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Human Action Classification Using SVM_2K Classifier on Motion Features.
- Source :
- Multimedia Content Representation, Classification & Security; 2006, p458-465, 8p
- Publication Year :
- 2006
-
Abstract
- In this paper, we study the human action classification problem based on motion features directly extracted from video. In order to implement a fast classification system, we select simple features that can be obtained from non-intensive computation. We also introduce the new SVM_2K classifier that can achieve improved performance over a standard SVM by combining two types of motion feature vector together. After learning, classification can be implemented very quickly because SVM_2K is a linear classifier. Experimental results demonstrate the method to be efficient and may be used in real-time human action classification systems. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783540393924
- Database :
- Complementary Index
- Journal :
- Multimedia Content Representation, Classification & Security
- Publication Type :
- Book
- Accession number :
- 33001614
- Full Text :
- https://doi.org/10.1007/11848035_61