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Type of publication:Incollection
Entered by:LP
TitleCommon spatial patterns for real-time classification of human actions
Bibtex cite ID
Booktitle Machine Learning for Human Motion Analysis: Theory and Practice
Year published 2010
Month January
Pages 55-73
Chapter 4
Publisher IGI Global
ISBN 978-1-60566-900-7
Keywords Human motion analysis,action recognition,common spatial patterns
Abstract
We present a discriminative approach to human action recognition. At the heart of our approach is the use of common spatial patterns (CSP), a spatial filter technique that transforms temporal feature data by using differences in variance between two classes. Such a transformation focuses on differences between classes, rather than on modeling each class individually. As a result, to distinguish between two classes, we can use simple distance metrics in the low-dimensional transformed space. The most likely class is found by pairwise evaluation of all discriminant functions, which can be done in real-time. Our image representations are silhouette boundary gradients, spatially binned into cells. We achieve scores of approximately 96% on the Weizmann human action dataset, and show that reasonable results can be obtained when training on only a single subject. We further compare our results with a recent examplarbased approach. Future work is aimed at combining our approach with automatic human detection.
Authors
Poppe, Ronald
Editors
Wang, Liang
Cheng, Li
Zhao, Guoying
Topics
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