Vehicle detection by edge-based candidate generation and appearance-based classification

This paper presents a monocular machine vision system capable of detecting vehicles in front or behind of our own vehicle. The system consists of two main steps: 1) generation of candidates with respect to a vehicle by analyzing textures, 2) verification of the candidates by an appearance-based meth...

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Bibliographic Details
Main Authors: Song, Gwang Yul, Lee, Ki Yong, Lee, Joon Woong
Format: Conference Proceeding
Language:English
Subjects:
Vehicles
Online Access:Request full text
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Summary:This paper presents a monocular machine vision system capable of detecting vehicles in front or behind of our own vehicle. The system consists of two main steps: 1) generation of candidates with respect to a vehicle by analyzing textures, 2) verification of the candidates by an appearance-based method using the AdaBoost learning algorithm. The vehicle candidates are generated by exploiting the facts that a vehicle has vertical and horizontal lines, and furthermore the rear and frontal shapes of a vehicle show symmetry. The proposed system is proven to be effective through experiments under various traffic scenarios.
ISSN:1931-0587
2642-7214
DOI:10.1109/IVS.2008.4621139