Audio surveillance of roads: A system for detecting anomalous sounds

Pasquale Foggia, Nicolai Petkov, Alessia Saggese, Nicola Strisciuglio, Mario Vento

Research output: Contribution to journalArticleAcademicpeer-review

61 Citations (Scopus)

Abstract

In the last decades, several systems based on video analysis have been proposed for automatically detecting accidents on roads to ensure a quick intervention of emergency teams. However, in some situations, the visual information is not sufficient or sufficiently reliable, whereas the use of microphones and audio event detectors can significantly improve the overall reliability of surveillance systems. In this paper, we propose a novel method for detecting road accidents by analyzing audio streams to identify hazardous situations such as tire skidding and car crashes. Our method is based on a two-layer representation of an audio stream: at a low level, the system extracts a set of features that is able to capture the discriminant properties of the events of interest, and at a high level, a representation based on a bag-of-words approach is then exploited in order to detect both short and sustained events. The deployment architecture for using the system in real environments is discussed, together with an experimental analysis carried out on a data set made publicly available for benchmarking purposes. The obtained results confirm the effectiveness of the proposed approach.

Original languageEnglish
Article number7321013
Pages (from-to)279-288
Number of pages10
JournalIEEE transactions on intelligent transportation systems
Volume17
Issue number1
DOIs
Publication statusPublished - Jan 2016
Externally publishedYes

    Fingerprint

Keywords

  • Accident detection
  • Audio detection
  • Audio events
  • Car crashes
  • Hazard detection
  • Tire skidding

Cite this