -- 5.1 Learned Filters for Super-Resolution -- 5.2 Learning Super-Resolution from ImageNet -- 5.3 Filter Number -- 5.4 Filter Size -- 6 Conclusion -- References -- Discriminative Indexing for Probabilistic Image Patch Priors -- 1 Introduction -- 2 Observations and Our General Framework -- 2.1 Background and Notations -- 2.2 Observations and Our Approach -- 3 Index-Assisted Patch Prior Optimization -- 4 Prior Index Construction -- 5 Experiments -- 5.1 Evaluation on Non-blind Image Deblurring -- 5.2 Evaluation on Prior Indexing and Parameter Tuning -- 5.3 Deblurring High-Resolution Photos from Real Life -- 5.4 Evaluation on Image Denoising -- 6 Conclusion -- References -- Modeling Video Dynamics with Deep Dynencoder -- 1 Introduction -- 2 Model Description -- 2.1 Dynencoder -- 2.2 Deep Dynencoder -- 2.3 Discussion -- 3 Vision Applications of Deep Dynencoder -- 3.1 DT Synthesis -- 3.2 Video Classification -- 3.3 Video Segmentation -- 4 Experiments -- 4.1 DT Synthesis -- 4.2 Traffic Scene Classification -- 4.3 Motion Segmentation.
5 Conclusion and Discussion -- References -- Good Image Priors for Non-blind Deconvolution: -- 1 Introduction -- 2 Overview -- 3 Patch-Pyramid Prior -- 3.1 Optimization -- 3.2 Z-Step -- 3.3 X-Step -- 4 Locally Adapted Priors -- 5 How Do Example Images Help? -- 6 Comparison to Leading Methods -- 6.1 Synthetically Blurred Images -- 6.2 Real Photos with Unknown Blur -- 6.3 Limitations -- 7 Conclusion -- References -- Image Deconvolution Ringing Artifact Detection and Removal via PSF Frequency Analysis -- 1 Introduction -- 2 Ringing Artifact Detection -- 2.1 Using Gabor Filters -- 2.2 Artifact Detection Algorithm -- 3 Ringing Artifact Removal -- 3.1 f Sub-problem -- 3.2 u Sub-problem -- 3.3 Summary of the Artifact Removal Algorithm -- 4 Experimental Results -- 5 Conclusions -- References -- View-Consistent 3D Scene Flow Estimation over Multiple Frames -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 View-Consistent Data Term -- 3.2 Shape and Motion Regularization -- 3.3 Spatial Segmentation Regularization -- 3.4 Multiple Frame Extension -- 3.5 Optimization and Proposal Generation -- 4 Evaluation -- 4.1 Qualitative Evaluation -- 4.2 KITTI Benchmark -- 5 Conclusion -- References -- Hand Waving Away Scale -- 1 Introduction -- 2 Related Work -- 2.1 Non-IMU Methods -- 2.2 IMU Methods -- 3 Recovery of Scale -- 3.1 In One Dimension -- 3.2 In Three Dimensions -- 3.3 Temporal Alignment -- 3.4 Gravity as a Friend -- 3.5 Classifying Useful Data -- 4 Experiments -- 4.1 Chessboard Experiments -- 4.2 Measuring Pupil Distance -- 4.3 3D Scanning -- 5 Conclusion -- References -- A Non-Linear Filter for Gyroscope-Based Video Stabilization -- 1 Introduction -- 2 Background and Prior Work -- 3 Algorithm Description -- 3.1 Camera Tracking Using the Gyroscope -- 3.2 Motion Model and Smoothing Algorithm -- 3.3 Output Synthesis and Rolling-Shutter Correction.
3.4 Parameter Selection.
Record Nr. UNISA-996202530403316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
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Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part III / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part III / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 851 p. 344 illus.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10578-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996198262203316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
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Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 853 p. 361 illus.)
