Object-Based Accumulated Motion Feature for the Compressed Domain Human Action Analysis
- 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.
- https://doi.org/10.2991/jcis.2006.262How to use a DOI?
- Compressed video,Video segmentation,Object-based accumulative motion vector (OAMV),Hidden Markov Models.
- 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.
- 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 -