Non-parametric depth calibration of a TOF camera

Time-of-Flight (TOF) cameras measure, in real-time, the distance between the camera and objects in the scene. This opens new perspectives in different application fields: 3D reconstruction, Augmented Reality, video-surveillance, etc. However, like any sensor, TOF cameras have limitations related to their technology. One of them is distance distortion. In this paper, we present a new depth calibration method (estimation of distance distortion) for TOF cameras. Our approach has several advantages. First, it is based on a non-parametric model, contrary to most of the other methods. Second, it models under the same formalism the distortion variation according to the distance and the pixel position in the image. This improves calibration accuracy even at the image boundaries which are typically more distorted than the image center. A comparison with two state of the art parametric methods is presented.