Improved Vehicle Detection Algorithm in Heavy Traffic for Intelligent Vehicle

Chung-Hee Lee, Young-Chul Lim, Dongyoung Kim, Kyu-Ik Sohng


Despite significant progress in vehicle detection over the last few decades, vehicle detection performance in heavy traffic is still inadequate. In this paper, we propose a new algorithm for vehicle detection in heavy traffic to improve detection performance. It uses two proposed segmentation methods, namely, the disparity map-based bird's-eye-view mapping segmentation method and the edge distance weighted conditional random field (CRF)-based segmentation method. Our experimental results show that the proposed algorithm outperforms conventional algorithms. The improvements in performance range from 10.8 % to 20.5 % increase in F-measure.



Intelligent vehicle; image segmentation; object recognition; stereo image processing

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Print ISSN: 1392-1215
Online ISSN: 2029-5731