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. Ed(S): Wang, Liang; Zhao, Guoying; Cheng, Li; Pietikainen, Matti - Machine Learning for Vision-Based Motion Analysis - 9781447126072 - V9781447126072
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Machine Learning for Vision-Based Motion Analysis

€ 185.46
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Description for Machine Learning for Vision-Based Motion Analysis Paperback. Based on contributions to the International Workshop on Machine Learning for Vision-Based Motion Analysis, this volume highlights the latest algorithms and systems for robust and effective vision-based motion understanding. Editor(s): Wang, Liang; Zhao, Guoying; Cheng, Li; Pietikainen, Matti. Series: Advances in Computer Vision and Pattern Recognition. Num Pages: 386 pages, biography. BIC Classification: UYQ; UYT. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 20. Weight in Grams: 593.

Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition.

Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms ... Read more

Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets.

Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.

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Product Details

Format
Paperback
Publication date
2012
Publisher
Springer London Ltd United Kingdom
Number of pages
386
Condition
New
Series
Advances in Computer Vision and Pattern Recognition
Number of Pages
372
Place of Publication
England, United Kingdom
ISBN
9781447126072
SKU
V9781447126072
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Machine Learning for Vision-Based Motion Analysis
From the reviews: “The successes of the First and Second International Workshops on Machine Learning for Vision-Based Motion Analysis, which were held in 2008 and 2009, prompted this book. The book consists of four parts, and each part includes a number of freestanding chapters. … This book provides a comprehensive introduction to machine learning for vision-based motion analysis. I ... Read more

Goodreads reviews for Machine Learning for Vision-Based Motion Analysis


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