Privacy-conscious human detection using low-resolution video
Nobuhiro Miyazaki, Kentaro Tsuji, Mingxie Zheng, Moyuri Nakashima, Yuji Matsuda, Eigo Segawa · 2015
We propose a human detection method for obtaining human flow information from low-resolution video generated by existing surveillance cameras. To use cameras in public spaces, it is necessary to protect the privacy of individuals appearing in the videos. We use low-resolution video in which individuals cannot be identified. In low-resolution video, human detection is more difficult than in high-resolution video because the human region consists of few pixels and has little information. Furthermore, it is challenging to detect an individual when others are captured nearby or occluded the individual. The proposed method offers detection based on the shape of the head, which is kept in a low-resolution image. In addition, to reduce false positives, which occur when detecting heads with simple shapes, head candidates are verified using the shape of the upper-body. The experimental results indicate a detection rate higher than 70% when the head width is from three to eight pixels (corresponding to about 20 to 50 pixels of the human height) in 428 people.