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얼굴인식 및 검색을 위한 얼굴영상의 특징추출에 관한 연구
이완주 용인대학교 자연과학연구소 2002 自然科學硏究所論文誌 Vol.7 No.1
This paper proposes an efficient method for detecting facial features, such as location of eye and mouth. Pupils are detected using features bases on the eye's shape. Supervised pixel-based classifications are employed to mark all pixels that are within predefined distances of skin color and lop color respectively. A pupil is detected using a function based on the difference of gray levels between pupil and sclera. Finally, a cost function is introduced to search eyes and mouse.
이완주 용인대학교 자연과학연구소 2008 自然科學硏究所論文誌 Vol.13 No.1
Object tracking in a real time environment is one of challenging subjects in computer vision area during past couple of years. This paper proposes a method of object detection and tracking using adaptive background estimation in real time environment. To obtain a stable and adaptive background, we combine 3-frame differential method and running average single gaussian background model. Using this background model, we can successfully detect moving objects while minimizing false moving objects caused by noise. In the tracking phase, we propose a matching criteria where the weight of position and inner brightness distribution can be controlled by the size of objects. Also, we adopt a Kalman Filter to overcome the occlusion of tracked objects. By experiments, we can successfully detect and track objects in real time environment.