DocumentCode
3434363
Title
Automatic Fall Incident Detection in Compressed Video for Intelligent Homecare
Author
Lin, Chia-Wen ; Ling, Zhi-Hong
Author_Institution
Nat. Tsing Hua Univ., Hsinchu
fYear
2007
fDate
13-16 Aug. 2007
Firstpage
1172
Lastpage
1177
Abstract
This paper presents a compressed-domain fall incident detection scheme for intelligent homecare applications. First, a compressed-domain object segmentation scheme is performed to extract moving objects based on global motion estimation and local motion clustering. After detecting the moving objects, three compressed-domain features of each object are then extracted for identifying and locating fall incidents. The proposed system can differentiate fall-down from squatting by taking into account the event duration. Our experiments show that the proposed method can correctly detect fall incidents in real time.
Keywords
feature extraction; home computing; motion estimation; video coding; automatic fall incident detection; compressed-domain feature extraction; compressed-domain object segmentation scheme; global motion estimation; intelligent homecare applications; motion clustering; video compression; Application software; Cameras; Computer vision; Computerized monitoring; Event detection; Injuries; Senior citizens; Smoke detectors; Surveillance; Video compression; compressed-domain processing; fall detetcion; homecare; video surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Communications and Networks, 2007. ICCCN 2007. Proceedings of 16th International Conference on
Conference_Location
Honolulu, HI
ISSN
1095-2055
Print_ISBN
978-1-4244-1251-8
Electronic_ISBN
1095-2055
Type
conf
DOI
10.1109/ICCCN.2007.4317978
Filename
4317978
Link To Document