Machine Learning for Audio, Image and Video Analysis

1. Front Matter

   Pages I-XVI

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2. From Perception to Computation

   1. Introduction

      Pages 1-10

   2. Audio Acquisition, Representation and Storage

      Pages 13-50

   3. Image and Video Acquisition, Representation and Storage

      Pages 51-80

3. Machine Learning

   1. Machine Learning

      Pages 83-89

   2. Bayesian Theory of Decision

      Pages 91-115

   3. Clustering Methods

      Pages 117-148

   4. Foundations of Statistical Learning and Model Selection

      Pages 149-172

   5. Supervised Neural Networks and Ensemble Methods

      Pages 173-209

   6. Kernel Methods

      Pages 211-263

   7. Markovian Models for Sequential Data

      Pages 265-303

   8. Feature Extraction Methods and Manifold Learning Methods

      Pages 305-341

4. Applications

   1. Speech and Handwriting Recognition

      Pages 345-379

   2. Automatic Face Recognition

      Pages 381-411

   3. Video Segmentation and Keyframe Extraction

      Pages 413-430

5. Back Matter

   Pages 431-494

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1. 1 TwoFundamentalQuestions There are two fundamental questions that should be answered before buying, and even more before reading, a book: • Why should one read the book? • What is the book about? This is the reason why this section, the ?rst of the whole text, proposes some motivations for potential readers (Section 1. 1. 1) and an overall description of the content (Section 1. 1. 2). If the answers are convincing, further information can be found in the rest of this chapter: Section 1. 2 shows in detail the str- ture of the book, Section 1. 3 presents some features that can help the reader to better move through the text, and Section 1. 4 provides some reading tracks targeting speci?c topics. 1. 1. 1 Why Should One Read The Book? One of the most interesting technological phenomena in recent years is the di?usion of consumer electronic products with constantly increasing acqui- tion, storage and processing power. As an example, consider the evolution of digital cameras: the ?rst models available in the market in the early nineties produced images composed of 1. 6 million pixels (this is the meaning of the expression 1. 6 megapixels), carried an onboard memory of 16 megabytes, and had an average cost higher than 10,000 U. S. dollars. At the time this book is being written, the best models are close to or even above 8 megapixels, have internal memories of one gigabyte and they cost around 1,000 U. S. dollars.

• Classification
• Clustering
• Ensemble methods
• Face verification
• HSV
• Hidden Markov methods
• Kernel methods
• MP3
• MPEG
• Speech and handwriting recognition
• cognition
• kernel method
• learning
• machine learning
• verification

From the reviews:

"A book that focuses on the intersection and intersection of these two fast-growing areas could not be better timed. … the book is organized into three major parts that cover audio and video processing, machine learning, and applications. … On the whole, this is a valuable and timely reference book for those interested in machine learning or audio, video, and image processing, although the need for a well-integrated book on this topic still remains." (M. Sasikumar, ACM Computing Reviews, December, 2008)

"…this book, unlike most other books in this field, not only introduces a few widely used techniques in audio and image analysis, but also discusses the latest advancements in the field. …Distinct from other books, it also points out several public software packages and benchmark data sets that encourage the reader to have a hands-on experience on how machine-learning techniques work to analyze audio and visual content. Its comprehensive coverage on recent development in this research area makes it easy for experienced researchers to further explore the latest techniques. …it is ideal as a textbook or supplemental material for senior graduate courses or advanced topic seminars." (Jie Yu, Journal of Electronic Imaging, Vol. 18, Apr–Jun 2009)

• Polo Universitario Guglielmo Marconi, University of Pisa, Italy

  Francesco Camastra

• IDIAP Research Institute, Martigny, Switzerland

  Alessandro Vinciarelli

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