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Proceedings Paper

Elderly fall detection using SIFT hybrid features
Author(s): Xiaoxiao Wang; Chao Gao; Yongcai Guo
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Paper Abstract

With the tendency of aging society, countries all over the world are dealing with the demographic change. Fall had been proven to be of the highest fatality rate among the elderly. To realize the elderly fall detection, the proposed algorithm used the hybrid feature. Based on the rate of centroid change, the algorithm adopted VEI to offer the posture feature, this combined motion feature with posture feature. The algorithm also took advantage of SIFT descriptor of VEI(V-SIFT) to show more details of behaviors with occlusion. An improved motion detection method was proposed to improve the accuracy of front-view motion detection. The experimental results on CASIA database and self-built database showed that the proposed approach has high efficiency and strong robustness which effectively improved the accuracy of fall detection.

Paper Details

Date Published: 8 October 2015
PDF: 6 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96751W (8 October 2015); doi: 10.1117/12.2199683
Show Author Affiliations
Xiaoxiao Wang, Chongqing Univ. (China)
Chao Gao, Chongqing Univ. (China)
Yongcai Guo, Chongqing Univ. (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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