Robust traffic event extraction via content understanding for highway surveillance system

Akio Yoneyama*, Chia H. Yeh, C. C.Jay Kuo

*Corresponding author for this work

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

Abstract

A method to extract traffic events by integrating the low-level, middle-level, and high-level feature extraction modules is developed in this research. The low-level module extracts features such as motion, size, and location. The middle-level module builds a bridge between the road surface plane in the real world and the captured image plane via geometric analysis. Finally, the high-level module identifies traffic events such as "traffic jam", "lane change", and "traffic rule violation", which require the understanding of video contents in a specific knowledge domain. In the high-level module, various traffic events are related to motion characteristics obtained from the middle-level module. It is demonstrated by experimental results that the proposed system can achieve robust traffic event extraction.

Original languageEnglish
Title of host publication2004 IEEE International Conference on Multimedia and Expo (ICME)
Pages1679-1682
Number of pages4
Publication statusPublished - 2004
Externally publishedYes
Event2004 IEEE International Conference on Multimedia and Expo (ICME) - Taipei, Taiwan
Duration: 2004 Jun 272004 Jun 30

Publication series

Name2004 IEEE International Conference on Multimedia and Expo (ICME)
Volume3

Conference

Conference2004 IEEE International Conference on Multimedia and Expo (ICME)
Country/TerritoryTaiwan
CityTaipei
Period2004/06/272004/06/30

ASJC Scopus subject areas

  • Engineering(all)

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