NDLI: On-line boosting based real-time tracking with efficient HOG

Content Provider	IEEE Xplore Digital Library
Author	Shuifa Sun Qing Guo Fangmin Dong Bangjun Lei
Copyright Year	2013
Description	Author affiliation: Inst. of Intell. Vision & Image Inf., China Three Gorges Univ., Yichang, China (Shuifa Sun; Qing Guo; Fangmin Dong; Bangjun Lei)
Abstract	In this paper, a real-time visual tracking system that delivers superior performance under difficult situations is proposed. The system is based on Histogram of Oriented Gradient (HOG) within the on-line boosting framework. For environmental adaptation, the HOG feature is calculated with blocks of random scale, position and aspect ratio which form a feature pool. The on-line boosting can then select the best distinguishable features from this pool for the robust tracking. The randomness of the blocks guarantees the existence of those features. Three experiments are conducted to highlight different characteristics of this new system. The first experiment proves the validity for the system to be able to pick out the best possible HOG features. The second experiment shows its robustness against bad illuminations and small foreground background difference. The third experiment demonstrates its advancement compared with the Haar-based state-of-the-art system. All those are offered without sacrificing the computation load.
Starting Page	2297
Ending Page	2301
File Size	705913
Page Count	5
File Format	PDF
ISBN	9781479903566
ISSN	15206149
DOI	10.1109/ICASSP.2013.6638064
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-26
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Boosting Lighting Robustness Real-time systems Histograms Classification algorithms Error analysis Random feature template Histograms of Oriented Gradient (HOG) on-line boosting integral histogram
Content Type	Text
Resource Type	Article

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