Machine Learning for Audio, Image and Video Analysis: Theory and Applications

Introduction.- Part I: From Perception to Computation.- Audio Acquisition, Representation and Storage.- Image and Video Acquisition, Representation and Storage.- Part II: Machine Learning.- Machine Learning.- Bayesian Theory of Decision.- Clustering Methods.- Foundations of Statistical Learning and Model Selection.- Supervised Neural Networks and Ensemble Methods.- Kernel Methods.- Markovian Models for Sequential Data.- Feature Extraction Methods and Manifold Learning Methods.- Part III: Applications.- Speech and Handwriting Recognition.- Speech and Handwriting Recognition.- Video Segmentation and Keyframe Extraction.- Real-Time Hand Pose Recognition.- Automatic Personality Perception.- Part IV: Appendices.- Appendix A: Statistics.- Appendix B: Signal Processing.- Appendix C: Matrix Algebra.- Appendix D: Mathematical Foundations of Kernel Methods.- Index.