Inverse lighting for non-homogeneous objects from color and depth image using wavelet representation

This paper provides a novel approach to estimating the lighting given a pair of color and depth image of non-homogeneous objects. Existing methods can be classified into two groups depending on the lighting model, either the basis model or point light model. In general, the basis model is effective for low frequency lighting while the point model is suitable for high frequency lighting. Later, a wavelet based method combines the advantages from both sides of the basis model and point light model. Because it represents all frequency lighting efficiently, we use the wavelets to reconstruct the lighting. However, all of the previous methods cannot reconstruct lighting from non-homogeneous objects. Our main contribution is to process the non-homogeneous object by dividing it into multiple homogeneous segments. From these segments, we first initialize material parameters and extract lighting coefficients accordingly. We then optimize material parameters with the estimated lighting. The iteration is repeated until the estimated lighting converged. To demonstrate the effectiveness of our method, we conduct six different experiments corresponding to the different number, size, and position of lighting. Based on the experiment study, we confirm that our algorithm is effective for identifying the light map.