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ID 115188
Title Alternative
Human Detection and Tracking Using Hog Feature and Particle Filter
Author
Bhuyain, Mobarok Hossain Tokushima University
Keywords
HOG Feature
Particle Filter
Tracking people
Video Surveillance System
Content Type
Journal Article
Description
Video surveillance system has recently attracted much attention in various fields for monitoring and ensuring security. One of its promising applications is in crowd control to maintain the general security in public places. However, the problem of video surveillance systems is the required continuous manual monitoring especially for crime deterrence. In order to assist the security monitoring the live surveillance systems, intelligent target detection and tracking techniques can send a warning signal to the monitoring officers automatically. Towards this end, in this paper, we propose an innovative method to detect and track a target person in a crowded area using the individual’s features. In the proposed method, to realize automatic detection and tracking we combine Histogram of Oriented Gradient (HOG) feature detection with a particle filter. The HOG feature is applied for the description of contour detection for the person, while the particle filter is used for tracking the targets using skin and clothes color based features. We have developed the evaluation system implementing our proposed method. From the experimental results, we have achieved high accuracy detection rate and tracked the specific target precisely.
Journal Title
International Journal of Advanced Intelligence
ISSN
18833918
Publisher
AIA International Advanced Information Institute
Volume
9
Issue
3
Start Page
397
End Page
407
Published Date
2017-09
EDB ID
FullText File
language
eng
TextVersion
Publisher
departments
Science and Technology
Technical Support Department