Cited 2 time in webofscience Cited 2 time in scopus

Improved Vehicle Detection Algorithm in Heavy Traffic for Intelligent Vehicle

Title
Improved Vehicle Detection Algorithm in Heavy Traffic for Intelligent Vehicle
Authors
Lee, CH[Lee, Chung-Hee]Lim, YC[Lim, Young-Chul]Kim, D[Kim, Dongyoung]Sohng, KI[Sohng, Kyu-Ik]
DGIST Authors
Lee, CH[Lee, Chung-Hee]; Lim, YC[Lim, Young-Chul]; Kim, D[Kim, Dongyoung]
Issue Date
2014
Citation
Elektronika Ir Elektrotechnika, 20(9), 54-58
Type
Article
Article Type
Article
Keywords
Image SegmentationIntelligent VehicleObject RecognitionStereo Image Processing
ISSN
1392-1215
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.
URI
http://hdl.handle.net/20.500.11750/3147
DOI
10.5755/j01.eee.20.9.3734
Publisher
Kaunas University of Technology
Related Researcher
Files:
There are no files associated with this item.
Collection:
Convergence Research Center for Future Automotive Technology1. Journal Articles


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