Disciplina 006.6
006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10590-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Organization -- Table of Contents -- Tracking and Activity Recognition -- Visual Tracking by Sampling Tree-Structured Graphical Models -- 1 Introduction -- 2 Related Work -- 3 Main Framework -- 3.1 Learning Tree Structure by MCMC -- 3.2 Tracking on Tree Structure -- 4 Hierarchical Construction of Tree Structure -- 4.1 Tree Construction on Key Frames -- 4.2 Tree Extension by Manifold Alignment -- 5 Experiments -- 5.1 Datasets -- 5.2 Identified Tree Structure -- 5.3 Quantitative and Qualitative Performance -- 6 Conclusion -- References -- Tracking Interacting Objects Optimally Using Integer Programming -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Bayesian Inference -- 3.2 Flow Constraints -- 3.3 Mixed Integer Programming -- 3.4 Graph Size Reduction -- 4 Estimating Probabilities of Occupancy -- 4.1 Oriented Objects -- 4.2 Objects Off the Ground Plane -- 5 Experiments -- 5.1 Test Sequences -- 5.2 Parameters and Baselines -- 5.3 Results -- 6 Conclusion -- References -- Learning Latent Constituents for Recognition of Group Activities in Video -- 1 Introduction -- 2 Related Work -- 3 Learning Functional Constituents of Group Activities -- 3.1 Functional Grouping of Part Instances -- 3.2 From Constituent Classifiers to Activity Classification -- 3.3 Inference in Novel Query Scenes -- 3.4 Joint Learning of Group Activity and Constituent Classifiers -- 4 Experimental Results -- 4.1 Experimental Protocol -- 4.2 Group Activity Recognition -- 5 Conclusion -- References -- Recognition -- Large-Scale Object Classification Using Label Relation Graphs -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Hierarchy and Exclusion (HEX) Graphs -- 3.2 Classification Model -- 3.3 Efficient Inference -- 4 Experiments -- 4.1 Implementation -- 4.2 Object Classification on ImageNet.
4.3 Zero-Shot Recognition on Animals with Attributes -- 4.4 Efficiency of Inference -- 5 Discussions and Conclusions -- References -- 30Hz Object Detection with DPM V5 -- 1 Introduction -- 1.1 Prior Work -- 2 Pyramid of Features vs. Pyramid of Templates -- 3 Hierarchical Vector Quantization -- 4 Object Proposal Using Hash Table -- 4.1 Hash Codes -- 4.2 Priority Lists -- 4.3 Hash Table Initialization -- 5 Object Scoring -- 6 Experimental Results -- 7 Discussion -- References -- Knowing a Good HOG Filter When You See It: Efficient Selection of Filters for Detection -- 1 Introduction -- 1.1 Related Work -- 2 Background -- 2.1 An Overview of Poselets for Object Detection -- 2.2 An Overview of Exemplar SVMs for Object Detection -- 3 Ranking and Diversity -- 3.1 Learning to Rank Parts -- 3.2 Selecting a Diverse Set of Parts -- 3.3 Features for Part Ranking -- 3.4 The LDA Acceleration -- 4 Experiments with Poselets -- 4.1 Training the Ranking Algorithm -- 4.2 Training the Diversity Model -- 4.3 Selection Methods Considered -- 4.4 Ranking Results -- 4.5 PASCAL VOC Detection Results -- 5 Experiments with Exemplar SVMs -- 5.1 PASCAL VOC Detection Results -- 5.2 An Analysis of Bicycle HOG Filters -- 6 Conclusion -- References -- Linking People in Videos with "Their" Names Using Coreference Resolution -- 1 Introduction -- 2 Related Work -- 3 Problem Setup -- 4 Our Model -- 4.1 Regression-Based Clustering -- 4.2 Name Assignment to Tracks -- 4.3 Name Assignment to Mentions and Coreference Resolution -- 4.4 Alignment between Tracks and Mentions -- 5 Optimization -- 6 Experiments -- 6.1 Name Assignment to Tracks in Video -- 6.2 Name Assignment to Mentions -- 7 Conclusion -- References -- Poster Session 1 -- Optimal Essential Matrix Estimation via Inlier-Set Maximization -- 1 Introduction -- 1.1 Related Work -- 2 Essential Manifold Parametrization.
