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Face Detection Using Multi-level Features for Privacy Protection in Large-scale Surveillance Video
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 Title & Authors
Face Detection Using Multi-level Features for Privacy Protection in Large-scale Surveillance Video
Lee, Seung Ho; Moon, Jung Ik; Kim, Hyung-Il; Ro, Yong Man;
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 Abstract
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.
 Keywords
Face Detection;Multi-level Facial Feature;Privacy Protection;Large-scale Video Surveillance System;
 Language
Korean
 Cited by
1.
CNN 기반의 와일드 환경에 강인한 고속 얼굴 검출 방법,송주남;김형일;노용만;

한국멀티미디어학회논문지, 2016. vol.19. 8, pp.1310-1319 crossref(new window)
1.
Fast and Robust Face Detection based on CNN in Wild Environment, Journal of Korea Multimedia Society, 2016, 19, 8, 1310  crossref(new windwow)
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