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http://dx.doi.org/10.5302/J.ICROS.2007.13.11.1074

AdaBoost-based Real-Time Face Detection & Tracking System  

Kim, Jeong-Hyun (부산대학교 기계공학부)
Kim, Jin-Young (동명대학교 메카트로닉스공학과)
Hong, Young-Jin (동명대학교 전기전자공학과)
Kwon, Jang-Woo (동명대학교 컴퓨터공학과)
Kang, Dong-Joong (부산대학교 기계공학부)
Lho, Tae-Jung (동명대학교 메카트로닉스공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.13, no.11, 2007 , pp. 1074-1081 More about this Journal
Abstract
This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.
Keywords
face detection; AdaBoost; CAMShift; real-time processing; computer vision;
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