3 Optimization Criteria -- 4 Branch and Bound over D2 π × B3 π -- 4.1 Lower-Bound Computation -- 4.2 Upper-Bound Computation via Relaxation -- 4.3 Efficient Bounding with Closed-Form Feasibility Test -- 4.4 The Main Algorithm -- 5 Experiment Results -- 5.1 Synthetic Scene Test: Normal Cases -- 5.2 Synthetic Scene Test: Special Cases -- 5.3 Real Image Test -- 6 Conclusion and Future Work -- References -- UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability -- 1 Introduction -- 1.1 Related Work -- 2 Theory -- 2.1 Geometry of the Absolute Pose Problem -- 2.2 Derivation of the Objective Function -- 2.3 Universal, Closed-Form Least-Squares Solution -- 2.4 Comparison to a Lagrangian Formulation -- 2.5 Elimination of Two-Fold Symmetry -- 2.6 Second-Order Optimality and Root Polishing -- 3 Experimental Evaluation -- 3.1 The Central Case -- 3.2 The Non-central Case -- 3.3 Computational Efficiency -- 3.4 Results on Real Data -- 4 Conclusion -- References -- 3D Reconstruction of Dynamic Textures in Crowd Sourced Data -- 1 Introduction -- 2 Related Work -- 3 Initial Model Generation -- 3.1 Static Reconstruction from Photo Collections -- 3.2 Coarse Dynamic Textures Priors from Video -- 3.3 Coarse Static Background Priors from Video Frames -- 3.4 Graph-Cut Based Dynamic Texture Refinement -- 3.5 Shape from Silhouettes -- 4 Closed Loop 3D Shape Refinement -- 4.1 Geometry Based Video to Image Label Transfer -- 4.2 Mitigating Dynamic Texture in SfM Estimates -- 4.3 Building a Static Background Prior for Single Images -- 4.4 Mitigating of Non-uniform Spatial Sampling -- 5 Experiments -- 6 Conclusion -- References -- 3D Interest Point Detection via Discriminative Learning -- 1 Introduction -- 2 Related Work -- 3 Attributes and Learning -- 3.1 Basic Attributes -- 3.2 DoG Attributes -- 3.3 Random Forest -- 3.4 Imbalanced Classes.
4 Ground Truth and Experiments -- 4.1 Ground Truth -- 4.2 Experiments -- 4.3 Training and Predicting -- 4.4 Evaluation Criteria -- 4.5 Results -- 5 Conclusions -- References -- Pose Locality Constrained Representation for 3D Human Pose Reconstruction -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Problem Description -- 3.2 Hierarchical Pose Tree -- 3.3 Pose Locality for Reconstruction -- 3.4 Algorithm Summary -- 4 Experiments -- 4.1 Quantitative Results -- 4.2 Qualitative Evaluation -- 4.3 The Selection of Parameters dM and E -- 4.4 Distribution of Anchor-Node Depth -- 5 Conclusions -- References -- Synchronization of Two Independently Moving Cameras without Feature Correspondences -- 1 Introduction -- 1.1 Previous Work -- 1.2 Contributions -- 1.3 Notation and Paper Organization -- 2 Static and Jointly Moving Cameras -- 2.1 Video Synchronization -- 2.2 Uniqueness of Solution -- 3 Independently Moving Cameras -- 3.1 Video Synchronization -- 4 Object Motion Recovery -- 5 Experimental Results -- 6 Conclusions -- References -- Multi Focus Structured Light for Recovering Scene Shape and Global Illumination -- 1 Introduction -- 1.1 Related Work -- 2 Modeling Image Formation and Illumination -- 3 Illumination Control and Image Acquisition -- 4 Recovering Shape with Defocused Light Patterns -- 5 Recovering Direct and Global Illumination Components -- 6 Results -- 6.1 Depth Recovery -- 6.2 Recovering Direct and Global Illumination -- 7 Discussion -- References -- Coplanar Common Points in Non-centric Cameras -- 1 Introduction -- 2 Ray Space Analysis -- 2.1 CCPs in General Linear Cameras -- 2.2 Concentric Mosaics -- 3 CCPs in Catadioptric Mirrors -- 3.1 Ray Space vs. Caustics -- 3.2 Rotationally Symmetric Mirrors -- 3.3 Cylinder Mirrors -- 4 Experiments -- 4.1 Synthetic Experiment -- 4.2 Real Experiment -- 5 Conclusions and Discussions.
