{"id":5961,"date":"2023-04-06T11:25:08","date_gmt":"2023-04-06T03:25:08","guid":{"rendered":"https:\/\/www.neuvition.cn\/?p=5961"},"modified":"2023-05-06T09:50:06","modified_gmt":"2023-05-06T01:50:06","slug":"%e5%88%86%e5%89%b2%e7%ae%97%e6%b3%95","status":"publish","type":"post","link":"https:\/\/www.neuvition.cn\/technology-blog\/%e5%88%86%e5%89%b2%e7%ae%97%e6%b3%95.html","title":{"rendered":"\u5206\u5272\u7b97\u6cd5"},"content":{"rendered":"\n

\u5206\u5272\u7b97\u6cd5\uff1a\u8fd9\u4e9b\u7b97\u6cd5\u6839\u636e\u70b9\u7684\u5c5e\u6027\uff08\u4f8b\u5982\u989c\u8272\u3001\u5f3a\u5ea6\u3001\u53cd\u5c04\u7387\u7b49\uff09\u5c06\u5b83\u4eec\u5206\u7ec4\uff0c\u4ee5\u8bc6\u522b\u573a\u666f\u4e2d\u7684\u5bf9\u8c61\u6216\u7279\u5f81\u3002<\/p>\n\n\n\n

\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u5206\u5272\u7b97\u6cd5\u5e94\u7528<\/strong><\/p>\n\n\n\n

\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u5206\u5272\u7b97\u6cd5\u7528\u4e8e\u57fa\u4e8e\u51e0\u4f55\u5f62\u72b6\u3001\u53cd\u5c04\u7387\u6216\u989c\u8272\u7b49\u7279\u5f81\u5c06\u70b9\u4e91\u5212\u5206\u4e3a\u4e0d\u540c\u7684\u6bb5\u3002\u8be5\u6280\u672f\u5177\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u5305\u62ec\u76ee\u6807\u8bc6\u522b\u548c\u8ddf\u8e2a\u3001\u81ea\u52a8\u9a7e\u9a76\u548c\u57ce\u5e02\u89c4\u5212\u3002\u4f8b\u5982\uff0c\u5728\u81ea\u52a8\u9a7e\u9a76\u4e2d\uff0c\u6fc0\u5149\u96f7\u8fbe\u5206\u5272\u88ab\u7528\u6765\u68c0\u6d4b\u548c\u8ddf\u8e2a\u884c\u4eba\u3001\u8f66\u8f86\u548c\u9053\u8def\u4e0a\u7684\u5176\u4ed6\u969c\u788d\u7269\u3002\u5728\u57ce\u5e02\u89c4\u5212\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5b83\u6765\u8bc6\u522b\u548c\u5206\u6790\u5efa\u7b51\u7269\u3001\u9053\u8def\u548c\u5176\u4ed6\u57fa\u7840\u8bbe\u65bd\u7684\u7279\u5f81\u3002\u603b\u4f53\u800c\u8a00\uff0c\u6fc0\u5149\u96f7\u8fbe\u5206\u5272\u7b97\u6cd5\u5bf9\u4ece\u70b9\u4e91\u6570\u636e\u63d0\u53d6\u6709\u7528\u4fe1\u606f\u5e76\u5728\u5404\u4e2a\u9886\u57df\u5b9e\u73b0\u667a\u80fd\u51b3\u7b56\u81f3\u5173\u91cd\u8981\u3002<\/p>\n\n\n\n

\u4ee5\u4e0b\u662f\u5341\u79cd\u5e38\u89c1\u7684LiDAR\u70b9\u4e91\u5206\u5272\u7b97\u6cd5\u53ca\u5176\u7b80\u8981\u63cf\u8ff0\u53ca\u4e0b\u8f7dURL\uff1a<\/strong><\/p>\n\n\n\n

1. Region Growing\uff08\u533a\u57df\u751f\u957f\uff09\uff1a\u6b64\u7b97\u6cd5\u5c06\u5177\u6709\u76f8\u4f3c\u5c5e\u6027\uff08\u5982\u989c\u8272\u6216\u5f3a\u5ea6\uff09\u7684\u76f8\u90bb\u70b9\u7ec4\u5408\u6210\u6bb5\u3002\u8be5\u7b97\u6cd5\u901a\u8fc7\u8fed\u4ee3\u5730\u6dfb\u52a0\u76f8\u90bb\u70b9\u5230\u6bb5\u4e2d\uff0c\u76f4\u5230\u4e0d\u80fd\u518d\u6dfb\u52a0\u4e3a\u6b62\u3002\u4e0b\u8f7dURL\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl\/segmentation\/region_growing.h<\/p>\n\n\n\n

