This paper presents a local structural feature description of point cloud to efficiently extract local geometric and structure features from LIDAR data for 3-dimensional objective. This approach using hierarchical projection to maps neighbor points with different radial distance to multi-Mercator layers to obtain different distance information of neighbor points to key points. The Mercator projection, a conformal mapping method, the preserves geometric and structure relationship properly. The local features of key points can be obtained by calculating the distribution histogram of each Mercator planes with normalization method. Comparing the proposed approach with other hand-crafted feature extraction methods on Stanford Bologna dataset and 3Dmatch dataset, our methods outperform on descriptiveness, robustness to noise.
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