Volume 9 Number 10 (Oct. 2014)
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JCP 2014 Vol.9(10): 2449-2454 ISSN: 1796-203X
doi: 10.4304/jcp.9.10.2449-2454

Efficient Surf Tracking by Nearest Neighbor Classifier

Minglei Tong1, Shudong Chen2
1School of Computer and Information, Shanghai University of Electric Power, Shanghai 201300, China
2Institute of Microelectronics of Chinese Academy of Sciences, Wuxi, China

Abstract—Visual object tracking is a fundamental problem in many real applications, like video security surveillance, human computer interaction (HCI), video communication and compression, augmented reality, traffic control, medical imaging and video editing. The common challenge towards this task is the ambiguity existing among object and the background. To differentiate object from background, SURF descriptor [12] is applied in this paper to enable the efficient tracking-by-detection. SURF descriptors are extracted only in region of interest in each frame, to ensure the tracker’s high efficiency. Under the recently proposed framework, nearest-neighbor criterion is used to match the corresponding feature points within or out of the object appearance. Efficient sub-window search method is applied to accelerate the searching process while without sacrificing to searching accuracy. Experimental results prove the proposed tracker could be used in a real time tracking scene.

Index Terms—Visual tracking, Feature extraction, Nearest neighbor classifier, Surf

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Cite: Minglei Tong, Shudong Chen, "Efficient Surf Tracking by Nearest Neighbor Classifier," Journal of Computers vol. 9, no. 10, pp. 2449-2454, 2014.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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