References -- SRA: Fast Removal of General Multipath for ToF Sensors -- 1 Introduction -- 1.1 Contributions -- 2 Prior Work -- 3 Sparse Reflections Analysis -- 3.1 The Multipath Representation -- 3.2 The SRA Algorithm -- 4 Fast Computation -- 5 Experiments -- 5.1 Running Time -- 5.2 General Multipath: Examples -- 5.3 Comprehensive Two-Path Evaluation -- 5.4 Real Images -- 6 Conclusions -- References -- Sub-pixel Layout for Super-Resolution with Images in the Octic Group -- 1 Introduction -- 1.1 Contributions -- 1.2 Related Work -- 2 Good Sub-pixel Layout for Super-Resolution -- 2.1 Single Image Case -- 2.2 Multiple Images in the Octic Group -- 2.3 Good Sub-pixel Layout -- 3 Reconstruction Algorithm -- 4 Performance Evaluation -- 4.1 Synthetic Test -- 4.2 Real Data Test -- 5 Discussion -- 6 Conclusion -- References -- Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 SFDL -- 3.2 Identification -- 3.3 Verification -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Experimental Settings -- 4.3 Results and Analysis -- 5 Conclusion and Future Work -- References -- Read My Lips: Continuous Signer Independent Weakly Supervised Viseme Recognition -- 1 Introduction -- 2 Mouthings in Sign Language, Challenging? -- 3 State of the Art -- 4 Corpora -- 5 Mouthing Features -- 6 Weakly Supervised Mouthing Recognition -- 6.1 Overview -- 6.2 Reordering Sentence Structure -- 6.3 Pronunciation Lexicon and Viseme Mapping -- 6.4 Training Viseme Models -- 6.5 Context-Dependent Visemes with a Visemic Classification and Regression Tree -- 6.6 Linear Discriminant Analysis -- 7 Results -- 8 Conclusions -- References -- Multilinear Wavelets: A Statistical Shape Space for Human Faces -- 1 Introduction -- 2 Related Work -- 3 Multilinear Wavelet Model.
3.1 Second Generation Spherical Wavelets.
Record Nr. UNISA-996198262103316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
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Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VI / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VI / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVI, 832 p. 351 illus.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10599-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto All-In-Focus Synthetic Aperture Imaging -- Photo Uncrop -- Solving Square Jigsaw Puzzles with Loop Constraints -- Geometric Calibration of Micro-Lens-Based Light-Field Cameras Using Line Features -- Spatio-temporal Matching for Human Detection in Video -- Collaborative Facial Landmark Localization for Transferring Annotations Across Datasets -- Facial Landmark Detection by Deep Multi-task Learning -- Joint Cascade Face Detection and Alignment -- Weighted Block-Sparse Low Rank Representation for Face Clustering in Videos -- Crowd Tracking with Dynamic Evolution of Group Structures -- Tracking Using Multilevel Quantizations -- Occlusion and Motion Reasoning for Long-Term Tracking -- MEEM: Robust Tracking via Multiple Experts Using Entropy Minimization -- Robust Motion Segmentation with Unknown Correspondences -- Monocular Multiview Object Tracking with 3D Aspect Parts -- Modeling Blurred Video with Layers -- Efficient Image and Video Co-localization with Frank-Wolfe Algorithm -- Non-parametric Higher-Order Random Fields for Image Segmentation -- Co-Sparse Textural Similarity for Interactive Segmentation -- A Convergent Incoherent Dictionary Learning Algorithm for Sparse Coding -- Free-Shape Polygonal Object Localization -- Interactively Guiding Semi-Supervised Clustering via Attribute-Based Explanations -- Attributes Make Sense on Segmented Objects -- Towards Transparent Systems: Semantic Characterization of Failure Modes -- Orientation Covariant Aggregation of Local Descriptors with Embeddings -- Similarity-Invariant