HMM based falling person detection using both audio and video

Date
2005
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Lecture Notes in Computer Science
Print ISSN
0302-9743
Electronic ISSN
1611-3349
Publisher
Springer
Volume
3766
Issue
Pages
211 - 220
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Series
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.

Course
Other identifiers
Book Title
Keywords
Citation
Published Version (Please cite this version)