An Euler Characteristic Curve Based Representation of 3DShapes in Statistical Analysis

Abstract

3D shape analysis is common in many fields such as medical science and biology. Analysis of original shape data is challenging and could be computationally heavy. A simplified representation of 3D shapes could help developing accessible shape analysis methods. In this paper we propose a method to generate a specific form of 3D shapes representation that could be applied in statistical analysis. We use Euler Characteristic curves to create the represention of shapes and utilize scaling function bases from diffusion wavelet to generate the representation. We discuss the details of our method and in the last we apply our method on a shape classification problem to test the performance of the representation.