Sketch-Based Image Retrieval in Large Databases -- Discovering Object Classes from Activities -- Weakly Supervised Object Localization with Latent Category Learning -- Food-101 – Mining Discriminative Components with Random Forests -- Latent-Class Hough Forests for 3D Object Detection and Pose Estimation -- FPM: Fine Pose Parts-Based Model with 3D CAD Models -- Learning High-Level Judgments of Urban Perception -- CollageParsing: Nonparametric Scene Parsing by Adaptive Overlapping Windows -- Discovering Video Clusters from Visual Features and Noisy Tags -- Category-Specific Video Summarization -- Assessing the Quality of Actions -- HiRF: Hierarchical Random Field for Collective Activity Recognition in Videos -- Part Bricolage: Flow-Assisted Part-Based Graphs for Detecting Activities in Videos -- GIS-Assisted Object Detection and Geospatial Localization -- Context-Based Pedestrian Path Prediction -- Sliding Shapes for 3D Object Detection in Depth Images -- Integrating Context and Occlusion for Car Detection by Hierarchical And-Or Model -- PanoContext: A Whole-Room 3D Context Model for Panoramic Scene Understanding -- Unfolding an Indoor Origami World -- Joint Semantic Segmentation and 3D Reconstruction from Monocular Video -- A New Variational Framework for Multiview Surface Reconstruction -- Multi-body Depth-Map Fusion with Non-intersection Constraints -- Shape from Light Field Meets Robust PCA -- Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval -- Reverse Training: An Efficient Approach for Image Set Classification -- Real-Time Exemplar-Based Face Sketch Synthesis -- Domain-Adaptive Discriminative One-Shot Learning of Gestures.
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
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Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXVIII, 854 p. 357 illus.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Computer Graphics
ISBN 3-319-10605-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Organization -- Table of Contents -- Learning and Inference (continued) -- Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment -- 1 Introduction -- 2 Related Works -- 2.1 Local Models with Regression Fitting -- 2.2 Deep Models -- 3 Coarse-to-Fine Auto-Encoder Networks -- 3.1 Method Overview -- 3.2 Global SAN -- 3.3 Local SANs -- 3.4 Discussions -- 4 Implementation Details -- 5 Experiments -- 5.1 Datasets and Methods for Comparison -- 5.2 Investigation of Each SAN in CFAN -- 5.3 Comparison on XM2VTS Dataset -- 5.4 Comparison on LFPW Dataset -- 5.5 Comparison on Helen Dataset -- 6 Conclusions and Future Works -- References -- From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices -- 1 Introduction -- 2 Related Work -- 3 Riemannian Geometry of SPD Manifolds -- 4 Geometry-Aware Dimensionality Reduction -- 4.1 Optimization on Grassmann Manifolds -- 4.2 Designing the Affinity Matrix -- 4.3 Discussion in Relation to Region Covariance Descriptors -- 5 Empirical Evaluation -- 5.1 Material Categorization -- 5.2 Action Recognition from Motion Capture Data -- 5.3 Face Recognition -- 6 Conclusions and Future Work -- References -- Pose Machines: Articulated Pose Estimation via Inference Machines -- 1 Introduction -- 2 Related Work -- 3 Pose Inference Machines -- 3.1 Background -- 3.2 Incorporating a Hierarchy -- 3.3 Context Features -- 3.4 Training -- 3.5 Stacking -- 3.6 Inference -- 3.7 Implementation -- 4 Evaluation -- 5 Discussion -- References -- Poster Session 2 -- Piecewise-Planar StereoScan: Structure and Motion from Plane Primitives -- 1 Introduction -- 1.1 Related Work -- 2 Background -- 2.1 Energy-Based Multi-Model Fitting -- 2.2 Semi-dense Piecewise Planar Stereo Reconstruction -- 3 Overview of the Approach -- 3.1 Semi-dense PPR from a Single Stereo Pair.
