3D Object Classification by Part Features Fusion

摘要

The paper proposes a part-level features fusion method for 3D object classification. 3D object is represented as a combination of its constituent parts, which are reconstructed by superquadric models. The presented classification method is decomposed into three main phrases: part features extraction of 3D objects, training set construction and classification implementation. Experimental results show the validity and potential of the presented method for part-level 3D object classification.