Silhouette Extraction in Hough Space

Object-space silhouette extraction is an important problem in fields ranging from non-photorealistic computer graphics to medical robotics. We present an efficient silhouette extractor for triangle meshes under perspective projection and make three contributions. First, we describe a novel application of 3D Hough transforms, which allows us to organize mesh data more effectively for silhouette computations than the traditional dual transform. Next, we introduce an incremental silhouette update algorithm which operates on an octree augmented with neighbour information and optimized for efficient low-level traversal. Finally, we present a method for initial extraction of silhouette, using the same data structure, whose performance is linear in the size of the extracted silhouette. We demonstrate significant performance improvements given by our approach over the current state of the art.