Abstract: We present an information-theoretic framework to compute the shape similarity between 3D polygonal models. From an information channel between a sphere of viewpoints and the polygonal mesh of a model, an information sphere is obtained and used as a shape descriptor of the model. Given two models, the minimum distance between their information spheres, the distance between their information histograms, and the difference of their mutual information are introduced as methods to calculate the similarity matrix between 3D models. The performance of these techniques is tested using the Princeton Shape Benchmark database.