Pattern Recognition: Applications and Methods [[electronic resource] ] : 4th International Conference, ICPRAM 2015, Lisbon, Portugal, January 10-12, 2015, Revised Selected Papers / / edited by Ana Fred, Maria De Marsico, Mário Figueiredo |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (XVI, 301 p. 166 illus. in color.) |
Disciplina | 006.4 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Pattern recognition
Optical data processing Artificial intelligence Computer graphics Computer simulation Computational intelligence Pattern Recognition Image Processing and Computer Vision Artificial Intelligence Computer Graphics Simulation and Modeling Computational Intelligence |
ISBN | 3-319-27677-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Invited Paper -- 3D Computer Vision: From Points to Concepts -- 1 Introduction -- 2 3D Sensors -- 3 Keypoints -- 4 Descriptors -- 4.1 Evaluating Descriptors -- 4.2 Genetic Algorithm-Evolved 3D Point Cloud Descriptor -- 5 3D Object Recognition -- 5.1 Set Distances -- 5.2 Deep Transfer Learning for 3D Object Recognition -- 6 3D Object Tracking -- 7 Challenges -- 8 Conclusion -- References -- Theory and Methods -- Density Difference Detection with Application to Exploratory Visualization -- 1 Introduction -- 2 Theoretical Foundations -- 2.1 Scale Space Representation -- 2.2 Kernel Density Estimation -- 2.3 Bandwidth Selection -- 2.4 Multiple Groups -- 3 Detection Framework -- 3.1 Scale Tracing -- 3.2 Spot Detection -- 3.3 Shape Adaption -- 4 Exploratory Visualization -- 4.1 Star Coordinate Visualization -- 4.2 Preserving Orthography -- 4.3 Guiding Explorations -- 5 Experiments -- 5.1 Decision Rule -- 5.2 Data Sets -- 5.3 Parameter Investigation -- 5.4 Classification Results -- 6 Conclusion -- References -- Identifying and Mitigating Labelling Errors in Active Learning -- 1 Introduction -- 2 Background -- 2.1 Active Learning with Uncertainty -- 2.2 Impact of Label Noise -- 3 Characterizing Mislabelled Instances -- 3.1 Mislabelling Likelihood -- 3.2 Informativeness of Possibly Mislabelled Instances -- 4 Mitigating Label Noise -- 4.1 Discard, Weight and Relabel -- 5 Experiments -- 5.1 Mislabelling Likelihood -- 5.2 Label Noise Mitigation -- 6 Conclusion and Future Work -- References -- A Holistic Classification Optimization Framework with Feature Selection, Preprocessing, Manifold Learning and Classifiers -- 1 Introduction -- 2 Automatic Optimization Frameworks -- 3 Classification Pipeline -- 3.1 Feature Selection Element -- 3.2 Feature Preprocessing Element -- 3.3 Feature Transform Element.
3.4 Classifier Element -- 3.5 Hyperparameters -- 4 Optimization of the Pipeline Configuration -- 4.1 Extended Evolution Strategies -- 4.2 Optimization Target Function -- 4.3 Multi-pipeline Classifier -- 5 Experiments -- 5.1 Evaluation of the Optimization Process -- 5.2 Analysis of the Optimization Trajectory -- 5.3 Top Configuration Graph -- 5.4 Evaluation of the Generalization -- 6 Conclusions -- References -- Feature Extraction and Learning Using Context Cue and R00E9nyi Entropy Based Mutual Information -- Abstract -- 1 Introduction -- 2 Feature Extraction Using CKD -- 2.1 Formulation of CMK -- 2.2 Approximation of CMK -- 3 Feature Learning Using CSQMI -- 3.1 R00E9nyi Entropy and CSQMI -- 3.2 Codebook Selection and Refinement Using CSQMI -- 3.2.1 Codebook Selection -- 3.2.2 Codebook Refinement -- 4 Experiments -- 4.1 Parameter Configuration -- 4.2 Evaluation of Codebook Learning -- 4.3 Evaluation of Object Recognition -- 4.4 Evaluation of Object Detection -- 5 Conclusion -- Acknowledgements -- References -- Detection of Abrupt Changes in Spatial Relationships in Video Sequences -- 1 Introduction -- 2 Rupture Detection Approach -- 2.1 Fuzzy Object Representation -- 2.2 Spatial Relationships and Rupture Detection -- 3 Experiments and Evaluations -- 3.1 Parameters Tuning -- 3.2 Ruptures in Spatial Relationships -- 3.3 Impact of Object Representation -- 4 Conclusion -- References -- Diffusion-Based Similarity for Image Analysis -- 1 Introduction -- 2 Diffusion Distance and Clustering -- 3 The Problems of Diffusion Distance -- 4 Normalised Diffusion Cosine Similarity -- 5 Experimental Results -- 6 Conclusions -- References -- Automatic Detection and Recognition of Symbols and Text on the Road Surface -- 1 Introduction -- 2 Related Work -- 3 Detection and Sorting of Candidate Regions -- 3.1 Detection of Candidate Regions. 