Estimating the missing Kinect depth information by polynomial fitting

The Microsoft Kinect enables real time 3D reconstruction of an indoor environment with low computational power by producing depth measurements with high resolution. Yet, the measured depth images are not in perfect quality because of the reflectance properties of the objects inside the scene. In this paper, we propose a novel depth prediction algorithm that is based on fitting a polynomial on the unknown depth locations. The parameters of the polynomials are found using the features and the depth measures of the pixels with known depth value. We conducted several experiments on different images and achieved predicting the depth of unknown locations with low error.