@inproceedings{35d37d7310a44ef1b5341ad4fa39e565,
title = "Motion Feature Combination for Human Action Recognition in Video",
abstract = "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.",
keywords = "Event recognition, Human action recognition, Video analysis, Support Vector Machine",
author = "Hongying Meng and Nick Pears and Chris Bailey",
note = "Volume is 'Computer Vision and Computer Graphics. Theory and Applications' within series 'Communications in Computer and Information Science' Print ISBN 978-3-540-89681-4; Online ISBN 978-3-540-89682-1; Series ISSN 1865-0929.",
year = "2009",
doi = "10.1007/978-3-540-89682-1_11",
language = "English",
isbn = "978-3-540-89681-4",
series = "Communications in Computer and Information Science ",
publisher = "Springer",
pages = "151--163",
booktitle = "Computer Vision and Computer Graphics. Theory and Applications",
address = "Germany",
}