{"id":13973,"date":"2023-02-14T10:27:15","date_gmt":"2023-02-14T02:27:15","guid":{"rendered":"http:\/\/139.9.1.231\/?p=13973"},"modified":"2023-02-14T10:36:15","modified_gmt":"2023-02-14T02:36:15","slug":"mvson-of-multi-view-stereo-reconstruction-algorithms","status":"publish","type":"post","link":"http:\/\/139.9.1.231\/index.php\/2023\/02\/14\/mvson-of-multi-view-stereo-reconstruction-algorithms\/","title":{"rendered":"MVS\u5b66\u4e60&#8211;\u300aA Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms\u300b"},"content":{"rendered":"\n<h2 id=\"\u524d\u8a00\">1. \u524d\u8a00<\/h2>\n\n\n\n<p>Middlebury\u662f\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u4e09\u7ef4\u4e2d\u95f4\u9886\u57df\u8457\u540d\u7684\u9ad8\u6821\uff0c\u7279\u522b\u662f\u63d0\u4f9b\u4e86\u8457\u540d\u7684\u7acb\u4f53\u5339\u914dbenchmark\u6570\u636e\u5e93\uff0c\u5e76\u4e0d\u65ad\u63d0\u4f9b\u65b0\u6570\u636e\u7684\u66f4\u65b0\u3002\u5728MVS\u9886\u57df\uff0c\u4e5f\u540c\u6837\u63d0\u4f9b\u4e86\u7ecf\u5178\u7684benchmark\u6570\u636e\u5e93\uff0c\u5305\u542b\u4e24\u4e2a\u7269\u4f53-Temple\u548cDino\uff0c\u5176\u4e2dTemple\u6709312\u5f20\u76f8\u7247\uff0cDino\u6709363\u5f20\u76f8\u7247\uff0c\u5982\u4e0b\u56fe\u6240\u793a\u3002\u5e76\u4e14\u6bcf\u4e2a\u7269\u4f53\u8fd8\u63d0\u4f9b\u4e86\u7531\u6fc0\u5149Lidar\u6d4b\u91cf\u5f97\u5230\u7684\u5730\u9762\u771f\u503c\uff08Groud Truth\uff09\u6570\u636e\uff0c\u56e0\u6b64\u53ef\u4ee5\u7528\u6765\u51c6\u786e\u7684\u8861\u91cf\u4e0d\u540cMVS\u7b97\u6cd5\u7684\u51c6\u786e\u6027\uff08\u91cd\u5efa\u7684\u4e09\u7ef4\u6a21\u578b\u4e0e\u771f\u503c\u7684\u5dee\u5f02\uff09\u548c\u5b8c\u6574\u6027\uff08\u6709\u591a\u5c11\u771f\u503c\u5305\u542b\u5728\u91cd\u5efa\u7684\u4e09\u7ef4\u6a21\u578b\u4e2d\uff09\u3002<\/p>\n\n\n\n<p>\u5728\u5efa\u7acb\u8be5\u6570\u636e\u5e93\u7684\u8fc7\u7a0b\u4e2d\uff0cMiddlebury\u7684\u7814\u7a76\u56e2\u961f\u5206\u7c7b\u603b\u7ed3\u4e86\u5f53\u65f6\uff082006\u5e74\uff09\u7684state-of-art\u7684\u7b97\u6cd5\uff0c\u63d0\u51fa\u4e86\u7b97\u6cd5\u6709\u6548\u6027\u8bc4\u4ef7\u6807\u51c6\u3002\u57fa\u4e8e\u8be5\u6807\u51c6\uff0c\u5e76\u4f7f\u7528\u8be5\u6570\u636e\u5e93\u9a8c\u8bc1\u8fd9\u4e9b\u7b97\u6cd5\u7684\u6709\u6548\u6027\uff0c\u6700\u7ec8\u5f62\u6210\u8be5\u6587\u7ae0<a href=\"https:\/\/whuhenry.github.io\/posts\/40a4b471\/#fn1\"><sup>1<\/sup><\/a>\u3002\u8fd9\u7bc7\u6587\u7ae0\u662f\u540e\u6765\u51e0\u4e4e\u6bcf\u4e00\u7bc7\u7814\u7a76MVS\u7b97\u6cd5\u7684\u6587\u7ae0\u7684\u5fc5\u5f15\u53c2\u8003\u6587\u732e\uff0c\u5176\u4e2d\u5bf9\u4e8e\u7b97\u6cd5\u7684\u5206\u7c7b\u4ecb\u7ecd\u548c\u6709\u6548\u6027\u9a8c\u8bc1\u89c4\u5219\u5341\u5206\u7ecf\u5178\uff0c\u4e0b\u9762\u5206\u522b\u8fdb\u884c\u603b\u7ed3\u3002<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-387.png\" alt=\"\" class=\"wp-image-13980\" width=\"360\" height=\"504\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-387.png 636w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-387-214x300.png 214w\" sizes=\"(max-width: 360px) 100vw, 360px\" \/><\/figure><\/div>\n\n\n\n<h2 id=\"mvs\u7b97\u6cd5\u5206\u7c7b\">2. MVS\u7b97\u6cd5\u5206\u7c7b<\/h2>\n\n\n\n<p>MVS\u662f\u6307Multiview