3.2 Sorting of Candidates into Words and Symbols -- 4 Recognition of Words -- 4.1 Correction of Perspective Distortion of Words -- 4.2 OCR of Region -- 5 Recognition of Symbols -- 5.1 Selection of Classifier -- 5.2 Selection of HOG Block Density -- 6 Temporal Information -- 6.1 Calculation of Road Movement -- 6.2 Matching and Temporal Fusion of Words and Symbols -- 7 Results -- 7.1 Results for Text Detection and Recognition -- 7.2 Results for Symbol Detection and Recognition -- 7.3 Failure Cases -- 8 Conclusion -- References -- Applications -- Using BLSTM for Spotting Regular Expressions in Handwritten Documents -- 1 Introduction -- 2 Related Work -- 3 BLSTM-CTC/HMM System -- 3.1 Character Recognition and Segmentation -- 3.2 Handwritten Word Spotting Model -- 3.3 Regular Expression Spotting Model -- 4 Experiments -- 4.1 Features Set -- 4.2 Results and Discussion -- 4.3 Using the BLSTM Without HMM -- 5 Conclusion -- References -- A Similarity-Based Color Descriptor for Face Detection -- 1 Introduction -- 2 Three-Patch LBP Descriptor and a Multi Scale Variant -- 3 A New Color Descriptor - Coupled-Chroma TPLBP -- 4 Evaluation of Color Descriptors -- 4.1 Invariance to Photometric and Geometric Variations -- 4.2 Invariance to Gaussian Noise -- 4.3 Discriminative Power -- 5 Evaluation of Color Descriptors in a Face Detection Setting -- 5.1 Dataset -- 5.2 Evaluation Protocol -- 5.3 Results -- 6 Conclusions -- References -- Pose Estimation and Movement Detection for Mobility Assessment of Elderly People in an Ambient Assisted Living Application -- 1 Introduction -- 2 Related Work -- 3 Mobility Assessment -- 3.1 Person Localisation -- 3.2 Movement Detection -- 3.3 Pose Estimation -- 3.4 Human Machine Interface -- 4 Experimental Results -- 5 Action Recognition -- 6 Conclusions -- 7 Future Work -- References. A Non-rigid Face Tracking Method for Wide Rotation Using Synthetic Data -- 1 Introduction -- 2 Face Representation -- 2.1 Shape Representation -- 2.2 Projection -- 2.3 Appearance Representation -- 3 Our Method -- 3.1 Model Training from Synthesized Data -- 3.2 Robust Initialization -- 3.3 Matching Strategy by Keyframes -- 3.4 Fitting via Pose-Wise Classifiers -- 4 Experimental Results -- 5 Conclusions -- References -- 3-D Face Recognition Using Geodesic-Map Representation and Statistical Shape Modelling -- 1 Introduction -- 2 Sparse Facial Landmark Detection -- 3 Geodesic-Map Representation -- 4 Geodesic-Map Matching -- 5 Dimensionality Reduction -- 6 New Dataset Fitting -- 7 Experimental Results -- 7.1 Facial Expression Changes -- 7.2 Data Resolution Variation -- 7.3 Missing Data -- 8 Conclusions -- References -- Learning Discriminative Mid-Level Patches for Fast Scene Classification -- 1 Introduction -- 2 Related Work -- 3 Discovering Discriminative Patches: Designed for Speed -- 3.1 Patch Selection and Feature Extraction -- 3.2 Classifier Training -- 3.3 Classifier Selection -- 4 Image Representation and Scene Classification -- 5 Experiments and Results -- 6 Conclusion -- References -- Modification of Polyp Size and Shape from Two Endoscope Images Using RBF Neural Network -- 1 Introduction -- 2 VBW Model -- 3 Proposed Approach -- 3.1 Estimating Reflectance Parameter -- 3.2 NN Learning for Modification of Surface Gradient -- 3.3 NN Generalization and Modification of Z -- 3.4 Regression Analysis for Shape Modification -- 4 Experimental Results -- 4.1 NN Learning -- 4.2 Order Number in Polynomial with Regression Analysis -- 4.3 Computer Simulation -- 4.4 Real Image Experiments -- 5 Conclusion -- References -- Detecting and Dismantling Composite Visualizations in the Scientific Literature -- 1 Introduction -- 2 Related Work. 3 Decomposition Algorithm -- 3.1 Step 1: Splitting -- 3.2 Step 2: Merging -- 3.3 Step 3: Selecting -- 4 Composite Figure Detection -- 5 Experimental Evaluation -- 6 Limitations and Future Work -- 7 Conclusions -- References -- Tensor Deep Stacking Networks and Kernel Deep Convex Networks for Annotating Natural Scene Images -- 1 Introduction -- 2 Convex Deep Learning Models -- 2.1 Tensor Deep Stacking Networks -- 2.2 Kernel Deep Convex Networks -- 2.3 Framework for Image Annotation -- 3 Experiments and Results -- 3.1 Experimental Setup -- 3.2 Feature Extraction -- 3.3 Datasets Used -- 3.4 Results -- 4 Summary and Conclusions -- References -- MOSAIC: Multi-object Segmentation for Assisted Image ReConstruction -- 1 Introduction -- 2 MOSAIC Procedures -- 2.1 Fragment Catalogue -- 2.2 Fragment Search -- 3 MOSAIC Interface -- 4 Experimental Results -- 4.1 An Experiment on a Real Life Case -- 5 Conclusions -- References -- Author Index. |
Record Nr. | UNISA-996466372703316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Pattern Recognition: Applications and Methods : 4th International Conference, ICPRAM 2015, Lisbon, Portugal, January 10-12, 2015, Revised Selected Papers / / edited by Ana Fred, Maria De Marsico, Mário Figueiredo |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (XVI, 301 p. 166 illus. in color.) |
Disciplina | 006.4 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Pattern recognition
Optical data processing Artificial intelligence Computer graphics Computer simulation Computational intelligence Pattern Recognition Image Processing and Computer Vision Artificial Intelligence Computer Graphics Simulation and Modeling Computational Intelligence |
ISBN | 3-319-27677-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Invited Paper -- 3D Computer Vision: From Points to Concepts -- 1 Introduction -- 2 3D Sensors -- 3 Keypoints -- 4 Descriptors -- 4.1 Evaluating Descriptors -- 4.2 Genetic Algorithm-Evolved 3D Point Cloud Descriptor -- 5 3D Object Recognition -- 5.1 Set Distances -- 5.2 Deep Transfer Learning for 3D Object Recognition -- 6 3D Object Tracking -- 7 Challenges -- 8 Conclusion -- References -- Theory and Methods -- Density Difference Detection with Application to Exploratory Visualization -- 1 Introduction -- 2 Theoretical Foundations -- 2.1 Scale Space Representation -- 2.2 Kernel Density Estimation -- 2.3 Bandwidth Selection -- 2.4 Multiple Groups -- 3 Detection Framework -- 3.1 Scale Tracing -- 3.2 Spot Detection -- 3.3 Shape Adaption -- 4 Exploratory Visualization -- 4.1 Star Coordinate Visualization -- 4.2 Preserving Orthography -- 4.3 Guiding Explorations -- 5 Experiments -- 5.1 Decision Rule -- 5.2 Data Sets -- 5.3 Parameter Investigation -- 5.4 Classification Results -- 6 Conclusion -- References -- Identifying and Mitigating Labelling Errors in Active Learning -- 1 Introduction -- 2 Background -- 2.1 Active Learning with Uncertainty -- 2.2 Impact of Label Noise -- 3 Characterizing Mislabelled Instances -- 3.1 Mislabelling Likelihood -- 3.2 Informativeness of Possibly Mislabelled Instances -- 4 Mitigating Label Noise -- 4.1 Discard, Weight and Relabel -- 5 Experiments -- 5.1 Mislabelling Likelihood -- 5.2 Label Noise Mitigation -- 6 Conclusion and Future Work -- References -- A Holistic Classification Optimization Framework with Feature Selection, Preprocessing, Manifold Learning and Classifiers -- 1 Introduction -- 2 Automatic Optimization Frameworks -- 3 Classification Pipeline -- 3.1 Feature Selection Element -- 3.2 Feature Preprocessing Element -- 3.3 Feature Transform Element.
