Ses ve video i̇şaretlerinde sakli markof modeli tabanli düşen kişi tespiti

Translated title of the contribution: HMM based falling person detection using both audio and video

B. Uǧur Töreyin*, Yiǧitham Dedeoǧlu, A. Enis Çetin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

62 Citations (Scopus)

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.

Translated title of the contributionHMM based falling person detection using both audio and video
Original languageTurkish
Title of host publication2006 IEEE 14th Signal Processing and Communications Applications Conference
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE 14th Signal Processing and Communications Applications - Antalya, Turkey
Duration: 17 Apr 200619 Apr 2006

Publication series

Name2006 IEEE 14th Signal Processing and Communications Applications Conference
Volume2006

Conference

Conference2006 IEEE 14th Signal Processing and Communications Applications
Country/TerritoryTurkey
CityAntalya
Period17/04/0619/04/06

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