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Vehicle detection and inter-vehicle distance estimation using single-lens video camera on urban/suburb roads
Affiliation:1. SAMSUNG Research Institute Brazil (SRBR), CEP 13097-160 Campinas, SP, Brazil;2. School of Engineering, Brown University, Providence, RI 02912 USA;3. Institute of Computing, University of Campinas (Unicamp), CEP 13083-852 Campinas, SP, Brazil;1. Aberystwyth University, Wales, UK;2. Middlesex University, London, UK;3. University of Karbala, Karbala, Iraq;1. Department of Computer and Radio Communications Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea;2. Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
Abstract:This paper presents a driver assistance system for vehicle detection and inter-vehicle distance estimation using a single-lens video camera on urban/suburb roads. The task of vehicle detection on urban/suburb roads is more challenging due to their high scene complexity. In this work, the still area of frame inside the host vehicle is first removed using temporal differencing, followed by detecting vanishing point. Segmentation of road regions is then conducted using vanishing point and road’s edge lines. Shadow regions at the bottoms of vehicles verified using the HOG feature and an SVM classifier are utilized to detect vehicle positions. The distances between the host and its front vehicles are estimated based on the locations of detected vehicles and vanishing point. Experimental results show varied performance of vehicle detection with different scenes of urban/suburb roads and the detection rate can achieve up to 94.08%, indicating the feasibility of the proposed method.
Keywords:Vehicle detection  Inter-vehicle distance estimation  Background subtraction  Histogram of oriented gradient (HOG)  Support vector machine (SVM)
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