Title :
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
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;
Conference_Titel :
Vehicular Electronics and Safety (ICVES), 2011 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-0576-2
DOI :
10.1109/ICVES.2011.5983805
