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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Motion Feature Combination for Human Action Recognition in Video
verfasst von : Hongying Meng, Nick Pears, Chris Bailey
Erschienen in: Computer Vision and Computer Graphics. Theory and Applications
Verlag: Springer Berlin Heidelberg
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We study the human action recognition problem based on motion features directly extracted from video. In order to implement a fast human action recognition system, we select simple features that can be obtained from non-intensive computation. We propose to use the motion history image (MHI) as our fundamental representation of the motion. This is then further processed to give a histogram of the MHI and the Haar wavelet transform of the MHI. The combination of these two features is computed cheaply and has a lower dimension than the original MHI. The combined feature vector is tested in a Support Vector Machine (SVM) based human action recognition system and a significant performance improvement has been achieved. The system is efficient to be used in real-time human action classification systems.