3D Shape Classification Using Information Fusion

The intent of 3D-model classification is to find categories of similar objects according to their shapes. This task is a challenging and important problem in 3D-mining and shape processing. In this paper, we present a novel method to categorize 3D-objects based on view-based descriptors. The proposed method goes into two stages. The first stage corresponds to the training in which 3D-objects in the same category are processed and a set of representative 2D views is selected, The second stage corresponds to the labelling in which unknown objects are classified using a belief based classifier. The experimental results obtained on the Shrec07 datasets show that the system efficiently performs in categorizing 3D-models.