Paper Info
Title
HMM based falling person detection using both audio and video
Abstract
Automatic detection of a falling person in video is an important problem with applications in security and safety areas including supportive home environments and CCTV surveillance systems. Human motion in video is modeled using Hidden Markov Models (HMM) in this paper. In addition, the audio track of the video is also used to distinguish a person simply sitting on a floor from a person stumbling and falling. Most video recording systems have the capability of recording audio as well and the impact sound of a falling person is also available as an additional clue. Audio channel data based decision is also reached using HMMs and fused with results of HMMs modeling the video data to reach a final decision.
Year
DOI
Venue
2005
10.1007/11573425_21
ICCV-HCI
Keywords
DocType
Volume
human motion,hidden markov models,video recording system,automatic detection,final decision,video data,audio track,cctv surveillance system,audio channel data,additional clue,person detection,hidden markov model
Conference
3766
ISBN
Citations 
PageRank 
3-540-29620-4
27
3.20
References 
Authors
4
3
Name
Order
Citations
PageRank
B. Uğur Töreyin118713.00
Yiğithan Dedeoğlu219112.73
A. Enis Çetin3871118.56