Statistical Learning and Pattern Analysis for Image and Video Processing

1. Front Matter

   Pages I-XVI

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2. Pattern Analysis and Statistical Learning

   • Nanning Zheng, Jianru Xue

   Pages 1-14

3. Unsupervised Learning for Visual Pattern Analysis

   • Nanning Zheng, Jianru Xue

   Pages 15-49

4. Component Analysis

   • Nanning Zheng, Jianru Xue

   Pages 51-85

5. Manifold Learning

   • Nanning Zheng, Jianru Xue

   Pages 87-119

6. Functional Approximation

   • Nanning Zheng, Jianru Xue

   Pages 121-158

7. Supervised Learning for Visual Pattern Classification

   • Nanning Zheng, Jianru Xue

   Pages 159-179

8. Statistical Motion Analysis

   • Nanning Zheng, Jianru Xue

   Pages 181-216

9. Bayesian Tracking of Visual Objects

   • Nanning Zheng, Jianru Xue

   Pages 217-244

10. Probabilistic Data Fusion for Robust Visual Tracking

    • Nanning Zheng, Jianru Xue

    Pages 245-285

11. Multitarget Tracking in Video-Part I

    • Nanning Zheng, Jianru Xue

    Pages 287-317

12. Multi-Target Tracking in Video – Part II

    • Nanning Zheng, Jianru Xue

    Pages 319-341

13. Information Processing in Cognition Process and New Artificial Intelligent Systems

    • Nanning Zheng, Jianru Xue

    Pages 343-362

14. Back Matter

    Pages 363-365

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Why are We Writing This Book? Visual data (graphical, image, video, and visualized data) affect every aspect of modern society. The cheap collection, storage, and transmission of vast amounts of visual data have revolutionized the practice of science, technology, and business. Innovations from various disciplines have been developed and applied to the task of designing intelligent machines that can automatically detect and exploit useful regularities (patterns) in visual data. One such approach to machine intelligence is statistical learning and pattern analysis for visual data. Over the past two decades, rapid advances have been made throughout the ?eld of visual pattern analysis. Some fundamental problems, including perceptual gro- ing,imagesegmentation, stereomatching, objectdetectionandrecognition,and- tion analysis and visual tracking, have become hot research topics and test beds in multiple areas of specialization, including mathematics, neuron-biometry, and c- nition. A great diversity of models and algorithms stemming from these disciplines has been proposed. To address the issues of ill-posed problems and uncertainties in visual pattern modeling and computing, researchers have developed rich toolkits based on pattern analysis theory, harmonic analysis and partial differential eq- tions, geometry and group theory, graph matching, and graph grammars. Among these technologies involved in intelligent visual information processing, statistical learning and pattern analysis is undoubtedly the most popular and imp- tant approach, and it is also one of the most rapidly developing ?elds, with many achievements in recent years. Above all, it provides a unifying theoretical fra- work for intelligent visual information processing applications.

• Motion Analysis
• Scalable Video Coding
• Statistical Learning
• Statistical Pattern Analysis
• Textur
• Video Segmentation
• Visual Tracking
• classification
• cognition
• intelligent systems
• learning
• modeling
• pattern recognition
• video analysis

From the reviews:

“The level for which the text was aimed was quite introductory, giving a well executed explanation of not just the technique, but also the supporting techniques. This would serve the book well as a tool to someone learning the technique from new … . Overall I enjoyed the book … . I found that the subjects were well discussed and at a level that suited my knowledge. I would recommend it as a general purpose book for image and video analysis … .” (Gavin Powell, International Association for Pattern Recognition, Vol. 32 (3), July, 2010)

• Inst. Artificial Intelligence & Robotics, Xi’an Jiaotong University, China, People’s Republic

  Nanning Zheng, Jianru Xue

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