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 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
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 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
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 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
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 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
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 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
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 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
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 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
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 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
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. |
Record Nr. | UNISA-996202530303316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
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 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|