Audition based event detection and classification for vehicular surveillance

Jongcheol Boo, Woohyun Choi, Jinsang Rho, David K. Han, Hanseok Ko

Research output: Contribution to conferencePaperpeer-review

Abstract

Currently, sensors embedded in automobiles for surveillance purpose are mainly composed of video based and/or acceleration based sensors. However, there are surveillance situations wherein image and acceleration information obtainable from vehicles may not be sufficient for recognizing surrounding abnormal situations. Such applicable events considered in this investigation include screaming, police car sirens, and noise of glass breaking observable in both driving and parked scenarios. In this paper, a two-step event recognition system is proposed. The first step is event detection through a threshold in high-frequency acoustic band, based on an assumption that the events considered here have greater acoustic energy concentrated in the high-frequency region compared to the background noise coming from the vehicle engine. The next step is to precisely classify the detected event robust from surrounding false positives. We present a set of features which are beat spectrum, spectral flux and their combinations. To enhance the classification performance, we employed confidence measures derived from time normalized log-likelihood score.

Original languageEnglish
Publication statusPublished - 2011
Event5th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems, DSP 2011 - Kiel, Germany
Duration: 2011 Sep 42011 Sep 7

Other

Other5th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems, DSP 2011
CountryGermany
CityKiel
Period11/9/411/9/7

Keywords

  • Acoustic event detection and classification
  • Confidence measure
  • Feature combination

ASJC Scopus subject areas

  • Signal Processing
  • Automotive Engineering

Fingerprint Dive into the research topics of 'Audition based event detection and classification for vehicular surveillance'. Together they form a unique fingerprint.

Cite this