3.4 Classifier Element -- 3.5 Hyperparameters -- 4 Optimization of the Pipeline Configuration -- 4.1 Extended Evolution Strategies -- 4.2 Optimization Target Function -- 4.3 Multi-pipeline Classifier -- 5 Experiments -- 5.1 Evaluation of the Optimization Process -- 5.2 Analysis of the Optimization Trajectory -- 5.3 Top Configuration Graph -- 5.4 Evaluation of the Generalization -- 6 Conclusions -- References -- Feature Extraction and Learning Using Context Cue and R00E9nyi Entropy Based Mutual Information -- Abstract -- 1 Introduction -- 2 Feature Extraction Using CKD -- 2.1 Formulation of CMK -- 2.2 Approximation of CMK -- 3 Feature Learning Using CSQMI -- 3.1 R00E9nyi Entropy and CSQMI -- 3.2 Codebook Selection and Refinement Using CSQMI -- 3.2.1 Codebook Selection -- 3.2.2 Codebook Refinement -- 4 Experiments -- 4.1 Parameter Configuration -- 4.2 Evaluation of Codebook Learning -- 4.3 Evaluation of Object Recognition -- 4.4 Evaluation of Object Detection -- 5 Conclusion -- Acknowledgements -- References -- Detection of Abrupt Changes in Spatial Relationships in Video Sequences -- 1 Introduction -- 2 Rupture Detection Approach -- 2.1 Fuzzy Object Representation -- 2.2 Spatial Relationships and Rupture Detection -- 3 Experiments and Evaluations -- 3.1 Parameters Tuning -- 3.2 Ruptures in Spatial Relationships -- 3.3 Impact of Object Representation -- 4 Conclusion -- References -- Diffusion-Based Similarity for Image Analysis -- 1 Introduction -- 2 Diffusion Distance and Clustering -- 3 The Problems of Diffusion Distance -- 4 Normalised Diffusion Cosine Similarity -- 5 Experimental Results -- 6 Conclusions -- References -- Automatic Detection and Recognition of Symbols and Text on the Road Surface -- 1 Introduction -- 2 Related Work -- 3 Detection and Sorting of Candidate Regions -- 3.1 Detection of Candidate Regions. 3.2 Sorting of Candidates into Words and Symbols -- 4 Recognition of Words -- 4.1 Correction of Perspective Distortion of Words -- 4.2 OCR of Region -- 5 Recognition of Symbols -- 5.1 Selection of Classifier -- 5.2 Selection of HOG Block Density -- 6 Temporal Information -- 6.1 Calculation of Road Movement -- 6.2 Matching and Temporal Fusion of Words and Symbols -- 7 Results -- 7.1 Results for Text Detection and Recognition -- 7.2 Results for Symbol Detection and Recognition -- 7.3 Failure Cases -- 8 Conclusion -- References -- Applications -- Using BLSTM for Spotting Regular Expressions in Handwritten Documents -- 1 Introduction -- 2 Related Work -- 3 BLSTM-CTC/HMM System -- 3.1 Character Recognition and Segmentation -- 3.2 Handwritten Word Spotting Model -- 3.3 Regular Expression Spotting Model -- 4 Experiments -- 4.1 Features Set -- 4.2 Results and Discussion -- 4.3 Using the BLSTM Without HMM -- 5 Conclusion -- References -- A Similarity-Based Color Descriptor for Face Detection -- 1 Introduction -- 2 Three-Patch LBP Descriptor and a Multi Scale Variant -- 3 A New Color Descriptor - Coupled-Chroma TPLBP -- 4 Evaluation of Color Descriptors -- 4.1 Invariance to Photometric and Geometric Variations -- 4.2 Invariance to Gaussian Noise -- 4.3 Discriminative Power -- 5 Evaluation of Color Descriptors in a Face Detection Setting -- 5.1 Dataset -- 5.2 Evaluation Protocol -- 5.3 Results -- 6 Conclusions -- References -- Pose Estimation and Movement Detection for Mobility Assessment of