Title :
Intelligent Human Fall Detection for Home Surveillance
Author :
Hong Lu;Bohong Yang;Rui Zhao;Pengliang Qu;Wenqiang Zhang
Author_Institution :
Shanghai Key Lab. of Intell. Inf. Process., Fudan Univ., Shanghai, China
Abstract :
We propose in this paper an intelligent system for human fall detection in indoor environments. It can serve as home surveillance for elderly person. Specifically, we detect the human body captured by camera using the Vibe algorithm. Then Gabor feature of a human body is extracted as observation feature. Based on the extracted feature, incidents are detected as the changes from the standing state to the fall state in the feature space. The feature is detected on single image and is effective and efficient. Compared with the motion features across images combined with biological inspired feed-forward network, our method can obtain more robust detection results.
Keywords :
"Feature extraction","Senior citizens","Conferences","Support vector machines","Robustness","Surveillance","Visualization"
Conference_Titel :
Ubiquitous Intelligence and Computing, 2014 IEEE 11th Intl Conf on and IEEE 11th Intl Conf on and Autonomic and Trusted Computing, and IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UTC-ATC-ScalCom)
DOI :
10.1109/UIC-ATC-ScalCom.2014.56