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Proceedings Paper

Real-time vehicle detection and tracking based on traffic scene analysis
Author(s): Zhi Zeng; Shengjin Wang; Xiaoqing Ding
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Paper Abstract

In this paper, upon the background of driving assistance on highway, we propose a real-time vehicle detection and tracking algorithm based on traffic scene analysis. We describe a general traffic scene analysis framework for vehicle detection and tracking based on roadside detection at first. On that basis, we present a new object detection algorithm via fusion of global classifier and part-based classifier and a vehicle detection algorithm integrating classifying confidence and local shadow. The local shadow is obtained by detecting the Maximally Stable Extremal Regions (MSER) using a multi-resolution strategy. Finally, we test our algorithm on several video sequence captured from highway and suburban roads. The test results show high efficiency and robustness when coping with environment transition, illumination variation and vehicle orientation change.

Paper Details

Date Published: 17 February 2007
PDF: 12 pages
Proc. SPIE 6503, Machine Vision Applications in Industrial Inspection XV, 65030M (17 February 2007); doi: 10.1117/12.703898
Show Author Affiliations
Zhi Zeng, Tsinghua Univ. (China)
Shengjin Wang, Tsinghua Univ. (China)
Xiaoqing Ding, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 6503:
Machine Vision Applications in Industrial Inspection XV
Fabrice Meriaudeau; Kurt S. Niel, Editor(s)

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