DocumentCode :
2508764
Title :
Slip and Fall Events Detection by Analyzing the Integrated Spatiotemporal Energy Map
Author :
Liao, Tim ; Huang, Chung-Lin
Author_Institution :
Electr. Eng. Dept., Nat. Tsing-Hua Univ., Hsinchu, Taiwan
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
1718
Lastpage :
1721
Abstract :
This paper presents a new method to detect slip and fall events by analyzing the integrated spatiotemporal energy (ISTE) map. ISTE map includes motion and time of motion occurrence as our motion feature. The extracted human shape is represented by an ellipse that provides crucial information of human motion activities. We use this features to detect the events in the video with non-fixed frame rate. This work assumes that the person lies on the ground with very little motion after the fall accident. Experimental results show that our method is effective for fall and slip detection.
Keywords :
image motion analysis; fall events detection; human motion activities; human shape; integrated spatiotemporal energy map; motion feature; motion occurrence; slip events detection; Event detection; Feature extraction; Humans; Motion segmentation; Shape; Spatiotemporal phenomena; Video sequences; Fall Event Detection; Integrated Spatiotemporal Energy (ISTE) map; Slip Event Detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.425
Filename :
5597479
Link To Document :
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