3.2 PPR from a Stereo Sequence -- 4 Relative Pose Estimation -- 4.1 Relative Pose from 3 Plane Correspondences -- 4.2 Relative Pose Estimation in Case Ni Has Rank 2 -- 4.3 Relative Pose Estimation in Case Ni Has Rank 1 -- 4.4 Robust Algorithm for Computing the Relative Pose -- 5 Discrete-Continuous Bundle Adjustment -- 6 Experimental Results -- 7 Conclusions -- References -- Nonrigid Surface Registration and Completion from RGBD Images -- 1 Introduction -- 2 Related Work -- 3 Nonrigid Surface Registration and Completion -- 3.1 Nonrigid Patch-Based Surface Model -- 3.2 Nonrigid Registration as Inference in a CRF -- 3.3 Incorporating New Patches -- 4 Experimental Results -- 4.1 Comparison with the Baselines -- 4.2 Missing Data and Occlusions -- 4.3 Incorporating New Patches -- 4.4 Video Editing -- 5 Conclusion -- References -- Unsupervised Dense Object Discovery, Detection, Tracking and Reconstruction -- 1 Introduction -- 2 Overview -- 3 Discovery and Detection -- 4 Tracking and Reconstruction -- 4.1 Tracking -- 4.2 Reconstruction -- 4.3 Tracking and Reconstruction Interaction -- 5 System Integration -- 6 Results and Discussion -- 7 Failure Cases and Future Work -- 8 Conclusions -- References -- Know Your Limits: Accuracy of Long Range Stereoscopic Object Measurements in Practice -- 1 Introduction -- 2 Related Work -- 3 Long Range Object Stereo: Algorithm Overview -- 3.1 Local Differential Matching (LDM) -- 3.2 Joint Matching and Segmentation (SEG) -- 3.3 Total Variation Stereo (TV) -- 3.4 Semi-Global Matching (SGM) -- 4 Evaluation -- 4.1 Dataset -- 4.2 Performance Measures -- 5 Results and Analysis -- 6 Conclusions -- References -- As-Rigid-As-Possible Stereo under Second Order Smoothness Priors -- 1 Introduction -- 1.1 Background -- 1.2 Contribution -- 2 As-Rigid-As-Possible Stereo -- 2.1 Second-Order Smoothness Priors.
2.2 As-Rigid-As-Possible Smoothness and Data Cost -- 2.3 Overall Energy -- 2.4 Interactions between the Two Priors -- 2.5 Optimization -- 3 Implementation -- 3.1 Initialize -- 3.2 Optimize ED -- 3.3 Optimize ES -- 3.4 Post-process -- 4 Experiments -- 4.1 Comparisons of Results -- 4.2 Running Time -- 5 Conclusion -- References -- Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional -- 1 Introduction -- 1.1 The Mumford-Shah Problem -- 1.2 Related Work -- 1.3 Contribution -- 2 Proposed Finite-Difference Discretization -- 3 Minimization Algorithm -- 3.1 Algorithm for Convex Regularizers R -- 3.2 Proposed Algorithm for the MS-Energy -- 4 Experiments -- 4.1 Energy in One-Dimensional Case -- 4.2 Comparison with Convex Relaxation -- 4.3 Comparison with Ambrosio-Tortorelli -- 4.4 Comparison with L0-Smoothing -- 4.5 Real-Time Unsupervised Image Segmentation -- 4.6 Real-Time Video Cartooning -- 5 Conclusion -- References -- A MAP-Estimation Framework for Blind Deblurring Using High-Level Edge Priors -- 1 Introduction -- 2 Our Blind Deconvolution Approach -- 2.1 Data Term Edata(k, x|I) -- 2.2 Blur Kernel Prior Term Ekernel(k) -- 2.3 Image Prior Term Eimg(x|e) -- 2.4 Edge Prior Term Eedge(e|x) -- 3 Geometric Parsing Prior for Blind Deconvolution -- 4 MAP-Estimation Inference -- 4.1 Optimizing over the Kernel k -- 4.2 Optimizing over the Latent Image -- 4.3 Optimizing over the Edge-Related Variables e -- 4.4 Multi-resolution Inference -- 5 Experimental Results -- 6 Conclusions -- References -- Efficient Color Constancy with Local Surface Reflectance Statistics -- 1 Introduction -- 2 Color Constancy with Local Surface Reflectance Estimation -- 2.1 Surface Reflectance Estimation in Local Region -- 2.2 Illuminant Estimation -- 3 Experimental Results -- 3.1 Real-World Image Set -- 3.2 An Indoor Image Dataset in Laboratory.
