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논문 기본 정보

저자정보
(KAIST) (SK Hynix) (KAIST) (KAIST)
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한국멀티미디어학회 멀티미디어학회논문지 멀티미디어학회논문지 제18권 제11호
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    초록·키워드

    In video surveillance system, the exposure of a person’s face is a serious threat to personal privacy. To protect the personal privacy in large amount of videos, an automatic face detection method is required to locate and mask the person’s face. However, in real-world surveillance videos, the effectiveness of existing face detection methods could deteriorate due to large variations in facial appearance (e.g., facial pose, illumination etc.) or degraded face (e.g., occluded face, low-resolution face etc.). This paper proposes a new face detection method based on multi-level facial features. In a video frame, different kinds of spatial features are independently extracted, and analyzed, which could complement each other in the aforementioned challenges. Temporal domain analysis is also exploited to consolidate the proposed method. Experimental results show that, compared to competing methods, the proposed method is able to achieve very high recall rates while maintaining acceptable precision rates.

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      UCI(KEPA) : I410-ECN-0101-2016-004-002159921