A Stereo-based Pedestrian Detection System for Smart Intersection
This paper introduces a stereo-based pedestrian detection system for smart intersection applications. Promising for real-time usage, a detector with sliding window approach is employed. In order to reduce scanning time, stereo cameras are utilized. Firstly, the system generates a disparity image from calibrated left and right images. Then, searching regions of interest (ROI) for pedestrians are obtained by clustering the disparity information. Finally, a raster scan is applied to all of the ROI and their scaled copies. For distance measurement, the authors developed a fast and accurate algorithm called Inverted Phase Filter (IPF), which can measure the disparity at sub-pixel level fast. Furthermore, for pedestrian classification, a novel feature – Staggered multi-scale LBP (Local Binary Pattern) histogram – is proposed. Evaluation results show that the proposed feature outperforms benchmarks like HOG and CoHOG on Panasonic night-time dataset and Daimler Chrysler dataset.
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Supplemental Notes:
- Abstract reprinted with permission from Intelligent Transportation Society of America.
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Corporate Authors:
1100 17th Street, NW, 12th Floor
Washington, DC United States 20036 -
Authors:
- Cao, Yunyun
- Pranata, Sugiri
- Yasugi, Makoto
- Niu, Zhiheng
- Nishimura, Hirofumi
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Conference:
- 19th ITS World Congress
- Location: Vienna , Austria
- Date: 2012-10-22 to 2012-10-26
- Publication Date: 2012
Language
- English
Media Info
- Media Type: Digital/other
- Features: CD-ROM; Figures; Photos; References; Tables;
- Pagination: 8p
- Monograph Title: 19th ITS World Congress, Vienna, Austria, 22 to 26 October 2012
Subject/Index Terms
- TRT Terms: Automated highways; Histograms; Intersections; Pedestrian detectors; Real time information; Stereoscopic cameras
- Subject Areas: Highways; Operations and Traffic Management; Pedestrians and Bicyclists; I73: Traffic Control;
Filing Info
- Accession Number: 01499136
- Record Type: Publication
- Files: TRIS
- Created Date: Nov 21 2013 9:14AM