Iterative motion estimation constrained by time and shape for detecting persons' falls

Doulamis, N

dc.contributor.author	Doulamis, N	en
dc.date.accessioned	2014-03-01T02:46:51Z
dc.date.available	2014-03-01T02:46:51Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32895
dc.subject	Event driven video analysis	en
dc.subject	Foreground detection	en
dc.subject	Motion Estimation	en
dc.subject.other	Ageing population	en
dc.subject.other	Background subtraction method	en
dc.subject.other	Camera information	en
dc.subject.other	Camera positions	en
dc.subject.other	Dynamic background	en
dc.subject.other	Dynamic changes	en
dc.subject.other	Elderly care	en
dc.subject.other	Elderly people	en
dc.subject.other	Fall detection	en
dc.subject.other	Foreground detection	en
dc.subject.other	Foreground object detection	en
dc.subject.other	Foreground objects	en
dc.subject.other	Frame differencing	en
dc.subject.other	Image pixels	en
dc.subject.other	Image processing and computer vision	en
dc.subject.other	Joint estimation	en
dc.subject.other	Mild dementia	en
dc.subject.other	Motion information	en
dc.subject.other	Motion scenes	en
dc.subject.other	Noise sensitivity	en
dc.subject.other	Quality of life	en
dc.subject.other	Research topics	en
dc.subject.other	Set of rules	en
dc.subject.other	Shape constraints	en
dc.subject.other	Time-continuity	en
dc.subject.other	Video analysis	en
dc.subject.other	Cameras	en
dc.subject.other	Computer vision	en
dc.subject.other	Estimation	en
dc.subject.other	Health hazards	en
dc.subject.other	Tracking (position)	en
dc.subject.other	Motion estimation	en
dc.title	Iterative motion estimation constrained by time and shape for detecting persons' falls	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1839294.1839368	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1839294.1839368	en
heal.identifier.secondary	62	en
heal.publicationDate	2010	en
heal.abstract	The quality of life for the ageing population is associated with the ability of the elderly people living independently. Fall is a major health hazard for the elders when they live independently. How to effectively assess, response and assist those elderly patients in trouble becomes an important research topic in medical elderly care services. This paper presents the visual fall detection subsystem developing the framework of ISISEMD project. The system is able to detect person falls by taking into consideration only camera information. The system is able to perform tracking of the person using advanced image processing and computer vision algorithms event in complex and dynamic background situations. The traditional approaches for detecting a human fall is based on the use of specialized devices, e.g., accelerometers, which is not a convenient framework, especially for persons with mild Dementia. Methods for automatic defection of person fall from camera cues uses motion information of the human object. However, using only motion information, we are not able to accurately detect a fall event. This is mainly due to the fact that a fall is encountered at different directions with respect to the camera position. In addition, motion information is a noise sensitive process. For this reason, accurate foreground object detection is required. However, foreground detection using the traditional background subtraction methods suffers from the dynamic changes of the background. To address these obstacles, we proposed in this paper a combined framework for fall alert based on joint estimation of foreground object and motion scene activity. In particular, motion information is estimated over a set of ""good image pixels"" to eliminate the noise sensitivity. Additionally, foreground object are extracted using frame differencing and a set of rules that express shape constraints, time continuity and the detection motion information in the scene. Experimental results on lad conditions indicate a accurate detection of a person fall. Copyright © 2010 ACM.	en
heal.journalName	ACM International Conference Proceeding Series	en
dc.identifier.doi	10.1145/1839294.1839368	en