Stereo\uff0c\u5177\u4f53\u6765\u8bf4\u662f\u901a\u8fc7\u591a\u5e45\u5df2\u77e5\u62cd\u6444\u65b9\u4f4d\u4fe1\u606f\uff08\u5916\u65b9\u4f4d\u5143\u7d20\uff09\u7684\u56fe\u50cf\u6765\u4f30\u8ba1\u76ee\u6807\u4e09\u7ef4\u4fe1\u606f\u7684\u7b97\u6cd5\uff0c\u6570\u636e\u57fa\u4e8e\u56fe\u50cf\u7684\u4e09\u7ef4\u91cd\u5efa\u4e2d\u4e00\u5927\u7c7b\u975e\u5e38\u91cd\u8981\u548c\u5b9e\u7528\u7684\u7b97\u6cd5\u3002\u6587\u7ae0\u4e2d\u63d0\u5230\u7c7b\u4f3c\u7684\u65b9\u6cd5\u8fd8\u6709\u53cc\u76ee\u6216\u8005\u4e09\u76ee\u7acb\u4f53\u5339\u914d\u65b9\u6cd5\uff0c\u8fd9\u4e00\u7c7b\u65b9\u6cd5\u80fd\u591f\u83b7\u5f97\u5355\u4e00\u7684\u89c6\u5dee\u56fe\uff0c\u4f46\u662f\u53d7\u9650\u4e8e\u7167\u7247\u6570\u91cf\u548c\u62cd\u6444\u89d2\u5ea6\uff0c\u65e0\u6cd5\u8986\u76d6\u7269\u4f53\u7684\u5168\u90e8\u8868\u9762\u3002\u53e6\u4e00\u7c7b\u65b9\u6cd5\u662f\u591a\u57fa\u7ebf\u7acb\u4f53\u91cd\u5efa\u65b9\u6cd5\uff0c\u53ef\u4ee5\u6784\u5efa\u7a00\u758f\u7279\u5f81\u70b9\u96c6\u3002<\/p>\n\n\n\n<p>\u4e00\u822c\u6765\u8bf4\uff0cMVS\u53ef\u4ee5\u6309\u7167\u5982\u4e0b6\u4e2a\u65b9\u9762\u7684\u6807\u51c6\u8fdb\u884c\u5206\u7c7b\uff1a<\/p>\n\n\n\n<ol type=\"1\"><li>\u573a\u666f\u8868\u8fbe\u65b9\u5f0f\uff08scene representation);<\/li><li>\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5\uff08photo consistency measure\uff09\uff1b<\/li><li>\u53ef\u89c1\u6027\u6a21\u578b\uff08visible model\uff09\uff1b<\/li><li>\u5728\u91cd\u5efa\u65f6\u4f18\u5148\u8003\u8651\u7684\u5f62\u72b6\u7ea6\u675f\uff08shape prior\uff09\uff1b<\/li><li>\u91cd\u5efa\u7b97\u6cd5\uff08reconstruction algorithm\uff09\uff1b<\/li><li>\u521d\u59cb\u5316\u6761\u4ef6\uff08initialization requirements\uff09\u3002<\/li><\/ol>\n\n\n\n<p>\u4e0b\u9762\u5206\u522b\u5bf9\u6bcf\u4e2a\u65b9\u9762\u8fdb\u884c\u7b80\u5355\u7684\u63cf\u8ff0\u3002<\/p>\n\n\n\n<h3 id=\"\u573a\u666f\u8868\u8fbescene-representation\">2.1 \u573a\u666f\u8868\u8fbe\uff08Scene Representation\uff09<\/h3>\n\n\n\n<p>\u573a\u666f\u8868\u8fbe\u662f\u6307\u91cd\u5efa\u5f97\u5230\u7684\u4e09\u7ef4\u573a\u666f\u4f7f\u7528\u4ec0\u4e48\u6837\u7684\u6570\u5b66\u6a21\u578b\u8fdb\u884c\u8868\u8fbe\uff0c\u4e00\u822c\u6765\u8bf4\u6709\u5982\u4e0b4\u79cd\u65b9\u5f0f\uff1a<\/p>\n\n\n\n<ol type=\"1\"><li>\u4f53\u7d20\uff08Voxel\uff09<\/li><li>\u5c42\u6b21\u7ea7\uff08level set\uff09\uff1a\u8bb0\u5f55\u6bcf\u4e2a\u70b9\u5230\u67d0\u4e2a\u6700\u8fd1\u5e73\u9762\u7684\u8ddd\u79bb<\/li><li>\u591a\u8fb9\u5f62\u5b9e\u4f53\uff08polygon mesh\uff09\uff1a\u8fd9\u662f\u5e94\u8be5\u662f\u6211\u4eec\u6700\u719f\u6089\u7684\u8868\u8fbe\u65b9\u5f0f\uff0c\u4e5f\u662f\u4eba\u5de5\u4e09\u7ef4\u5efa\u6a21\u6700\u5e38\u89c1\u7684\u6570\u636e\u8868\u8fbe\u65b9\u5f0f<\/li><li>\u6df1\u5ea6\u56fe\uff08depth map\uff09\uff1a\u4e00\u822c\u57fa\u4e8e\u50cf\u65b9\u7acb\u4f53\u5339\u914d\u7b97\u6cd5\u7b97\u6cd5\u751f\u6210\u7684\u7ed3\u679c\u5c31\u662f\u6df1\u5ea6\u56fe\uff0c\u6bcf\u4e2a\u50cf\u7d20\u7684\u7070\u5ea6\u503c\u4ee3\u8868\u8be5\u50cf\u7d20\u8ddd\u79bb\u5f53\u524d\u56fe\u50cf\u5e73\u9762\u7684\u8ddd\u79bb\u3002<\/li><\/ol>\n\n\n\n<h3 