Unsupervised Texture Segmentation on Graphics Hardware Chris White Data Driven Graphics Problem Statement Given an image, segment into regions of similar texture Perform segmentation quickly – hopefully in real time Method Transform each pixel in the input image into a feature vector that captures local structure Cluster resulting feature vectors into Feature vectors Smooth the structure tensor via nonlinear diffusion GPU implementation is straight forward Segmentation of Features K-means or Level set Non-trivial GPGPU work Metrics for Success Efficiency – wall clock comparison to CPU algorithm Accuracy – for synthetic scenes consisting of objects textured with examples from Brodatz texture database, ground truth is known and error can be computed Several Brodatz textures