Face depth prediction by the scene depth

Depth map, also known as range image, can directly reflect the geometric shape of the objects. Due to several issues such as cost, privacy and accessibility, face depth information is not easy to obtain. However, the spatial information of faces is very important in many aspects of computer vision especially in the biometric identification. In contrast, scene depth information is related easier to obtain with the development of autonomous driving technology in recent years. An idea of face depth estimation inspired is to bridge the gap between the scene depth and the face depth. Previously, face depth estimation and scene depth estimation were treated as two completely separate domains. This paper proposes and explores utilizing scene depth knowledge learned to estimate the depth map of faces from monocular 2D images. Through experiments, we have preliminarily verified the possibility of using scene depth knowledge to predict the depth of faces and its potential in face feature representation.