Illumination Estimation of 3D Surface Texture Based on Active Basis

This paper describes an approach to estimate illumination directions of 3D surface texture based on Active Basis. Instead of applying Gabor wavelet transform to extract texture features, we represent our texture features with a simple Haar feature to improve efficiency. The Active Basis model can be learned from training image patches by the shared pursuit algorithm. The base histogram can then be obtained based on each model. We measure the illumination directions by minimizing the Euclidean distance and the entropy difference of base histograms between the test image and the training sets. Experimental results demonstrate the effectiveness and accuracy of the proposed approach.