Statistical Learning and Pattern Analysis for Image and Video Processing

Zheng, Nanning; Xue, Jianru

ISBN 10: 1848823118 / ISBN 13: 9781848823112

Edité par Springer London Ltd, 2010

This textbook is an overview of theories, methodologies, and recent developments in the field, covering the theoretical foundation and providing a complete summary of the latest advances. It also presents key issues to be considered in making a real system. Series: Advances in Computer Vision and Pattern Recognition. Num Pages: 381 pages, 10 black & white tables, biography. BIC Classification: UYQP. Category: (P) Professional & Vocational. Dimension: 239 x 166 x 29. Weight in Grams: 806. . 2009. Hardback. . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9781848823112

Synopsis :

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.

Présentation de l'éditeur:

This textbook is an overview of theories, methodologies, and recent developments in the field, covering the theoretical foundation and providing a complete summary of the latest advances. It also presents key issues to be considered in making a real system.

Détails bibliographiques

Titre : Statistical Learning and Pattern Analysis ...
Éditeur : Springer London Ltd
Date d'édition : 2010
Reliure : Couverture rigide
Etat : New