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