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Proceedings Paper

Object tracking via background subtraction for monitoring illegal activity in crossroad
Author(s): Deepak Ghimire; Sunghwan Jeong; Sang Hyun Park; Joonwhoan Lee
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Paper Abstract

In the field of intelligent transportation system a great number of vision-based techniques have been proposed to prevent pedestrians from being hit by vehicles. This paper presents a system that can perform pedestrian and vehicle detection and monitoring of illegal activity in zebra crossings. In zebra crossing, according to the traffic light status, to fully avoid a collision, a driver or pedestrian should be warned earlier if they possess any illegal moves. In this research, at first, we detect the traffic light status of pedestrian and monitor the crossroad for vehicle pedestrian moves. The background subtraction based object detection and tracking is performed to detect pedestrian and vehicles in crossroads. Shadow removal, blob segmentation, trajectory analysis etc. are used to improve the object detection and classification performance. We demonstrate the experiment in several video sequences which are recorded in different time and environment such as day time and night time, sunny and raining environment. Our experimental results show that such simple and efficient technique can be used successfully as a traffic surveillance system to prevent accidents in zebra crossings.

Paper Details

Date Published: 11 July 2016
PDF: 6 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 1001103 (11 July 2016); doi: 10.1117/12.2242877
Show Author Affiliations
Deepak Ghimire, Korea Electronics Technology Institute (Korea, Republic of)
Sunghwan Jeong, Korea Electronics Technology Institute (Korea, Republic of)
Sang Hyun Park, Korea Electronics Technology Institute (Korea, Republic of)
Joonwhoan Lee, Chonbuk National Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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