Improved vehicle detection algorithm in heavy traffic for intelligent vehicle

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

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)54-58
Number of pages5
JournalElektronika ir Elektrotechnika
Volume20
Issue number9
DOIs
StatePublished - 2014

Keywords

  • Image segmentation
  • Intelligent vehicle
  • Object recognition
  • Stereo image processing

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