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8 October 2015 Elderly fall detection using SIFT hybrid features
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Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 96751W (2015) https://doi.org/10.1117/12.2199683
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaoxiao Wang, Chao Gao, and Yongcai Guo "Elderly fall detection using SIFT hybrid features", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96751W (8 October 2015); https://doi.org/10.1117/12.2199683
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