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http://dx.doi.org/10.5302/J.ICROS.2011.17.5.490

A Study on the Pedestrian Detection on the Road Using Machine Vision  

Lee, Byung-Ryong (University of Ulsan)
Truong, Quoc Bao (University of Ulsan)
Kim, Hyoung-Seok (University of Ulsan)
Bae, Yong-Hwan (Andong National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.17, no.5, 2011 , pp. 490-498 More about this Journal
Abstract
In this paper, we present a two-stage vision-based approach to detect multi views of pedestrian in road scene images. The first stage is HG (Hypothesis Generation), in which potential pedestrian are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map, and different colors between road background and pedestrian's clothes to determine the leg position of pedestrian, then a novel symmetry peaks processing is performed to define how many pedestrians is covered in one potential candidate region. Finally, the real candidate region where pedestrian exists will be constructed. The second stage is HV (Hypothesis Verification). In this stage, all hypotheses are verified by Support Vector Machine for classification, which is robust for multi views of pedestrian detection and recognition problems.
Keywords
pedestrian detection; vision-based; HG (Hypothesis Generation); HV (Hypothesis Verification); different color method; symmetry peak processing; SVM (Support Vector Machine);
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