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FIS: Facial Information Segmentation for Video Redaction

机译:FIS:视频重放面部信息分割

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The camera is a ubiquitous and inseparable part of our daily life. However, the camera also puts people's privacy at risk because people are more likely to be unexpectedly captured due to the increased amount of cameras. Video redaction systems have been proposed to selectively redact facial information in a video. However, they are either not secure enough to protect all facial information or too secure to redact image areas not revealing facial information. To solve this problem, this paper proposes the Facial Information Segmentation algorithm (FIS) that combines the Harris Corner, the color information and an off-the-shelf face detection algorithm to identify pixels revealing facial information. We evaluate this method by comparing it with the human trace tracking (HTT) and an off-the-shelf face detection algorithm (FD) proposed in earlier works. The result demonstrates that FD is unsuitable for video redaction. Further, compared with HTT, FIS achieves higher background preservation with negligible loss of video privacy in most cases.
机译:相机是我们日常生活中普遍存在的和不可分割的一部分。然而,相机还将人们的隐私造成风险,因为由于摄像机的数量增加,人们更有可能意外地捕获。已经提出了视频缩放系统以在视频中选择性地重复面部信息。但是,它们要么不够安全,无法保护所有面部信息或过于安全,以减少未透露面部信息的图像区域。为了解决这个问题,本文提出了结合HARRIS角,颜色信息和特性面部检测算法的面部信息分割算法(FIS)来识别显示面部信息的像素。通过将其与人的迹线跟踪(HTT)与早期作品中提出的人的轨迹(HTT)进行比较来评估该方法。结果表明FD不适合视频重放。此外,与HTT相比,在大多数情况下,FIS实现了更高的背景保存,并且在大多数情况下可忽略可忽略的视频隐私。

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