Audio analysis for surveillance applications

Regunathan Radhakrishnan, Ajay Divakaran, Paris Smaragdis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We proposed a time series analysis based approach for systematic choice of audio classes for detection of crimes in elevators in [1]. Since all the different sounds in a surveillance environment cannot be anticipated, a surveillance system for event detection cannot completely rely on a supervised audio classification framework. In this paper, we propose a hybrid solution that consists two parts; one that performs unsupervised audio analysis and another that performs analysis using an audio classification framework obtained from off-line analysis and training. The proposed system is capable of detecting new kinds of suspicious audio events that occur as outliers against a background of usual activity. It adaptively learns a Gaussian Mixture Model(GMM) to model the background sounds and updates the model incrementally as new audio data arrives. New types of suspicious events can be detected as deviants from this usual background model. The results on elevator audio data are promising.

Original languageEnglish (US)
Title of host publication2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Pages158-161
Number of pages4
DOIs
StatePublished - Dec 1 2005
Externally publishedYes
Event2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics - New Paltz, NY, United States
Duration: Oct 16 2005Oct 19 2005

Publication series

NameIEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Other

Other2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
CountryUnited States
CityNew Paltz, NY
Period10/16/0510/19/05

ASJC Scopus subject areas

  • Signal Processing

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  • Cite this

    Radhakrishnan, R., Divakaran, A., & Smaragdis, P. (2005). Audio analysis for surveillance applications. In 2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (pp. 158-161). [1540194] (IEEE Workshop on Applications of Signal Processing to Audio and Acoustics). https://doi.org/10.1109/ASPAA.2005.1540194