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Table of Contents
Foreword; Preface; Contents; About the Editors; 1 Practical Matters in Computer Vision; Abstract; 1.1 Introduction; 1.2 Chapters Included in the Book; 1.3 Conclusion; References; 2 Human Action Recognition: Contour-Based and Silhouette-Based Approaches; Abstract; 2.1 Introduction; 2.2 Human Action Recognition in Videos; 2.2.1 Human Object Tracking; 2.2.2 Feature Extraction; 2.2.3 Action Classification; 2.2.4 Human Action Recognition in Weizmann Dataset: Literature Review; 2.3 Human Object Tracking in Weizmann Dataset; 2.3.1 Weizmann Human Action Dataset; 2.3.2 Background Subtraction Process.
2.3.3 Direction Detection Process2.3.4 Horizontal Alignment Process; 2.3.5 Computing Aligned Silhouettes Image Process; 2.3.6 Unifying Direction Process; 2.3.7 Cropping Bounding Box Process; 2.4 Contour-Based Feature Extraction; 2.4.1 Cartesian Coordinate Feature; 2.4.2 Fourier Descriptor Feature; 2.4.3 Centroid-Distance Features; 2.4.4 Chord-Length Features; 2.5 Silhouette-Based Feature Extraction; 2.5.1 Histogram of Oriented Gradient Feature; 2.5.2 Histogram of Oriented Optical Flow Feature; 2.5.3 Structural Similarity Index Measure Feature; 2.6 Action Classification.
2.6.1 K-Nearest Neighbor Classifier2.6.2 Support Vector Machine Classifier; 2.7 Human Action Recognition in Videos Algorithm; 2.7.1 Training Mode; 2.7.2 Testing Mode; 2.8 Experimental Results; 2.8.1 Cartesian Coordinate Feature Experiment; 2.8.2 Fourier Descriptor Feature Experiments; 2.8.3 Centroid-Distance Feature Experiments; 2.8.4 Chord-Length Feature Experiments; 2.8.5 Histogram of Oriented Gradient Feature Experiments; 2.8.6 Histogram of Oriented Optical Flow Feature Experiments; 2.8.7 Structure Similarity Index Measure Feature Experiments; 2.8.8 Experimental Results Discussion.
2.9 ConclusionReferences; 3 The Application of Machine Learning Techniques to Real Time Audience Analysis System; Abstract; 3.1 Introduction; 3.2 Face Detection; 3.3 Face Tracking; 3.4 Gender Recognition; 3.5 Age Estimation; 3.6 Conclusion; References; 4 Panorama Construction from Multi-view Cameras in Outdoor Scenes; Abstract; 4.1 Introduction; 4.2 Problem Statement; 4.3 Related Work; 4.4 Intelligent Selection and Overlapping of Representative Frames; 4.4.1 Selection of Representative Frames; 4.4.2 Overlapping Analysis of Selected Frames; 4.5 Stitching of Selected Frames.
4.5.1 Feature Points Detection4.5.2 Feature Points Matching; 4.5.3 Feature Points Correspondence; 4.5.4 Image Projection and Geometrical Improvement of Panorama; 4.5.5 Visualization of High Speed Objects in Panoramic Images; 4.6 Lighting Improvement of Panoramic Images; 4.6.1 Application of Enhancement Multi-scale Retinex Algorithm; 4.6.2 The Edges Smoothing Procedure; 4.6.3 Blending Algorithm for Stitching Area; 4.7 Discussion of Experimental Results; 4.8 Conclusion; References.
2.3.3 Direction Detection Process2.3.4 Horizontal Alignment Process; 2.3.5 Computing Aligned Silhouettes Image Process; 2.3.6 Unifying Direction Process; 2.3.7 Cropping Bounding Box Process; 2.4 Contour-Based Feature Extraction; 2.4.1 Cartesian Coordinate Feature; 2.4.2 Fourier Descriptor Feature; 2.4.3 Centroid-Distance Features; 2.4.4 Chord-Length Features; 2.5 Silhouette-Based Feature Extraction; 2.5.1 Histogram of Oriented Gradient Feature; 2.5.2 Histogram of Oriented Optical Flow Feature; 2.5.3 Structural Similarity Index Measure Feature; 2.6 Action Classification.
2.6.1 K-Nearest Neighbor Classifier2.6.2 Support Vector Machine Classifier; 2.7 Human Action Recognition in Videos Algorithm; 2.7.1 Training Mode; 2.7.2 Testing Mode; 2.8 Experimental Results; 2.8.1 Cartesian Coordinate Feature Experiment; 2.8.2 Fourier Descriptor Feature Experiments; 2.8.3 Centroid-Distance Feature Experiments; 2.8.4 Chord-Length Feature Experiments; 2.8.5 Histogram of Oriented Gradient Feature Experiments; 2.8.6 Histogram of Oriented Optical Flow Feature Experiments; 2.8.7 Structure Similarity Index Measure Feature Experiments; 2.8.8 Experimental Results Discussion.
2.9 ConclusionReferences; 3 The Application of Machine Learning Techniques to Real Time Audience Analysis System; Abstract; 3.1 Introduction; 3.2 Face Detection; 3.3 Face Tracking; 3.4 Gender Recognition; 3.5 Age Estimation; 3.6 Conclusion; References; 4 Panorama Construction from Multi-view Cameras in Outdoor Scenes; Abstract; 4.1 Introduction; 4.2 Problem Statement; 4.3 Related Work; 4.4 Intelligent Selection and Overlapping of Representative Frames; 4.4.1 Selection of Representative Frames; 4.4.2 Overlapping Analysis of Selected Frames; 4.5 Stitching of Selected Frames.
4.5.1 Feature Points Detection4.5.2 Feature Points Matching; 4.5.3 Feature Points Correspondence; 4.5.4 Image Projection and Geometrical Improvement of Panorama; 4.5.5 Visualization of High Speed Objects in Panoramic Images; 4.6 Lighting Improvement of Panoramic Images; 4.6.1 Application of Enhancement Multi-scale Retinex Algorithm; 4.6.2 The Edges Smoothing Procedure; 4.6.3 Blending Algorithm for Stitching Area; 4.7 Discussion of Experimental Results; 4.8 Conclusion; References.