Machine Learning for Human Motion Analysis
Theory and Practice
Published on 31. December 2009
Book
Hardback
318 pages
978-1-60566-900-7 (ISBN)
Description
With the ubiquitous presence of video data and its increasing importance in a wide range of real-world applications, it is becoming increasingly necessary to automatically analyze and interpret object motions from large quantities of footage. Machine Learning for Human Motion Analysis: Theory and Practice highlights the development of robust and effective vision-based motion understanding systems. This advanced publication addresses a broad audience including practicing professionals working with specific vision applications such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.
More details
Language
English
Place of publication
Hershey
United States
Publishing group
IGI Global
Target group
Professional and scholarly
Illustrations
illustrations
Dimensions
Height: 286 mm
Width: 221 mm
Thickness: 22 mm
Weight
1063 gr
ISBN-13
978-1-60566-900-7 (9781605669007)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Liang Wang obtained the BEng and MEng degrees in electronic engineering from Anhui University and PhD in pattern recognition and intelligent system from National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences. From July 2004 to January 2007, he worked at Imperial College London (UK), and at Monash University (Australia), respectively. He is currently working as a research fellow at The University of Melbourne (Australia). His main research interests include pattern recognition, machine learning, computer vision, and data mining. He has widely published at IEEE TPAMI, TIP, TKDE, TCSVT, TSMC, CVIU, PR, CVPR, ICCV, and ICDM. He serves for many major international journals and conferences as AE, reviewer, or PC member. He is currently an associate editor of IEEE TSMC-B, IJIG and Signal Processing. He is a co-editor of four books to be published by IGI Global and Springer, and a guest editor of three special issues for the international journals PRL, IJPRAI and IEEE TSMC-B, as well as co-chairing a special session and three workshops for VM'08, MLVMA'08 and THEMIS'08. Xin Geng received the BSc and MSc degrees in computer science from Nanjing University (China), and the PhD degree in computer science from Deakin University (Australia). He is currently an associate professor in the School of Computer Science and Engineering, Southeast University (China). His research interests include computer vision, pattern recognition, and machine learning. He has published over twenty refereed papers in these areas, including those published in prestigious journals and top international conferences. He has been a guest editor of several international journals, such as PRL and IJPRAI. He has served as a program committee member for a number of international conferences, such as PRICAI'08, AI'08, MMSP'08, CIT'08, and IEEE IRI'09. He is also a frequent reviewer for various international journals and conferences.