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Vehicle Detection Based on Multi-feature Clues and Dempster-Shafer Fusion Theory

Authors :
Mutsuhiro Terauchi
Mahdi Rezaei
Source :
Image and Video Technology ISBN: 9783642538414, PSIVT
Publication Year :
2014
Publisher :
Springer Berlin Heidelberg, 2014.

Abstract

On-road vehicle detection and rear-end crash prevention are demanding subjects in both academia and automotive industry. The paper focuses on monocular vision-based vehicle detection under challenging lighting conditions, being still an open topic in the area of driver assistance systems. The paper proposes an effective vehicle detection method based on multiple features analysis and Dempster-Shafer-based fusion theory. We also utilize a new idea of Adaptive Global Haar-like (AGHaar) features as a promising method for feature classification and vehicle detection in both daylight and night conditions. Validation tests and experimental results show superior detection results for day, night, rainy, and challenging conditions compared to state-of-the-art solutions.

Details

ISBN :
978-3-642-53841-4
ISBNs :
9783642538414
Database :
OpenAIRE
Journal :
Image and Video Technology ISBN: 9783642538414, PSIVT
Accession number :
edsair.doi...........d63b4dc8f468d7205119a6621cef1f19