11 July 2016 Object tracking via background subtraction for monitoring illegal activity in crossroad
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Proceedings Volume 10011, First International Workshop on Pattern Recognition; 1001103 (2016) https://doi.org/10.1117/12.2242877
Event: First International Workshop on Pattern Recognition, 2016, Tokyo, Japan
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Deepak Ghimire, Deepak Ghimire, Sunghwan Jeong, Sunghwan Jeong, Sang Hyun Park, Sang Hyun Park, Joonwhoan Lee, Joonwhoan Lee, } "Object tracking via background subtraction for monitoring illegal activity in crossroad", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 1001103 (11 July 2016); doi: 10.1117/12.2242877; https://doi.org/10.1117/12.2242877


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