A Parametric Model for Describing the Correlation Between Single Color Images and Depth Maps

Abstract

This letter introduces a new approach for modeling the correlation between a single color image and its depth map with a set of parameters. The proposed model treats the color image as a set of patches and describes the correlation with a kernel function in a non-linear mapping space. We also present how to estimate the model parameters from sampled color image patches as well as the corresponding depth values. The proposed approach is tested on different color images and experimental results are comparable to the state-of-the-art, which demonstrates the power of the proposed method. Furthermore, we validate the efficiency of the proposed parametric model by evaluating each of its component, including the filters optimization, the choice of the patches and the kernel function.