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 :
بازگشت