3.3 SFU Grey Ball Image Datasets -- 3.4 SFU HDR Dataset -- 4 Discussion and Conclusion -- 5 Appendix -- References -- A Contrast Enhancement Framework with JPEG Artifacts Suppression -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Structure-Texture Decomposition -- 3.2 Reducing Artifacts in the Texture Layer -- 3.3 Layer Recomposition -- 4 Results -- 5 Discussion and Conclusion -- References -- Radial Bright Channel Prior for Single Image Vignetting Correction -- 1 Introduction -- 2 Related Work -- 3 Radial Bright Channel Prior -- 4 Vignetting Correction Using RBC Prior -- 4.1 Simple Estimation of the Vignetting Function -- 4.2 Model-Based Vignetting Estimation with Outlier Handling -- 4.3 Restoring the Vignetting-Free Image -- 5 Results -- 5.1 Synthetic Examples -- 5.2 Real Examples -- 5.3 Computation Time -- 6 Discussion and Future Work -- References -- Tubular Structure Filtering by Ranking Orientation Responses of Path Operators -- 1 Introduction -- 2 Related Works -- 2.1 Differential Filters -- 2.2 Non-linear Filters -- 3 General Strategy -- 4 Ranking Orientation Responses of Path Operators -- 4.1 Path Operators -- 4.2 RPO-Based Filtering -- 4.3 Orientation Space Sampling -- 4.4 Cone-Oriented Robust Path Opening -- 4.5 Pointwise Rank Filtering -- 4.6 RORPO: A Filter Based on Ranking Orientations Responses Path Operator -- 4.7 Suppressing Artifacts Generated by Limit Cases -- 5 Experiments and Results -- 5.1 ComparedMethods and Quality Scores -- 5.2 Synthetic Images -- 5.3 Real Images -- 6 Discussion and Conclusion -- References -- Optimization-Based Artifact Correction for Electron Microscopy Image Stacks -- 1 Introduction -- 2 Artifact Correction Algorithm -- 2.1 Problem Formulation -- 2.2 Coarse-to-Fine Procedure -- 2.3 Removing the Blocking Effects -- 2.4 Parallelization -- 3 Evaluation on Electron Microscopy Data.
3.1 Image Quality Evaluation -- 3.2 Segmentation Accuracy Evaluation -- 4 Electron Microscopy Results -- 4.1 Comparison of NIQE Scores -- 4.2 Comparison of Segmentation Accuracy -- 5 Lighting Correction of Time-Lapse Photography -- 6 Discussion -- References -- Metric-Based Pairwise and Multiple Image Registration -- 1 Introduction -- 1.1 Desired Properties in an Objective Function -- 1.2 Past and Current Literature -- 2 Metric-BasedImage Registration -- 2.1 Image Representation and Pairwise Registration -- 2.2 Gradient Method for Optimization Over Γ -- 2.3 Distance in the Quotient Space -- 3 Experiments -- 3.1 Pairwise Image Registration -- 3.2 Registering Multiple Images -- 3.3 Image Classification -- 4 Conclusion -- References -- Canonical Correlation Analysis on Riemannian Manifolds and Its Applications -- 1 Introduction -- 2 Canonical Correlation in Euclidean Space -- 3 Mathematical Preliminaries -- 4 A Model for CCA on Riemannian Manifolds -- 5 Optimization Schemes -- 5.1 An Augmented Lagrangian Method -- 5.2 Extensions to the Product Riemannian Manifold -- 6 Experiments -- 6.1 CCA on SPD Manifolds -- 6.2 Synthetic Experiments -- 6.3 CCA for Multi-modal Risk Analysis -- 7 Conclusion -- References -- Scalable 6-DOF Localization on Mobile Devices -- 1 Introduction -- 2 Overall Approach -- 3 Local and Global Pose Estimation -- 3.1 Local Pose Tracking Using SLAM -- 3.2 Server-Based Global Localization -- 4 Aligning the Local Map Globally -- 5 Experimental Evaluation -- 5.1 Comparison of the Proposed Alignment Strategies -- 5.2 Accuracy, Efficiency and Scalability of Pose Estimation -- 6 Conclusion and Future Work -- References -- On Mean Pose and Variability of 3D Deformable Models -- 1 Introduction -- 2 Related Work -- 3 Mean Pose Inference Model -- 3.1 Shape Space Parameterization -- 3.2 Mean Pose -- 3.3 Generative Model.
3.4 Expectation-Maximization Inference.
Record Nr. UNISA-996198261903316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui