People sensing occurs everywhere, in the Internet of Things (IoT). Cameras are being increasingly used because they provide inexpensive and effective sensing devices. However, the camera acquires the information that identifies an individual, there is a problem that the privacy of the person is invaded. Furthermore, since home appliances are increasingly being connected to the Internet via the IoT, it has become possible for user images to leak out unintentionally. With these concerns in mind, we propose a face detection method that protects user privacy by using intentionally blurred images. In this method, the presence of a human being is determined by dividing an image into several regions and then calculating the heart rate detected in each region. In our performance evaluation, the proposed method showed dominant performance results when compared with an existing face detection method, and was confirmed to be an effective method for detecting faces in both normal and blurred images. We confirmed the influence of the performance in the proposed method when changing the sharpness of the images. The proposed method also showed high accuracy position detection performance results. Furthermore, we confirmed the effectiveness of the proposed method in near-infrared images and distorted images.
J-STAGEがリニューアルされました! https://www.jstage.jst.go.jp/browse/-char/ja/