id=\"\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5photo-consistency-measure\">2.2 \u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5\uff08Photo Consistency Measure\uff09<\/h3>\n\n\n\n<p>\u8fd9\u90e8\u5206\u548c\u53cc\u76ee\u7acb\u4f53\u5339\u914d\u4e2d\u7528\u5230\u7684\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5\u7c7b\u4f3c\uff0c\u4f46\u662f\u8003\u8651\u5230MVS\u672c\u8eab\u7684\u7279\u6b8a\u6027\uff0c\u4e00\u822c\u6765\u8bf4\uff0cMVS\u4e2d\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u6839\u636e\u641c\u7d22\u5185\u5bb9\u7684\u4e0d\u540c\u5206\u4e3a\u4ee5\u4e0b\u4e24\u79cd\u65b9\u6cd5<\/p>\n\n\n\n<h4 id=\"\u57fa\u4e8e\u7269\u65b9\u7684\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5\">1. \u57fa\u4e8e\u7269\u65b9\u7684\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5<\/h4>\n\n\n\n<p>\u901a\u5e38\u4f7f\u7528\u4f53\u7d20\u8868\u8fbe\u65b9\u6cd5\uff0c\u641c\u7d22\u7a7a\u95f4\u4e2d\u7684\u6bcf\u4e2a\u4f53\u7d20\u5728\u5bf9\u5e94\u4e24\u5e45\u56fe\u50cf\u4e2d\u7684\u6295\u5f71\u4f4d\u7f6e\u7684\u56fe\u50cf\u4e00\u81f4\u6027\uff0c\u5982\u679c\u8be5\u4e00\u81f4\u6027\u8ba1\u7b97\u503c\u5c0f\u4e8e\u67d0\u4e2a\u9608\u503c\uff0c\u5219\u8be5\u4f53\u7d20\u53ef\u4ee5\u8ba4\u4e3a\u662f\u4ee3\u8868\u4e86\u771f\u5b9e\u7269\u4f53\u3002<\/p>\n\n\n\n<h4 id=\"\u57fa\u4e8e\u50cf\u65b9\u7684\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5\">2. \u57fa\u4e8e\u50cf\u65b9\u7684\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u65b9\u6cd5<\/h4>\n\n\n\n<p>\u6839\u636e\u6781\u7ebf\u7ea6\u675f\uff0c\u5bf9\u4e8e\u4e00\u5e45\u56fe\u50cf\u7684\u67d0\u4e2a\u70b9\uff0c\u641c\u7d22\u5176\u5bf9\u5e94\u6781\u7ebf\u4e0a\u6700\u76f8\u4f3c\u7684\u5339\u914d\u70b9\uff08\u4e00\u81f4\u6027\u6700\u9ad8\uff09\uff0c\u8fd9\u79cd\u65b9\u6cd5\u901a\u5e38\u5728\u53cc\u76ee\u7acb\u4f53\u89c6\u89c9\u4e2d\u4f7f\u7528\u3002<\/p>\n\n\n\n<p>\u9700\u8981\u6ce8\u610f\u7684\u662f\u8fd9\u4e24\u79cd\u65b9\u6cd5\u90fd\u662f\u57fa\u4e8e\u7269\u4f53\u8868\u9762\u4e3aLambartian\u7684\u5047\u8bbe\uff0c\u4f46\u662f\u4e5f\u6709\u8fdb\u4e00\u6b65\u7684\u7814\u7a76\u5229\u7528BRDF\u8fdb\u884c\u8ba1\u7b97\uff0c\u6216\u8005\u8003\u8651\u7269\u4f53\u7684\u9634\u5f71\uff0c\u6d88\u9664\u7269\u4f53\u9634\u5f71\u5bf9\u4e8e\u4e00\u81f4\u6027\u8ba1\u7b97\u7684\u5f71\u54cd\u3002<\/p>\n\n\n\n<h3 id=\"\u53ef\u89c1\u6027\u6a21\u578bvisible-model\">2.3 \u53ef\u89c1\u6027\u6a21\u578b\uff08Visible Model\uff09<\/h3>\n\n\n\n<p>\u53ef\u89c1\u6027\u6a21\u578b\u662f\u5728\u8ba1\u7b97\u56fe\u50cf\u4e00\u81f4\u6027\u65f6\uff0c\u51b3\u5b9a\u7a76\u7adf\u54ea\u4e9b\u56fe\u50cf\u548c\u53c2\u8003\u56fe\u50cf\u6709\u5171\u89c6\u533a\u57df\uff0c\u53ef\u4ee5\u8fdb\u884c\u56fe\u50cf\u4e00\u81f4\u6027\u8ba1\u7b97\u7684\u65b9\u6cd5\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u6709\u5982\u4e0b\u4e09\u79cd\u6a21\u578b<\/p>\n\n\n\n<ul><li>\u51e0\u4f55\u6a21\u578b\u3002<\/li><li>\u51c6\u51e0\u4f55\u6a21\u578b\u3002<\/li><li>\u57fa\u4e8e\u7c97\u5dee\uff08outlier\uff09\u7684\u6a21\u578b\uff0c\u901a\u5e38\u662f\u5c06\u906e\u6321\u89c6\u4e3a\u7c97\u5dee\uff0c\u56e0\u4e3a\u5bf9\u4e8e\u4e00\u4e2a\u70b9\u6765\u8bf4\uff0c\u5728\u4e24\u89c6\u4e2d\u88ab\u770b\u5230\u7684\u53ef\u80fd\u6027\u5927\u4e8e\u88ab\u906e\u6321\u7684\u53ef\u80fd\u6027\u3002<\/li><\/ul>\n\n\n\n<h3 