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A Large-Scale Evaluation Of Shape-Aware Neighborhood Weights And Neighborhood Sizes
In this paper, we define and evaluate a weighting scheme for neighborhoods in point sets. Our weighting takes the shape of the geometry, i.e., the normal information, into account. This causes the obtained neighborhoods to be more reliable in the sense that connectivity also depends on the orientation of the point set. We utilize a sigmoid to define the weights based on the normal variation. For an evaluation of the weighting scheme, we turn to a Shannon entropy model for feature classificationdoi:10.1016/j.cad.2021.103107 fatcat:d3cavbpnuzcvld5uxle3zoejxa