A Rapid Pretreatment Method For Object Detection in Dynamic Scenes - Volume 3 Number 2 (Apr. 2014) - IJFCC
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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Google Scholar,  Crossref, Electronic Journals LibraryEI (INSPEC, IET), etc.
    • E-mail:  ijfcc@ejournal.net 
Editor-in-chief
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2014 Vol.3(2): 119-123 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2014.V3.281

A Rapid Pretreatment Method For Object Detection in Dynamic Scenes

Zhenming Nong, Yuesheng Zhu, and Hao Lai
Abstract—In this paper, an efficient approach is proposed to improve detection efficiency of sliding window based detection methods by setting adaptive thresholds for regular object detection in the moving environment. In the proposed approach, the symmetry and variance (SYM-VAR) information of targets is learned from current frame and historical frames, and the information is used to filter out the sub-windows which may not contain the targets in the next frame. Our experimental results have demonstrated that the proposed approach can reduce nearly 50% of the average detection time with a small tradeoff of accuracy compared to typical HOG-based (histogram of oriented gradient) methods.

Index Terms—Adaptive online learning, variance, symmetry, sliding window detection.

The authors are with the Communication and Information Security Lab, Shenzhen Graduate School, Peking University, China (e-mail: zhuys@pkusz.edu.cn).

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Cite:Zhenming Nong, Yuesheng Zhu, and Hao Lai, "A Rapid Pretreatment Method For Object Detection in Dynamic Scenes," International Journal of Future Computer and Communication vol. 3, no. 2, pp. 119-123, 2014.

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