9th Joint International Conference on Information Sciences (JCIS-06)

Object-Based Accumulated Motion Feature for the Compressed Domain Human Action Analysis

Authors
Cheng-Chang Lien 0, Chen-Yu Hong, Yu-Ting Fu
Corresponding Author
Cheng-Chang Lien
0Dept. of CSIE, Chung Hua University
Available Online undefined NaN.
DOI
https://doi.org/10.2991/jcis.2006.262How to use a DOI?
Keywords
Compressed video,Video segmentation,Object-based accumulative motion vector (OAMV),Hidden Markov Models.
Abstract
This paper proposed an effective and robust method to detect the rare behavior events within the compressed video directly. New motion feature called object-based accumulative motion vector (OAMV) is generated to extract a prominent motion feature and then polar histograms are used to describe the distribution patterns for each human action. The various kinds of human actions are identified by the HMM method. Experimental results show that the human actions may be identified accurately.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Publication Date
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ISBN
978-90-78677-01-7
DOI
https://doi.org/10.2991/jcis.2006.262How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Cheng-Chang Lien
AU  - Chen-Yu Hong
AU  - Yu-Ting Fu
PY  - NaN/NaN
DA  - NaN/NaN
TI  - Object-Based Accumulated Motion Feature for the Compressed Domain Human Action Analysis
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/jcis.2006.262
DO  - https://doi.org/10.2991/jcis.2006.262
ID  - LienNaN/NaN
ER  -