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http://dx.doi.org/10.9723/jksiis.2015.20.2.045

Integral Histogram-based Framework for Rapid Object Tracking  

Ko, Jaepil (금오공과대학교 컴퓨터공학과)
Ahn, Jung-Ho (강남대학교 컴퓨터공학부)
Hong, Won-Kee (대구대학교 멀티미디어학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.20, no.2, 2015 , pp. 45-56 More about this Journal
Abstract
In this paper we propose a very rapid moving object tracking method for an object-based auto focus on a smart phone camera. By considering the limit of non-learning approach on low-performance platforms, we use a sliding-window detection technique based on histogram features. By adapting the integral histogram, we solve the problem of the time-consuming histogram computation on each sub-window. For more speed up, we propose a local candidate search, and an adaptive scaling template method. In addition, we propose to apply a stabilization term in the matching function for a stable detection location. In experiments on our dataset, we demonstrated that we achieved a very rapid tracking performance demonstrating over 100 frames per second on a PC environment.
Keywords
Object Detection; Tracking; Integral Histogram; Histogram Matching;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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