Elderly fall detection using SIFT hybrid features

Xiaoxiao Wang; Chao Gao; Yongcai Guo

doi:10.1117/12.2199683

8 October 2015 Elderly fall detection using SIFT hybrid features

Xiaoxiao Wang, Chao Gao, Yongcai Guo

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.

Citation Download Citation

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

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available