HMM based falling person detection using both audio and video

Date

2005

Editor(s)

Advisor

Supervisor

Co-Advisor

Co-Supervisor

Instructor

BUIR Usage Stats
0
views
17
downloads

Citation Stats

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.

Source Title

Lecture Notes in Computer Science

Publisher

Springer

Course

Other identifiers

Book Title

Keywords

Degree Discipline

Degree Level

Degree Name

Citation

Published Version (Please cite this version)

Language

English