NDLI: Detection of pedestrian crossing road

Content Provider	IEEE Xplore Digital Library
Author	Hariyono, J. Kang-Hyun Jo
Copyright Year	2015
Description	Author affiliation: Grad. Sch. of Electr. & Comput. Eng., Univ. of Ulsan, Ulsan, South Korea (Hariyono, J.; Kang-Hyun Jo)
Abstract	Detection of pedestrian crossing road is described in this paper. Single camera is used to detect pedestrians, thus classify them as a pedestrian crossing road or not. The moving pedestrian is detected using improved sparse optical flow method. The proposed technique consists of three main components. First, overlapping blocks are applied in consecutive images. KLT tracker is used to find corresponding corner feature in consecutive images. Second, classify each block into motion region (foreground) and background, where each block is processed by a cascade composed of three classifiers. Third, probabilistic generation of the foreground mask is performed. The classification decisions for all blocks are integrated into final pixel-level foreground segmentation. In order to classify the pedestrian crossing road, a walking human model is proposed. It is calculated by the region volume of the detected bounding box. A walking human is defined as the ratio of the width divided by the height of the detected bounding box. To be sure that the moving object is a walking human, ratio of the centroid location from the ground plane divided by the height of bounding box should satisfy a constraint. The proposed algorithms are evaluated using publicly (Caltech and ETH) datasets and our real world driving data. The performance result shows the correct pedestrian detection rate is 99.50% at 0.09 false positive per image. The pedestrian crossing road classification shown correct detection rate is 98.10%.
Starting Page	4585
Ending Page	4588
File Size	874796
Page Count	4
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351675
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Roads Legged locomotion Computer vision Optical imaging Image motion analysis Vehicles Image color analysis location classification Pedestrian detection optical flow
Content Type	Text
Resource Type	Article

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