如约而至
Lv6
1805 积分
2020-12-13 加入
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感谢,点赞,速度真快,帮大忙了
1年前
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嗯嗯好的
2年前
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有pdf版吗
2年前
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感谢,点赞,速度真快,帮大忙了
2年前
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感谢,点赞,速度真快,帮大忙了
2年前
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感谢,帮大忙了
2年前
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速度真快
2年前
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已找到【积分已退回】
2年前
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看错了 看到是2019的就
2年前
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The effective segmentation of point clouds is a prerequisite for surface reconstruction, blind spot repair, and so on. Among them, regional growth is widely used due to its simple and easy to implement algorithm. However, the traditional regional growth segmentation algorithm often causes problems such as over-segmentation or voiding of the segmentation result due to the instability of the local features of the point cloud or the unreasonable selection of the initial seed nodes. In view of the above shortcomings, this paper proposes an improved region growing point cloud algorithm. Firstly, by calculating the Gaussian curvature and the average curvature of the point cloud data and sorting them, and setting the minimum curvature point as the seed node, the total number of clusters is reduced, and the quality of the classification result is improved. Secondly, the growth of the point cloud region growth criterion is determined by combining the normal angles.
2年前