id=\"\u5728\u91cd\u5efa\u65f6\u4f18\u5148\u8003\u8651\u7684\u5f62\u72b6\u7ea6\u675fshape-prior\">2.4 \u5728\u91cd\u5efa\u65f6\u4f18\u5148\u8003\u8651\u7684\u5f62\u72b6\u7ea6\u675f\uff08Shape Prior\uff09<\/h3>\n\n\n\n<p>\u7531\u4e8e\u5e38\u89c1\u7684\u5f31\u7eb9\u7406\uff08\u5927\u8303\u56f4\u533a\u57df\u989c\u8272\u76f8\u540c\u6216\u8005\u76f8\u8fd1\uff09\u6216\u8005\u65e0\u7eb9\u7406\u7b49\u539f\u56e0\uff0c\u5bfc\u81f4\u5728\u5339\u914d\u662f\u5728\u8fd9\u4e9b\u533a\u57df\u65e0\u6cd5\u5f97\u5230\u826f\u597d\u7684\u5339\u914d\u7ed3\u679c\uff0c\u56e0\u6b64\u9700\u8981\u5f15\u5165\u5f62\u72b6\u7ea6\u675f\u6765\u8fd1\u4f3c\u7ea6\u675f\u8fd9\u4e9b\u533a\u57df\u7684\u53ef\u80fd\u5f62\u72b6\uff0c\u53ef\u4ee5\u4f7f\u5f97\u6700\u7ec8\u5f97\u5230\u7684\u573a\u666f\u5177\u6709\u67d0\u79cd\u7279\u6b8a\u7684\u6027\u8d28\u3002\u8fd9\u79cd\u65b9\u6cd5\u5728\u53cc\u76ee\u7acb\u4f53\u5339\u914d\u7684\u7814\u7a76\u4e2d\u662f\u6781\u4e3a\u5e38\u89c1\u7684\u65b9\u6cd5\uff0c\u4f46\u662f\u5728MVS\u4e2d\uff0c\u7531\u4e8e\u591a\u5e45\u56fe\u50cf\u63d0\u4f9b\u66f4\u5f3a\u7684\u7ea6\u675f\uff0c\u8f83\u5c11\u4f7f\u7528\u8fd9\u79cd\u65b9\u6cd5\u3002\u5e38\u89c1\u7684\u5f62\u72b6\u7ea6\u675f\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n\n\n\n<ol type=\"1\"><li>\u57fa\u4e8e\u573a\u666f\u91cd\u5efa\u7684\u6280\u672f\u901a\u5e38\u91c7\u7528\u201c\u6700\u5c11\u5e73\u9762\u6570\u201d\u7ea6\u675f\uff0c\u56e0\u4e3a\u8fc7\u591a\u7684\u591a\u8fb9\u5f62\u9762\u7247\u4f1a\u4f7f\u5f97\u573a\u666f\u8fc7\u4e8e\u7834\u788e\u3002<\/li><li>\u57fa\u4e8e\u4f53\u7d20\u548cSpace carve\u7684\u91cd\u5efa\u65b9\u6cd5\u901a\u5e38\u589e\u52a0\u201c\u6700\u591a\u5e73\u9762\u6570&#8221;\u7ea6\u675f\uff0c\u4f7f\u5f97\u8868\u9762\u5177\u6709\u66f4\u52a0\u4e30\u5bcc\u7684\u7ec6\u8282\u3002<\/li><li>\u5728\u57fa\u4e8e\u50cf\u65b9\u7684\u5339\u914d\u65b9\u6cd5\u4e2d\uff0c\u901a\u5e38\u6dfb\u52a0\u5c40\u90e8\u5e73\u6ed1\u7ea6\u675f\uff1a\u4f8b\u5982\u53cc\u76ee\u7acb\u4f53\u5339\u914d\u4e2d\u5e38\u89c1\u7684piece-wise smothness\uff0c\u5047\u8bbe\u573a\u666f\u4e2d\u7684\u5f31\u7eb9\u7406\u533a\u57df\u662f\u4e0e\u6444\u5f71\u5e73\u9762\u5e73\u884c\u7684\u5c0f\u5e73\u9762\u3002<\/li><\/ol>\n\n\n\n<h3 id=\"\u91cd\u5efa\u7b97\u6cd5reconstruction-algorithm\">2.5 \u91cd\u5efa\u7b97\u6cd5\uff08Reconstruction Algorithm\uff09<\/h3>\n\n\n\n<ol type=\"1\"><li>\u4f53\u7d20\u7740\u8272\u7b97\u6cd5\uff1a\u4ece\u4e00\u4e2avolumn\u4e2d\u63d0\u53d6\u4e00\u4e2a\u5e73\u9762\u51fa\u6765<\/li><li>\u901a\u8fc7\u9012\u63a8\u7684\u65b9\u6cd5\u5c55\u5f00\u4e00\u4e2a\u5e73\u9762\uff1a\u5728\u8fc7\u7a0b\u4e2d\u6700\u5c0f\u5316\u4ee3\u4ef7\u51fd\u6570\uff08based on voxels\uff0c level-set\uff0c mesh)<\/li><li>\u57fa\u4e8e\u50cf\u65b9\u7684\u5339\u914d\uff0c\u751f\u6210\u6df1\u5ea6\u56fe\uff0c\u5e76\u5bf9\u4e0d\u540c\u56fe\u50cf\u95f4\u7684\u6df1\u5ea6\u56fe\u8fdb\u884c\u878d\u5408<\/li><li>\u63d0\u53d6\u7279\u5f81\u70b9\uff0c\u62df\u5408\u4e00\u4e2a\u9762\u6765\u91cd\u5efa\u7279\u5f81<\/li><\/ol>\n\n\n\n<h3 