On-road vehicle detection fusing radar and vision

Author

Liu, Xin ; Sun, Zhenping ; He, Hangen

Author_Institution

Inst. of Autom., Nat. Univ. of Defense Technol., Changsha, China

fYear

2011

fDate

10-12 July 2011

Firstpage

150

Lastpage

154

Abstract

This paper presents a cross-verification approach to fuse radar and vision data for vehicle detection. Firstly, a realtime vision approach using specific shadow segmentation is used to detect vehicles in whole image independently. The fusion approach contains two steps: matching and validation. The targets respectively from radar and vision verify each other in matching process. Then the unmatched radar targets are validated by vision data once again. Experiment results with test dataset from real traffic scenes on freeway and urban roads are presented to illustrate the performance of this approach.

Keywords

image segmentation; radar detection; road vehicle radar; telecommunication traffic; cross-verification approach; matching fusion approach; on-road vehicle detection fusing radar; on-road vehicle detection vision data; real traffic scene; real-time vision approach; shadow segmentation; unmatched radar target; validation fusion approach; Clustering algorithms; Radar detection; Radar imaging; Roads; Vehicle detection; Vehicles; fusion; radar; vehicle detection; vehicle shadow segmentation; vision;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicular Electronics and Safety (ICVES), 2011 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4577-0576-2

Type

conf

DOI

10.1109/ICVES.2011.5983805

Filename

5983805