Shape Complexity from Image Similarity
Danyi Wang, Alexander G. Belyaev, Waqar Saleem, Hans‐Peter Seidel · MPG.PuRe (Max Planck Society) · 2008
We present an approach to automatically compute the complexity of a given 3D shape. Previous approaches have made use of geometric and/or topological properties of the 3D shape to compute complexity. Our approach is based on shape appearance and estimates the complexity of a given 3D shape according to how 2D views of the shape diverge from each other. We use similarity among views of the 3D shape as the basis for our complexity computation. Hence our approach uses claims from psychology that humans mentally represent 3D shapes as organizations of 2D views and, therefore, mimics how humans gauge shape complexity. Experimental results show that our approach produces results that are more in agreement with the human notion of shape complexity than those obtained using previous approaches.