id=\"\u521d\u59cb\u5316\u6761\u4ef6initialization-requirements\">2.6 \u521d\u59cb\u5316\u6761\u4ef6\uff08Initialization Requirements\uff09<\/h3>\n\n\n\n<ol type=\"1\"><li>\u9700\u8981\u56fe\u50cf\u96c6\uff08\u6bd5\u7adf\u662f\u57fa\u4e8e\u56fe\u50cf\u7684\u4e09\u7ef4\u91cd\u5efa\uff0c\u9700\u8981\u5c3d\u53ef\u80fd\u591a\u7684\u591a\u89d2\u5ea6\u62cd\u6444\u7684\u540c\u4e00\u573a\u666f\u7684\u56fe\u50cf\uff09<\/li><li>\u51e0\u4e4e\u6240\u6709\u7684\u7b97\u6cd5\u90fd\u8981\u6c42\u6216\u8005\u5047\u8bbe\u5f85\u91cd\u5efa\u4e09\u7ef4\u76ee\u6807\u7684\u7a7a\u95f4\u8303\u56f4\u6216\u8005scene geometry<\/li><li>\u57fa\u4e8e\u50cf\u65b9\u7684\u65b9\u6cd5\u8981\u6c42\u6700\u5927\/\u6700\u5c0f\u89c6\u5dee\uff08\u8fd9\u4e00\u70b9\u8981\u6c42\u548c2\u7c7b\u4f3c\uff09<\/li><\/ol>\n\n\n\n<h2 id=\"mvs\u7b97\u6cd5\u7684\u8bc4\u4ef7\">3. MVS\u7b97\u6cd5\u7684\u8bc4\u4ef7<\/h2>\n\n\n\n<p>\u6587\u7ae0\u4e2d\u63d0\u51fa\uff0c\u5bf9\u4e8eMVS\u7b97\u6cd5\u5e94\u8be5\u4ece\u4e00\u4e0b\u4e24\u4e2a\u65b9\u9762\u8fdb\u884c\u8bc4\u4ef7<\/p>\n\n\n\n<h3 id=\"\u51c6\u786e\u6027\">1. \u51c6\u786e\u6027<\/h3>\n\n\n\n<p>\u51c6\u786e\u6027\u662f\u6307\u91cd\u5efa\u7ed3\u679c\u4e0e\u771f\u503c\u95f4\u7684\u5dee\u8ddd\uff0c\u4e00\u822c\u65b9\u6cd5\u662f\uff0c\u5bf9\u4e8e\u91cd\u5efa\u7ed3\u679c\u4e2d\u7684\u4e00\u4e2a\u4e09\u7ef4\u7a7a\u95f4\u70b9\uff0c\u5bfb\u627e\u5176\u5bf9\u5e94\u771f\u503c\u4e2d\u7684\u70b9\uff0c\u8ba1\u7b97\u5176\u8ddd\u79bb\uff0c\u6700\u540e\u7edf\u8ba1\u6240\u6709\u70b9\u8ddd\u79bb\u771f\u503c\u7684\u8ddd\u79bb\u3002 \u6839\u636e\u7edf\u8ba1\u7ed3\u679c\u6765\u8bc4\u4ef7\u91cd\u5efa\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002<\/p>\n\n\n\n<h3 id=\"\u5b8c\u6574\u6027\">2. \u5b8c\u6574\u6027<\/h3>\n\n\n\n<p>\u5b8c\u6574\u6027\u662f\u6307\u6709\u591a\u5c11\u771f\u503c\u88ab\u5305\u542b\u5728\u91cd\u5efa\u7ed3\u679c\u4e2d\u3002\u4e00\u822c\u65b9\u6cd5\u4e0e\u51c6\u786e\u6027\u8ba1\u7b97\u7c7b\u4f3c\uff0c\u4f46\u662f\u662f\u8ba1\u7b97\u771f\u503c\u4e2d\u7684\u70b9\u5230\u91cd\u5efa\u7ed3\u679c\u4e2d\u6700\u8fd1\u70b9\u7684\u8ddd\u79bb\uff0c\u7edf\u8ba1\u6240\u6709\u771f\u503c\u70b9\u7684\u8ba1\u7b97\u7ed3\u679c\u6765\u8bc4\u4ef7\u91cd\u5efa\u7684\u5b8c\u6574\u6027\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u5982\u679c\u771f\u503c\u4e2d\u7684\u70b9\u8ddd\u79bb\u91cd\u5efa\u7ed3\u679c\u4e2d\u6700\u8fd1\u70b9\u7684\u8ddd\u79bb\u5927\u4e8e\u67d0\u4e2a\u9608\u503c\uff0c\u5219\u8ba4\u4e3a\u662f\u6ca1\u6709\u627e\u6253\u5339\u914d\u70b9\uff0c\u4e5f\u5c31\u662f\u8be5\u771f\u503c\u70b9\u6ca1\u6709\u88ab\u8986\u76d6\u3002<\/p>\n\n\n\n<h2 id=\"sfm\u7684\u91cd\u5efa\u6210\u679c\u662f\u7a00\u758f\u4e09\u7ef4\u70b9\u4e91\u4e3a\u4e86\u8fdb\u5165\u66f4\u52a0\u6df1\u523b\u7684\u9886\u57df\u83b7\u5f97\u66f4\u597d\u7684\u7ed3\u679c\u6211\u4eec\u8fdb\u5165\u5230mvs\">SFM\u7684\u91cd\u5efa\u6210\u679c\u662f\u7a00\u758f\u4e09\u7ef4\u70b9\u4e91\uff0c\u800cMVS\u53ef\u4ee5\u83b7\u5f97\u66f4\u597d\u7684\u7ed3\u679c<\/h2>\n\n\n\n<h4 