2.Mean Shift\uff08\u5747\u503c\u6f02\u79fb\uff09\uff1a\u6b64\u7b97\u6cd5\u901a\u8fc7\u8fed\u4ee3\u5730\u5c06\u70b9\u5411\u5176\u5c40\u90e8\u5206\u5e03\u7684\u6a21\u5f0f\u79fb\u52a8\uff0c\u76f4\u81f3\u6536\u655b\u6765\u8bc6\u522b\u6bb5\u3002\u5b83\u53ef\u7528\u4e8e\u805a\u7c7b\u6216\u70b9\u4e91\u5206\u5272\u3002<\/p>\n\n\n\n

\u4e0b\u8f7dURL\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl\/segmentation\/impl\/mean_shift.hpp<\/p>\n\n\n\n

3. Euclidean Cluster Extraction\uff08\u6b27\u51e0\u91cc\u5f97\u805a\u7c7b\u63d0\u53d6\uff09\uff1a\u6b64\u7b97\u6cd5\u6839\u636e\u6b27\u51e0\u91cc\u5f97\u8ddd\u79bb\u5c06\u63a5\u8fd1\u7684\u70b9\u7fa4\u7ec4\u5408\u6210\u7fa4\u96c6\u3002\u5b83\u53ef\u7528\u4e8e\u5c06\u70b9\u4e91\u5212\u5206\u4e3a\u4e0d\u540c\u7684\u5bf9\u8c61\u6216\u533a\u57df\u3002<\/p>\n\n\n\n

\u4e0b\u8f7dURL\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl \/ segmentation \/ extract_clusters.h<\/p>\n\n\n\n

4.Conditional Euclidean Clustering\uff08\u6761\u4ef6\u6b27\u51e0\u91cc\u5f97\u805a\u7c7b\uff09\uff1a\u6b64\u7b97\u6cd5\u5c06\u6ee1\u8db3\u7ed9\u5b9a\u6761\u4ef6\uff08\u5982\u63a5\u8fd1\u5ea6\u548c\u989c\u8272\u76f8\u4f3c\u6027\uff09\u7684\u70b9\u7ec4\u5408\u6210\u7fa4\u96c6\u3002\u5b83\u53ef\u7528\u4e8e\u5c06\u70b9\u4e91\u5212\u5206\u4e3a\u6709\u610f\u4e49\u7684\u5bf9\u8c61\u6216\u533a\u57df\u3002<\/p>\n\n\n\n

\u4e0b\u8f7dURL: https:\/\/github.com \/ PointCloudLibrary \/ pcl \/ blob \/ master \/ segmentation \/ include \/ pcl \/ segmentation conditional_euclidean_clustering.h<\/p>\n\n\n\n

5.Split and Merge\uff08\u62c6\u5206\u4e0e\u5408\u5e76\uff09: \u6b64\u7b97\u6cd5\u57fa\u4e8e\u6807\u51c6\uff08\u4f8b\u5982\u5e73\u9762\u6027\u6216\u66f2\u7387\uff09\u9012\u5f52\u5730\u5c06\u70b9\u4e91\u62c6\u5206\u6210\u8f83\u5c0f\u7684\u7247\u6bb5\uff0c\u7136\u540e\u6839\u636e\u5b83\u4eec\u7684\u76f8\u4f3c\u6027\u5c06\u5b83\u4eec\u5408\u5e76\u3002\u5b83\u53ef\u7528\u4e8e\u5c06\u70b9\u4e91\u62c6\u5206\u4e3a\u5177\u6709\u4e0d\u540c\u5f62\u72b6\u548c\u5927\u5c0f\u7684\u5bf9\u8c61\u3002<\/p>\n\n\n\n

\u4e0b\u8f7dURL\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl\/segmentation\/sac_segmentation.h<\/p>\n\n\n\n

6.Connected Components\uff08\u8fde\u901a\u5206\u91cf\uff09: \u6b64\u7b97\u6cd5\u5c06\u7531\u8fb9\u8fde\u63a5\u7684\u70b9\u7ec4\u6210\u8fde\u901a\u5206\u91cf\uff0c\u53ef\u7528\u4e8e\u5c06\u70b9\u4e91\u5212\u5206\u4e3a\u5bf9\u8c61\u6216\u533a\u57df\u3002<\/p>\n\n\n\n

\u4e0b\u8f7dURL\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl \/ segmentation \/ connected_components.h<\/p>\n\n\n\n

