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Pedestrian detection algorithm based on video sequences and laser point cloud |
Hui LI1,*( ),Yun LIU1,Shengwu XIONG2,Lin WANG2 |
1. School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China 2. School of Computer Science, Wuhan University of Technology,Wuhan 430070, China |
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Abstract Pedestrian detection is a critical problem in the field of computer vision. Although most existing algorithms are able to detect pedestrians well in controlled environments, it is often difficult to achieve accurate pedestrian detection from video sequences alone, especially in pedestrian-intensive scenes wherein pedestrians may cause mutual occlusion and thus incomplete detection. To surmount these difficulties, this paper presents pedestrian detection algorithm based on video sequences and laser point cloud. First, laser point cloud is interpreted and classified to separate pedestrian data and vehicle data. Then a fusion of video image data and laser point cloud data is achieved by calibration. The region of interest after fusion is determined using feature information contained in video image and three-dimensional information of laser point cloud to remove false detection of pedestrian and thus to achieve pedestrian detection in intensive scenes. Experimental verification and analysis in video sequences demonstrate that fusion of two data improves the performance of pedestrian detection and has better detection results.
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Keywords
computer vision
pedestrian detection
video sequences
laser point cloud
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Corresponding Author(s):
Hui LI
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Issue Date: 18 May 2015
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