NDLI: Human body fall detection based on the Kinect sensor

Content Provider	IEEE Xplore Digital Library
Author	Liu, Yuan Wang, Nan Lv, Chaohui Cui, Jie
Copyright Year	2015
Description	Author affiliation: Communication University of China, Beijing, China (Liu, Yuan; Wang, Nan; Lv, Chaohui; Cui, Jie)
Abstract	Health problems of the elderly are more and more serious with the growth of aging population. The accidents like falling down need to be paid more attention especially. Through the analysis of the existing detection methods, a more simple and rapid algorithm about human body fall detection based on the Kinect sensor is proposed in this paper. This algorithm is composed of three parts, which are moving target depth of image acquisition, processing of depth image and identification of target motion behavior. The realization of the detection algorithm is based on the depth map sequence obtained by the Kinect. The data of falling and bending are collected and compared in this experiment. And the OTSU algorithm which has anti-noise performance is used to process depth map. It is conducive to the body contour extraction. After extracting the contour, the corrosion operation is used to repair the edge. Then three parameters are extracted, which are the aspect ratio of human external rectangle, the gravity center of human body and the inclination degree. Every frame image outputs aspect ratio and dip angle value. By comparing these values with the threshold, the system judges whether human falls down. The experimental results show that this algorithm is a kind of effective fall detection algorithm.
Starting Page	367
Ending Page	371
File Size	455527
Page Count	5
File Format	PDF
e-ISBN	9781467390989
DOI	10.1109/CISP.2015.7407906
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kinect OTSU algorithm Shape Senior citizens Signal processing algorithms Human Fall detection Shape feature extraction Feature extraction Cameras Acceleration Detection algorithms
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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