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학술지
Tracking and Face Recognition of Multiple People Based on GMM, LKT and PCA
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- 저자
- 이원오, 박영호, 이의철, 이희경, 박강령
- 발행일
- 201204
- 출처
- 멀티미디어학회논문지, v.15 no.4, pp.449-471
- ISSN
- 1229-7771
- 출판사
- 한국멀티미디어학회
- 협약과제
- 12PR4200, IPTV용 Interactive 시점제어 기술 개발, 차지훈
- 초록
- In intelligent surveillance systems, it is required to robustly track multiple people. Most of the previous studies adopted a Gaussian mixture model (GMM) for discriminating the object from the background. However, it has a weakness that its performance is affected by illumination variations and shadow regions can be merged with the object. And when two foreground objects overlap, the GMM method cannot correctly discriminate the occluded regions. To overcome these problems, we propose a new method of tracking and identifying multiple people. The proposed research is novel in the following three ways compared to previous research: First, the illuminative variations and shadow regions are reduced by an illumination normalization based on the median and inverse filtering of the L*a*b* image. Second, the multiple occluded and overlapped people are tracked by combining the GMM in the still image and the Lucas-Kanade-Tomasi (LKT) method in successive images. Third, with the proposed human tracking and the existing face detection & recognition methods, the tracked multiple people are successfully identified. The experimental results show that the proposed method could track and recognize multiple people with accuracy.
- KSP 제안 키워드
- Face detection, Foreground objects, GMM method, Gaussian mixture Model(GMM), Human tracking, Illumination Normalization, Illumination variations, Intelligent Surveillance, Inverse Filtering, Lucas-Kanade, Recognition method