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Preface; Contents; Contributors; Acronyms; 1 Feature Representation and Extraction for Image Search and Video Retrieval; 1.1 Introduction; 1.2 Spatial Pyramid Matching, Soft Assignment Coding, Fisher Vector Coding, and Sparse Coding; 1.2.1 Spatial Pyramid Matching; 1.2.2 Soft Assignment Coding; 1.2.3 Fisher Vector Coding; 1.2.4 Sparse Coding; 1.2.5 Some Sparse Coding Variants; 1.3 Local Binary Patterns (LBP), Feature LBP (FLBP), Local Quaternary Patterns (LQP), and Feature LQP (FLQP); 1.4 Scale Invariant Feature Transform (SIFT) and SIFT Variants; 1.4.1 Color SIFT; 1.4.2 SURF; 1.4.3 MSIFT
1.4.4 DSP-SIFT1.4.5 LPSIFT; 1.4.6 FAIR-SURF; 1.4.7 Laplacian SIFT; 1.4.8 Edge-SIFT; 1.4.9 CSIFT; 1.4.10 RootSIFT; 1.4.11 PCA-SIFT; 1.5 Conclusion; References; 2 Learning and Recognition Methods for Image Search and Video Retrieval; 2.1 Introduction; 2.2 Deep Learning Networks and Models; 2.2.1 Feedforward Deep Neural Networks; 2.2.2 Deep Autoencoders; 2.2.3 Convolutional Neural Networks (CNNs); 2.2.4 Deep Boltzmann Machine (DBM); 2.3 Support Vector Machines; 2.3.1 Linear Support Vector Machine; 2.3.2 Soft-Margin Support Vector Machine; 2.3.3 Non-linear Support Vector Machine
2.3.4 Simplified Support Vector Machines2.3.5 Efficient Support Vector Machine; 2.3.6 Applications of SVM; 2.4 Other Popular Kernel Methods and Similarity Measures; 2.5 Conclusion; References; 3 Improved Soft Assignment Coding for Image Classification; 3.1 Introduction; 3.2 Related Work; 3.3 The Improved Soft-Assignment Coding; 3.3.1 Revisiting the Soft-Assignment Coding; 3.3.2 Introduction to Fisher Vector and VLAD Method; 3.3.3 The Thresholding Normalized Visual Word Plausibility; 3.3.4 The Power Transformation; 3.3.5 Relation to VLAD Method; 3.4 Experiments
3.4.1 The UIUC Sports Event Dataset3.4.2 The Scene 15 Dataset; 3.4.3 The Caltech 101 Dataset; 3.4.4 The Caltech 256 Dataset; 3.4.5 In-depth Analysis; 3.5 Conclusion; References; 4 Inheritable Color Space (InCS) and Generalized InCS Framework with Applications to Kinship Verification; 4.1 Introduction; 4.2 Related Work; 4.3 A Novel Inheritable Color Space (InCS); 4.4 Properties of the InCS; 4.4.1 The Decorrelation Property; 4.4.2 Robustness to Illumination Variations; 4.5 The Generalized InCS (GInCS) Framework; 4.6 Experiments
4.6.1 Experimental Results Using the KinFaceW-I and the KinFaceW-II Datasets4.6.2 Experimental Results Using the UB KinFace Dataset; 4.6.3 Experimental Results Using the Cornell KinFace Dataset; 4.7 Comprehensive Analysis; 4.7.1 Comparative Evaluation of the InCS and Other Color Spaces; 4.7.2 The Decorrelation Property of the InCS Method; 4.7.3 The Robustness of the InCS and the GInCS to Illumination Variations; 4.7.4 Performance of Different Color Components of the InCS and the GInCS; 4.7.5 Comparison Between the InCS and the Generalized InCS
1.4.4 DSP-SIFT1.4.5 LPSIFT; 1.4.6 FAIR-SURF; 1.4.7 Laplacian SIFT; 1.4.8 Edge-SIFT; 1.4.9 CSIFT; 1.4.10 RootSIFT; 1.4.11 PCA-SIFT; 1.5 Conclusion; References; 2 Learning and Recognition Methods for Image Search and Video Retrieval; 2.1 Introduction; 2.2 Deep Learning Networks and Models; 2.2.1 Feedforward Deep Neural Networks; 2.2.2 Deep Autoencoders; 2.2.3 Convolutional Neural Networks (CNNs); 2.2.4 Deep Boltzmann Machine (DBM); 2.3 Support Vector Machines; 2.3.1 Linear Support Vector Machine; 2.3.2 Soft-Margin Support Vector Machine; 2.3.3 Non-linear Support Vector Machine
2.3.4 Simplified Support Vector Machines2.3.5 Efficient Support Vector Machine; 2.3.6 Applications of SVM; 2.4 Other Popular Kernel Methods and Similarity Measures; 2.5 Conclusion; References; 3 Improved Soft Assignment Coding for Image Classification; 3.1 Introduction; 3.2 Related Work; 3.3 The Improved Soft-Assignment Coding; 3.3.1 Revisiting the Soft-Assignment Coding; 3.3.2 Introduction to Fisher Vector and VLAD Method; 3.3.3 The Thresholding Normalized Visual Word Plausibility; 3.3.4 The Power Transformation; 3.3.5 Relation to VLAD Method; 3.4 Experiments
3.4.1 The UIUC Sports Event Dataset3.4.2 The Scene 15 Dataset; 3.4.3 The Caltech 101 Dataset; 3.4.4 The Caltech 256 Dataset; 3.4.5 In-depth Analysis; 3.5 Conclusion; References; 4 Inheritable Color Space (InCS) and Generalized InCS Framework with Applications to Kinship Verification; 4.1 Introduction; 4.2 Related Work; 4.3 A Novel Inheritable Color Space (InCS); 4.4 Properties of the InCS; 4.4.1 The Decorrelation Property; 4.4.2 Robustness to Illumination Variations; 4.5 The Generalized InCS (GInCS) Framework; 4.6 Experiments
4.6.1 Experimental Results Using the KinFaceW-I and the KinFaceW-II Datasets4.6.2 Experimental Results Using the UB KinFace Dataset; 4.6.3 Experimental Results Using the Cornell KinFace Dataset; 4.7 Comprehensive Analysis; 4.7.1 Comparative Evaluation of the InCS and Other Color Spaces; 4.7.2 The Decorrelation Property of the InCS Method; 4.7.3 The Robustness of the InCS and the GInCS to Illumination Variations; 4.7.4 Performance of Different Color Components of the InCS and the GInCS; 4.7.5 Comparison Between the InCS and the Generalized InCS