id=\"\uff11\u5982\u4f55\u7406\u89e3\u5bc6\u96c6\u70b9\u4e91\u7684\u751f\u6210\u539f\u7406\">\uff08\uff11\uff09\u5982\u4f55\u7406\u89e3\u5bc6\u96c6\u70b9\u4e91\u7684\u751f\u6210\u539f\u7406<\/h4>\n\n\n\n<p id=\"mvs\u662f\u751f\u6210\u5bc6\u96c6\u70b9\u4e91\u7684\u65b9\u6cd5\u4e8b\u5b9e\u4e0a\u4e3a\u4ec0\u4e48\u6211\u4eec\u5728sfm\u4e2d\u4e0d\u80fd\u5f97\u5230\u5bc6\u96c6\u70b9\u4e91\u56e0\u4e3asfm\u4e2d\u6211\u4eec\u7528\u6765\u505a\u91cd\u5efa\u7684\u70b9\u662f\u7531\u7279\u5f81\u5339\u914d\u63d0\u4f9b\u7684\u8fd9\u4e9b\u5339\u914d\u70b9\u5929\u751f\u4e0d\u5bc6\u96c6\u800c\u4f7f\u7528\u8ba1\u7b97\u673a\u6765\u8fdb\u884c\u4e09\u7ef4\u70b9\u4e91\u91cd\u5efa\u6211\u4eec\u5fc5\u987b\u8ba4\u8bc6\u5230\u70b9\u4e91\u7684\u5bc6\u96c6\u7a0b\u5ea6\u662f\u7531\u4eba\u4e3a\u8fdb\u884c\u7f16\u7a0b\u8fdb\u884c\u83b7\u53d6\u7684sfm\u83b7\u5f97\u70b9\u7684\u65b9\u5f0f\u51b3\u5b9a\u4e86\u5b83\u4e0d\u53ef\u80fd\u76f4\u63a5\u751f\u6210\u5bc6\u96c6\u70b9\u4e91\">\u3000\u3000MVS\u662f\u751f\u6210\u5bc6\u96c6\u70b9\u4e91\u7684\u65b9\u6cd5\uff0c\u4e8b\u5b9e\u4e0a\uff0c\u4e3a\u4ec0\u4e48\u6211\u4eec\u5728SFM\u4e2d\u4e0d\u80fd\u5f97\u5230\u5bc6\u96c6\u70b9\u4e91\uff1f\u56e0\u4e3a\uff0cSFM\u4e2d\u6211\u4eec\u7528\u6765\u505a\u91cd\u5efa\u7684\u70b9\u662f\u7531\u7279\u5f81\u5339\u914d\u63d0\u4f9b\u7684\uff01\u8fd9\u4e9b\u5339\u914d\u70b9\u5929\u751f\u4e0d\u5bc6\u96c6\uff01\u800c\u4f7f\u7528\u8ba1\u7b97\u673a\u6765\u8fdb\u884c\u4e09\u7ef4\u70b9\u4e91\u91cd\u5efa\uff0c\u6211\u4eec\u5fc5\u987b\u8ba4\u8bc6\u5230\uff0c\u70b9\u4e91\u7684\u5bc6\u96c6\u7a0b\u5ea6\u662f\u7531\u4eba\u4e3a\u8fdb\u884c\u7f16\u7a0b\u8fdb\u884c\u83b7\u53d6\u7684\u3002SFM\u83b7\u5f97\u70b9\u7684\u65b9\u5f0f\u51b3\u5b9a\u4e86\u5b83\u4e0d\u53ef\u80fd\u76f4\u63a5\u751f\u6210\u5bc6\u96c6\u70b9\u4e91\u3002<\/p>\n\n\n\n<p id=\"\u800cmvs\u5219\u51e0\u4e4e\u5bf9\u7167\u7247\u4e2d\u7684\u6bcf\u4e2a\u50cf\u7d20\u70b9\u90fd\u8fdb\u884c\u5339\u914d\u51e0\u4e4e\u91cd\u5efa\u6bcf\u4e00\u4e2a\u50cf\u7d20\u70b9\u7684\u4e09\u7ef4\u5750\u6807\u8fd9\u6837\u5f97\u5230\u7684\u70b9\u7684\u5bc6\u96c6\u7a0b\u5ea6\u53ef\u4ee5\u8f83\u63a5\u8fd1\u56fe\u50cf\u4e3a\u6211\u4eec\u5c55\u793a\u51fa\u7684\u6e05\u6670\u5ea6\">\u3000\u3000\u800cMVS\u5219\u51e0\u4e4e\u5bf9\u7167\u7247\u4e2d\u7684\u6bcf\u4e2a\u50cf\u7d20\u70b9\u90fd\u8fdb\u884c\u5339\u914d\uff0c\u51e0\u4e4e\u91cd\u5efa\u6bcf\u4e00\u4e2a\u50cf\u7d20\u70b9\u7684\u4e09\u7ef4\u5750\u6807\uff0c\u8fd9\u6837\u5f97\u5230\u7684\u70b9\u7684\u5bc6\u96c6\u7a0b\u5ea6\u53ef\u4ee5\u8f83\u63a5\u8fd1\u56fe\u50cf\u4e3a\u6211\u4eec\u5c55\u793a\u51fa\u7684\u6e05\u6670\u5ea6\u3002<\/p>\n\n\n\n<p id=\"\u5176\u5b9e\u73b0\u7684\u7406\u8bba\u4f9d\u636e\u5728\u4e8e\u591a\u89c6\u56fe\u7167\u7247\u95f4\u5bf9\u4e8e\u62cd\u6444\u5230\u7684\u76f8\u540c\u7684\u4e09\u7ef4\u51e0\u4f55\u7ed3\u6784\u90e8\u5206\u5b58\u5728\u6781\u7ebf\u51e0\u4f55\u7ea6\u675f\">\u3000\u3000\u5176\u5b9e\u73b0\u7684\u7406\u8bba\u4f9d\u636e\u5728\u4e8e\uff0c\u591a\u89c6\u56fe\u7167\u7247\u95f4\uff0c\u5bf9\u4e8e\u62cd\u6444\u5230\u7684\u76f8\u540c\u7684\u4e09\u7ef4\u51e0\u4f55\u7ed3\u6784\u90e8\u5206\uff0c\u5b58\u5728\u6781\u7ebf\u51e0\u4f55\u7ea6\u675f\u3002<\/p>\n\n\n\n<p