Authors:
- Presents a comprehensive overview of the state of the art in feature representation and machine learning algorithms for action recognition from depth sensors
- Provides in-depth descriptions of novel feature representations and machine learning techniques
- Covers lower-level depth and skeleton features, higher-level representations to model temporal structure and human-object interactions, and feature selection techniques for occlusion handling
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (4 chapters)
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Front Matter
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Back Matter
About this book
Reviews
“It is a relatively short but self-contained volume that presents recent advances in the popular research area of human action recognition. … I was quite pleased when the student, to whom I passed the book for a through read, told me at the end that he found it very useful and a good start for his research. ... book is a good read for someone with an existing background in depth camera technology and research about human action recognition.” (Nicola Bellotto, IAPR Newsletter, Vol. 37 (2), 2015)
Authors and Affiliations
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Northwestern University, Evanston, USA
Jiang Wang, Ying Wu
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Microsoft Research, Redmond, USA
Zicheng Liu
Bibliographic Information
Book Title: Human Action Recognition with Depth Cameras
Authors: Jiang Wang, Zicheng Liu, Ying Wu
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-319-04561-0
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s) 2014
Softcover ISBN: 978-3-319-04560-3Published: 04 February 2014
eBook ISBN: 978-3-319-04561-0Published: 25 January 2014
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: VIII, 59
Number of Illustrations: 23 b/w illustrations, 9 illustrations in colour
Topics: Image Processing and Computer Vision, Biometrics, User Interfaces and Human Computer Interaction