7.Graph-based Segmentation\uff08\u57fa\u4e8e\u56fe\u50cf\u7684\u5206\u5272\uff09: \u6b64\u7b97\u6cd5\u901a\u8fc7\u6784\u5efa\u4e00\u4e2a\u56fe\u5f62\u6765\u5c06\u70b9\u4e91\u5206\u5272\u6210\u533a\u57df\uff0c\u5176\u4e2d\u6bcf\u4e2a\u70b9\u662f\u4e00\u4e2a\u8282\u70b9\uff0c\u8fb9\u8fde\u63a5\u76f8\u90bb\u7684\u70b9\u3002\u7136\u540e\u901a\u8fc7\u6700\u5c0f\u5316\u8003\u8651\u8282\u70b9\u76f8\u4f3c\u6027\u548c\u8fde\u901a\u6027\u7684\u80fd\u91cf\u51fd\u6570\u6765\u5bf9\u5c5e\u4e8e\u540c\u4e00\u6bb5\u843d\u4e2d\u7684\u8282\u70b9\u8fdb\u884c\u5206\u7ec4\u3002
\u4e0b\u8f7d\u94fe\u63a5\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl\/segmentation\/graph_based_segmentation.h<\/p>\n\n\n\n

8. Supervoxel Clustering\uff08\u8d85\u4f53\u7d20\u805a\u7c7b\uff09\uff1a\u8be5\u7b97\u6cd5\u5c06\u70b9\u4e91\u5206\u5272\u6210\u8d85\u4f53\u7d20\uff0c\u8fd9\u4e9b\u8d85\u4f53\u7d20\u662f\u70b9\u4e91\u7684\u7d27\u51d1\u3001\u50cf\u7d20\u5316\u8868\u793a\uff0c\u4fdd\u7559\u4e86\u51e0\u4f55\u548c\u62d3\u6251\u7ed3\u6784\u3002\u5b83\u53ef\u4ee5\u7528\u4e8e\u63d0\u53d6\u6bcf\u4e2a\u8d85\u4f53\u7d20\u7684\u6cd5\u7ebf\u548c\u989c\u8272\u7b49\u7279\u5f81\u3002<\/p>\n\n\n\n

\u4e0b\u8f7d\u94fe\u63a5\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl\/segmentation\/supervoxel_clustering.h<\/p>\n\n\n\n

9. Expectation-Maximization Clustering\uff08\u671f\u671b\u6700\u5927\u5316\u805a\u7c7b\uff09\uff1a\u8be5\u7b97\u6cd5\u5c06\u70b9\u4e91\u5efa\u6a21\u4e3a\u9ad8\u65af\u6df7\u5408\u7269\uff0c\u5e76\u4f7f\u7528\u671f\u671b\u6700\u5927\u5316\u7b97\u6cd5\u4f30\u8ba1\u9ad8\u65af\u6df7\u5408\u7269\u7684\u53c2\u6570\u3002\u5b83\u53ef\u4ee5\u6839\u636e\u7edf\u8ba1\u5c5e\u6027\u5c06\u70b9\u4e91\u805a\u7c7b\u5230\u4e0d\u540c\u7684\u5bf9\u8c61\u6216\u533a\u57df\u4e2d\u3002<\/p>\n\n\n\n

\u4e0b\u8f7d\u94fe\u63a5\uff1ahttps:\/\/github.com\/PointCloudLibrary\/pcl\/blob\/master\/segmentation\/include\/pcl\/segmentation\/impl\/em.h<\/p>\n\n\n\n

10.Convex Hull-based Segmentation\uff08\u57fa\u4e8e\u51f8\u5305\u7684\u5206\u5272\u662f\u4e00\u79cd\u56fe\u50cf\u5206\u5272\u6280\u672f\uff09\uff0c\u5b83\u4f7f\u7528\u4e00\u7ec4\u70b9\u7684\u51f8\u5305\u6765\u5b9a\u4e49\u56fe\u50cf\u4e2d\u5bf9\u8c61\u7684\u8fb9\u754c\u3002\u5b83\u9996\u5148\u627e\u5230\u5c5e\u4e8e\u7279\u5b9a\u5bf9\u8c61\u7684\u6240\u6709\u56fe\u50cf\u4e2d\u7684\u70b9\uff0c\u7136\u540e\u4f7f\u7528\u8fd9\u4e9b\u70b9\u521b\u5efa\u4e00\u4e2a\u51f8\u5305\u6765\u5b9a\u4e49\u8be5\u5bf9\u8c61\u7684\u8fb9\u754c\u3002<\/p>\n\n\n\n

\u4e0b\u8f7d\u94fe\u63a5\uff1ahttps:\/\/github.com\/search?q=Convex+Hull-based+Segmentation&type=<\/p>\n","protected":false},"excerpt":{"rendered":"

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