id=\"\u63cf\u8ff0\u8fd9\u79cd\u51e0\u4f55\u7ea6\u675f\">\u63cf\u8ff0\u8fd9\u79cd\u51e0\u4f55\u7ea6\u675f\uff1a<\/p>\n\n\n\n<p id=\"\u60f3\u8c61\u5bf9\u4e8e\u5728\u4e24\u5f20\u56fe\u7247\u4e2d\u7684\u540c\u4e00\u4e2a\u70b9\u73b0\u5728\u56de\u5230\u62cd\u6444\u7167\u7247\u7684\u90a3\u4e00\u523b\u5728\u4e09\u7ef4\u4e16\u754c\u4e2d\u5b58\u5728\u4e00\u6761\u5149\u7ebf\u4ece\u7167\u7247\u4e0a\u8fd9\u4e00\u70b9\u540c\u65f6\u7a7f\u8fc7\u62cd\u6444\u8fd9\u5f20\u7167\u7247\u7684\u76f8\u673a\u7684\u6210\u50cf\u4e2d\u5fc3\u70b9\u6700\u540e\u4f1a\u5230\u8fbe\u7a7a\u95f4\u4e2d\u4e00\u4e2a\u4e09\u7ef4\u70b9\u8fd9\u4e2a\u4e09\u7ef4\u70b9\u540c\u65f6\u4e5f\u4f1a\u5728\u53e6\u4e00\u5f20\u7167\u7247\u4e2d\u4ee5\u540c\u6837\u7684\u65b9\u5f0f\u6295\u5f71\">\u3000\u3000\u60f3\u8c61\uff0c\u5bf9\u4e8e\u5728\u4e24\u5f20\u56fe\u7247\u4e2d\u7684\u540c\u4e00\u4e2a\u70b9\u3002\u73b0\u5728\u56de\u5230\u62cd\u6444\u7167\u7247\u7684\u90a3\u4e00\u523b\uff0c\u5728\u4e09\u7ef4\u4e16\u754c\u4e2d\uff0c\u5b58\u5728\u4e00\u6761\u5149\u7ebf\u4ece\u7167\u7247\u4e0a\u8fd9\u4e00\u70b9\uff0c\u540c\u65f6\u7a7f\u8fc7\u62cd\u6444\u8fd9\u5f20\u7167\u7247\u7684\u76f8\u673a\u7684\u6210\u50cf\u4e2d\u5fc3\u70b9\uff0c\u6700\u540e\u4f1a\u5230\u8fbe\u7a7a\u95f4\u4e2d\u4e00\u4e2a\u4e09\u7ef4\u70b9\uff0c\u8fd9\u4e2a\u4e09\u7ef4\u70b9\u540c\u65f6\u4e5f\u4f1a\u5728\u53e6\u4e00\u5f20\u7167\u7247\u4e2d\u4ee5\u540c\u6837\u7684\u65b9\u5f0f\u6295\u5f71\u3002<\/p>\n\n\n\n<p 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id=\"x\u8868\u793a\u7a7a\u95f4\u4e2d\u7684\u4e00\u70b9x1x2\u4e3ax\u5728\u4e24\u5f20\u56fe\u7247\u4e2d\u7684\u540c\u4e00\u70b9\u7531\u4e8e\u5929\u7136\u7684\u7ea6\u675f\u5df2\u77e5x1\u60f3\u8981\u5728\u53e6\u4e00\u5f20\u56fe\u7247\u4e2d\u627e\u5230x2\u53ef\u4ee5\u5728\u76f4\u7ebfl2\u4e0a\u8fdb\u884c\u4e00\u7ef4\u5bfb\u627e-mvs\u4e3b\u8981\u505a\u7684\u5c31\u662f\u5982\u4f55\u6700\u4f73\u641c\u7d22\u5339\u914d\u4e0d\u540c\u76f8\u7247\u7684\u540c\u4e00\u4e2a\u70b9\">\u3000\u3000X\u8868\u793a\u7a7a\u95f4\u4e2d\u7684\u4e00\u70b9\uff0cx1\u3001x2\u4e3aX\u5728\u4e24\u5f20\u56fe\u7247\u4e2d\u7684\u540c\u4e00\u70b9\u3002\u7531\u4e8e\u5929\u7136\u7684\u7ea6\u675f\uff0c\u5df2\u77e5x1\uff0c\u60f3\u8981\u5728\u53e6\u4e00\u5f20\u56fe\u7247\u4e2d\u627e\u5230x2\uff0c\u53ef\u4ee5\u5728\u76f4\u7ebfL2\u4e0a\u8fdb\u884c\u4e00\u7ef4\u5bfb\u627e\u3002\u3000\u3000MVS\u4e3b\u8981\u505a\u7684\u5c31\u662f\u5982\u4f55\u6700\u4f73\u641c\u7d22\u5339\u914d\u4e0d\u540c\u76f8\u7247\u7684\u540c\u4e00\u4e2a\u70b9\u3002<\/p>\n\n\n\n<h4 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loading=\"lazy\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-396-1024x123.png\" alt=\"\" class=\"wp-image-14110\" width=\"424\" height=\"50\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-396-1024x123.png 1024w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-396-300x36.