Chi-square goodness-of-fit test of 3D point correspondence for model similarity measure and analysis

Accurate and robust correspondence calculations are the pre-requisite step in many 3D model query and retrieval process. However, the correspondence problem is particularly difficult for 3D biomedical model surfaces, especially for roundish and approximate symmetric organs such as liver, stomach, kidney etc. In this paper, we define a new feature representation called the Neighborhood Relative Angle context Distribution (NRACD) for each vertex and, based upon it, we apply the Chi-Square Goodness-of-Fit test to establish 3D point correspondence. We further define the similarities between correspondence ready models by Chi-Square test statistic values. The experimental results demonstrate that this approach is efficient and robust for surface point matching and is particularly applicable to the retrieval and analysis of 3D deformable objects. © Springer-Verlag Berlin Heidelberg 2005.