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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44196

Title: Grid-based Template Matching for People Counting
Authors: Jun-Wei Hsieh
Cheng-Shuang Peng
Kao-Chin Fan
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Cameras
Hair
Face detection
Robustness
Filters
Grid computing
Working environment noise
Video surveillance
Security
Trajectory
Date: 2007-10
Issue Date: 2017-11-16
Publisher: 2007 IEEE International Workshop on Multimedia Signal Processing
Abstract: Abstract:This paper presents a novel template matching method to detect and track pedestrians for people counting in real-time. Firstly, a novel background subtraction method is proposed for extracting all foreground objects from background. Then, a shadow elimination method is used to remove unwanted shadow from the background. In order to identify pedestrians from non-pedestrian objects, this paper proposed a novel grid-based template matching scheme to robustly verify each pedestrian. Usually, a pedestrian will have different appearances at different positions. The grid-based approach can effectively reduce the perspective effects into a minimum since it uses different templates to record the appearance changes at each grid. When more templates are used, the detection process will become more inefficient. To speed up its efficiency, an integral image is used to filter out all impossible candidates in advance. Lastly, a tracking method is applied to tracking the direction of each moving pedestrian so that the real number of passing people per direction can be counted more accurately. Experimental results have proved that the proposed method is robust, accurate, and powerful in people counting.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44196
Appears in Collections:[資訊工程學系] 演講及研討會

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