AOMC: An Adaptive Point Cloud Clustering Approach for Feature Extraction

Figure 8

Comparison of point cloud feature sampling point between AOMC and random sampling. A total of 10m24 feature points are collected for each point cloud model; the left is random sampling; and the right is using AOMC to sample feature points. (a) Details of the wing are lost by random sampling. (b) and (c) Point cloud distribution of AOMC is more uniform than random sampling. (a) Airplane, (b) chair, and (c) car.

(a)

(b)

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