An Efficient and Compact 3D Local Descriptor Based on the Weighted Height Image Abstract   3D local descriptors are the fundamental and essential elements that have been commonly applied in 3D computer vision. This paper proposes a novel and effective 3D local descriptor for describing the 3D local shape. The research focuses on accelerating the descriptor generation by simplifying the Local Reference Frame (LRF) and optimizing the feature space through a Weighted Height Image (WHI). An indepth theoretical analysis of the LRF is conducted. Then, this study proposes a simplified LRF to reduce the redundant computations of the covariance matrix and share the calculations with the 3D information coding. Besides, the feature space is modeled and analyzed in this paper. Based on the analysis, we propose a weighting function to strengthen the abilities of the feature representation. The experimental results indicate that the proposed WHI descriptor outperforms the stateoftheart (SOTA) algorithms in terms of accuracy and efficiency. Meanwhile, the compactness of the WHI is about six times more than that of the SOTA algorithms. Moreover, for the application of point cloud registration, the proposed WHI exhibits high effectiveness in terms of both accuracy and realtime capability.

3D Feature Matching for Point Cloud Object Extraction Effective object extraction plays an important role in many point cloudbased applications. This letter proposes a 3D feature matching framework for point cloud object extraction. To determine the optimal affine transformation parameters for each template feature point, a convex dissimilarity function and the locally affineinvariant geometric constraints are designed to construct the overall objective function. The 3D feature matching framework is integrated into a point cloud object extraction workflow. Extraction results on six test data sets show that average completeness, correctness, quality, and    F_1   measure of 0.96, 0.97, 0.93, and 0.96, respectively, are obtained in extracting light poles, vehicles, and palm trees. Comparative studies also confirm that the proposed method performs effectively and robustly, and exhibits superior or compatible performance over the other compared methods.