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-396-768x93.png 768w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/02\/image-396.png 1054w\" sizes=\"(max-width: 424px) 100vw, 424px\" \/><\/figure><\/div>\n\n\n\n<p id=\"\u03c0-p\u662f\u4f7f\u5f97\u70b9p\u6295\u5f71\u5230\u7167\u7247\u4e0a\u4e00\u70b9\u7684\u51fd\u6570-\u03c9x-\u51fd\u6570\u5b9a\u4e49\u4e86\u4e00\u4e2a\u70b9x\u5468\u56f4\u7684\u533a\u57dfix-\u51fd\u6570\u4ee3\u8868\u4e86\u7167\u7247\u533a\u57df\u7684\u5f3a\u5ea6\u7279\u5f81\u03c1f-g-\u662f\u7528\u6765\u6bd4\u8f83\u4e24\u4e2a\u5411\u91cf\u4e4b\u95f4\u7684\u76f8\u4f3c\u7a0b\u5ea6\u7684\">\u3000\u3000 \u03c0 (p)\u662f\u4f7f\u5f97\u70b9p\u6295\u5f71\u5230\u7167\u7247\u4e0a\u4e00\u70b9\u7684\u51fd\u6570\uff0c \u03a9(x) \u51fd\u6570\u5b9a\u4e49\u4e86\u4e00\u4e2a\u70b9x\u5468\u56f4\u7684\u533a\u57df\uff0cI(x) \u51fd\u6570\u4ee3\u8868\u4e86\u7167\u7247\u533a\u57df\u7684\u5f3a\u5ea6\u7279\u5f81\uff0c\u03c1(f, g) \u662f\u7528\u6765\u6bd4\u8f83\u4e24\u4e2a\u5411\u91cf\u4e4b\u95f4\u7684\u76f8\u4f3c\u7a0b\u5ea6\u7684<\/p>\n\n\n\n<p id=\"\u03c1\u51fd\u6570\u548c\u03c9\u51fd\u6570\u7684\u5177\u4f53\u9009\u62e9\u51b3\u5b9a\u8fd9\u4e2a\u4e00\u81f4\u6027\u5224\u522b\u7684\u51c6\u786e\u5ea6\">\u3000\u3000\u03c1\u51fd\u6570\u548c\u03a9\u51fd\u6570\u7684\u5177\u4f53\u9009\u62e9\u51b3\u5b9a\u8fd9\u4e2a\u201d\u4e00\u81f4\u6027\u5224\u522b\u201c\u7684\u51c6\u786e\u5ea6\u3002\u8fd9\u4e2a\u51fd\u6570\u7684\u5177\u4f53\u5b9e\u73b0\uff0c\u7531\u7f16\u7a0b\u5b9e\u73b0\u3002<\/p>\n\n\n\n<h4 id=\"title-1\">\u3000\u3000<\/h4>\n\n\n\n<h2 id=\"\u53c2\u8003\u6587\u732e\">\u53c2\u8003\u6587\u732e<\/h2>\n\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n\n<ol><li>Seitz, S. M., Curless, B., Diebel, J., Scharstein, D., &amp; Szeliski, R. (n.d.). A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms. In 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition &#8211; Volume 1 (CVPR\u201906) (Vol. 1, pp. 519\u2013528). IEEE. https:\/\/doi.org\/10.1109\/CVPR.2006.19<\/li><\/ol>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>1. \u524d\u8a00 Middlebury\u662f\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u4e09\u7ef4\u4e2d\u95f4\u9886\u57df\u8457\u540d\u7684\u9ad8\u6821\uff0c\u7279\u522b\u662f\u63d0\u4f9b\u4e86\u8457\u540d\u7684\u7acb\u4f53\u5339\u914dbenchma &hellip; <a href=\"http:\/\/139.9.1.231\/index.php\/2023\/02\/14\/mvson-of-multi-view-stereo-reconstruction-algorithms\/\" class=\"more-link\">\u7ee7\u7eed\u9605\u8bfb<span class=\"screen-reader-text\">MVS\u5b66\u4e60&#8211;\u300aA Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms\u300b<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[4,33],"tags":[],"_links":{"self":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/13973"}],"collection":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/comments?post=13973"}],"version-history":[{"count":21,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/13973\/revisions"}],"predecessor-version":[{"id":14112,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/13973\/revisions\/14112"}],"wp:attachment":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/media?parent=13973"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/categories?post=13973"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/tags?post=13973"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}