Elderly People in an Ambient Assisted Living Application -- 1 Introduction -- 2 Related Work -- 3 Mobility Assessment -- 3.1 Person Localisation -- 3.2 Movement Detection -- 3.3 Pose Estimation -- 3.4 Human Machine Interface -- 4 Experimental Results -- 5 Action Recognition -- 6 Conclusions -- 7 Future Work -- References. A Non-rigid Face Tracking Method for Wide Rotation Using Synthetic Data -- 1 Introduction -- 2 Face Representation -- 2.1 Shape Representation -- 2.2 Projection -- 2.3 Appearance Representation -- 3 Our Method -- 3.1 Model Training from Synthesized Data -- 3.2 Robust Initialization -- 3.3 Matching Strategy by Keyframes -- 3.4 Fitting via Pose-Wise Classifiers -- 4 Experimental Results -- 5 Conclusions -- References -- 3-D Face Recognition Using Geodesic-Map Representation and Statistical Shape Modelling -- 1 Introduction -- 2 Sparse Facial Landmark Detection -- 3 Geodesic-Map Representation -- 4 Geodesic-Map Matching -- 5 Dimensionality Reduction -- 6 New Dataset Fitting -- 7 Experimental Results -- 7.1 Facial Expression Changes -- 7.2 Data Resolution Variation -- 7.3 Missing Data -- 8 Conclusions -- References -- Learning Discriminative Mid-Level Patches for Fast Scene Classification -- 1 Introduction -- 2 Related Work -- 3 Discovering Discriminative Patches: Designed for Speed -- 3.1 Patch Selection and Feature Extraction -- 3.2 Classifier Training -- 3.3 Classifier Selection -- 4 Image Representation and Scene Classification -- 5 Experiments and Results -- 6 Conclusion -- References -- Modification of Polyp Size and Shape from Two Endoscope Images Using RBF Neural Network -- 1 Introduction -- 2 VBW Model -- 3 Proposed Approach -- 3.1 Estimating Reflectance Parameter -- 3.2 NN Learning for Modification of Surface Gradient -- 3.3 NN Generalization and Modification of Z -- 3.4 Regression Analysis for Shape Modification -- 4 Experimental Results -- 4.1 NN Learning -- 4.2 Order Number in Polynomial with Regression Analysis -- 4.3 Computer Simulation -- 4.4 Real Image Experiments -- 5 Conclusion -- References -- Detecting and Dismantling Composite Visualizations in the Scientific Literature -- 1 Introduction -- 2 Related Work. 3 Decomposition Algorithm -- 3.1 Step 1: Splitting -- 3.2 Step 2: Merging -- 3.3 Step 3: Selecting -- 4 Composite Figure Detection -- 5 Experimental Evaluation -- 6 Limitations and Future Work -- 7 Conclusions -- References -- Tensor Deep Stacking Networks and Kernel Deep Convex Networks for Annotating Natural Scene Images -- 1 Introduction -- 2 Convex Deep Learning Models -- 2.1 Tensor Deep Stacking Networks -- 2.2 Kernel Deep Convex Networks -- 2.3 Framework for Image Annotation -- 3 Experiments and Results -- 3.1 Experimental Setup -- 3.2 Feature Extraction -- 3.3 Datasets Used -- 3.4 Results -- 4 Summary and Conclusions -- References -- MOSAIC: Multi-object Segmentation for Assisted Image ReConstruction -- 1 Introduction -- 2 MOSAIC Procedures -- 2.1 Fragment Catalogue -- 2.2 Fragment Search -- 3 MOSAIC Interface -- 4 Experimental Results -- 4.1 An Experiment on a Real Life Case -- 5 Conclusions -- References -- Author Index. |
Record Nr. | UNINA-9910483798303321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
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Lo trovi qui: Univ. Federico II | ||
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