Improved 3D Local Feature Descriptor Based on Rotational Projection Statistics and Depth Information

3D local feature descriptor construction is a very challenging task in the field of 3D model analysis. In this paper, an improved Rotational Projection Statistics (IRoPS) descriptor is proposed. For each feature point, the local coordinate system is firstly built and its neighboring points are normalized. Then the normalized neighboring points are rotated and projected onto three coordinate planes. For each rotation, the distribution matrix is computed and the subdescriptor can be obtained using the central moment, the Shannon entropy, the mean and variance of local depth values. Finally the IRoPS descriptor is constructed by concatenating all the sub-descriptors into a vector. Compared with the Rotational Projection Statistics (RoPS) descriptor, the IRoPS descriptor includes the local depth information and it has better discriminative power. Extensive experiments are performed to verify the superior performance of the proposed descriptor.