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Proceedings Paper

Vision-based object detection and recognition system for intelligent vehicles
Author(s): Bin Ran; Henry Xianghong Liu; Wilfung Martono
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Paper Abstract

Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

Paper Details

Date Published: 8 January 1999
PDF: 12 pages
Proc. SPIE 3525, Mobile Robots XIII and Intelligent Transportation Systems, (8 January 1999); doi: 10.1117/12.335712
Show Author Affiliations
Bin Ran, Univ. of Wisconsin/Madison (United States)
Henry Xianghong Liu, Univ. of Wisconsin/Madison (United States)
Wilfung Martono, Univ. of Wisconsin/Madison (United States)

Published in SPIE Proceedings Vol. 3525:
Mobile Robots XIII and Intelligent Transportation Systems
Howie M. Choset; Pushkin Kachroo; Mikhail A. Kourjanski; Douglas W. Gage; Pushkin Kachroo; Marten J. de Vries; Mikhail A. Kourjanski; Marten J. de Vries, Editor(s)

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