{"id":93111,"date":"2026-08-11T23:33:03","date_gmt":"2026-08-11T15:33:03","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/93111.html"},"modified":"2026-08-11T23:33:03","modified_gmt":"2026-08-11T15:33:03","slug":"vio%e5%af%bc%e8%88%aa-%e7%ac%ac-03-%e7%af%87-%c2%b7-%e7%89%b9%e5%be%81%e7%82%b9%e6%8f%90%e5%8f%96%e4%b8%8e%e5%85%89%e6%b5%81%e8%b7%9f%e8%b8%aa","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/93111.html","title":{"rendered":"VIO\u5bfc\u822a--\u7b2c 03 \u7bc7 \u00b7 \u7279\u5f81\u70b9\u63d0\u53d6\u4e0e\u5149\u6d41\u8ddf\u8e2a"},"content":{"rendered":"

\u00b7 \u672c\u7bc7\u4f60\u5c06\u5b66\u5230<\/h3>\n
  • \n

    Shi-Tomasi \u89d2\u70b9\u5224\u636e\u4e0e Harris \u7684\u5173\u7cfb，\u4ee5\u53ca goodFeaturesToTrack \u7684\u4f5c\u7528；<\/p>\n<\/li>\n

  • \n

    KLT \u91d1\u5b57\u5854\u5149\u6d41\u7684\u4eae\u5ea6\u6052\u5b9a\u5047\u8bbe\u4e0e Lucas-Kanade \u65b9\u7a0b；<\/p>\n<\/li>\n

  • \n

    \u6b63\u53cd\u5411\u5149\u6d41\u6821\u9a8c（FLOW_BACK）\u5982\u4f55\u5254\u9664\u5916\u70b9；<\/p>\n<\/li>\n

  • \n

    Mask \u63a9\u819c\u6cd5\u5982\u4f55\u8ba9\u7279\u5f81\u5728\u56fe\u50cf\u4e0a\u5747\u5300\u5206\u5e03\u3001\u4e14\u4f18\u5148\u4fdd\u7559\u957f\u5bff\u547d\u70b9；<\/p>\n<\/li>\n

  • \n

    trackImage \u5168\u6d41\u7a0b\u7cbe\u8bfb，\u4ee5\u53ca featureFrame 7 \u7ef4 [x,y,z,u,v,vx,vy] \u7684\u771f\u5b9e\u6765\u6e90\u3002<\/p>\n<\/li>\n

    \n

    \u4e00\u3001\u524d\u7aef\u89c6\u89c9\u7684\u4f5c\u7528\u4e0e\u6311\u6218<\/h3>\n

    VIO \u540e\u7aef\u4f18\u5316\u7684\u89c6\u89c9\u6b8b\u5dee，\u9700\u8981\u7684\u662f\u300c\u540c\u4e00\u4e2a\u7269\u7406\u70b9\u5728\u591a\u5e27\u95f4\u7684\u89c2\u6d4b\u5bf9\u5e94\u300d\u3002\u524d\u7aef（feature tracker）\u7684\u804c\u8d23\u5c31\u662f\u5efa\u7acb\u8fd9\u79cd\u5bf9\u5e94：\u8f93\u5165\u4e00\u4e32\u7070\u5ea6\u56fe，\u8f93\u51fa\u6bcf\u5e27\u4e2d\u82e5\u5e72\u7279\u5f81\u70b9\u7684\u5f52\u4e00\u5316\u5750\u6807\u4e0e\u552f\u4e00 ID，\u8ba9\u540e\u7aef\u77e5\u9053\u300c\u7b2c 5 \u5e27\u7684 37 \u53f7\u70b9\u300d\u548c\u300c\u7b2c 6 \u5e27\u7684 37 \u53f7\u70b9\u300d\u662f\u540c\u4e00\u4e2a\u4e16\u754c\u70b9\u3002<\/p>\n

    \u6311\u6218\u6709\u4e09：\u2460\u63d0\u53d6\u2013\u54ea\u4e9b\u50cf\u7d20\u9002\u5408\u957f\u671f\u8ddf\u8e2a（\u89d2\u70b9\u4f18\u4e8e\u5e73\u5766\u533a\u57df）；\u2461\u8ddf\u8e2a\u2013\u5df2\u77e5\u4e0a\u4e00\u5e27\u89d2\u70b9，\u5982\u4f55\u5728\u5f53\u524d\u5e27\u627e\u5230\u5bf9\u5e94（\u5149\u6d41）；\u2462\u7ba1\u7406\u2013\u7279\u5f81\u8981\u5206\u5e03\u5747\u5300\u3001\u4e22\u5931\u8981\u53ca\u65f6\u8865\u5145\u3001\u5916\u70b9\u8981\u5254\u9664\u3002VINS \u7684\u524d\u7aef\u7528 Shi-Tomasi \u89d2\u70b9 + KLT \u5149\u6d41 + Mask \u5747\u5300\u5316\u4e09\u4ef6\u5957\u89e3\u51b3\u3002<\/p>\n

    \u67b6\u6784\u5dee\u5f02\u63d0\u9192：\u539f\u7248 VINS-Mono \u7684\u524d\u7aef\u5165\u53e3\u53eb readImage（\u8fd4\u56de void，featureFrame \u5728 ROS \u5c42\u6784\u5efa）；VINS-Fusion \u91cd\u6784\u4e3a trackImage（feature_tracker.cpp:94），\u76f4\u63a5\u8fd4\u56de featureFrame\u3002\u672c\u7cfb\u5217\u4ee5 VINS-Fusion \u4ee3\u7801\u4e3a\u51c6，\u7cbe\u8bfb trackImage\u3002<\/p>\n

    \n

    \u4e8c\u3001Shi-Tomasi \u89d2\u70b9\u63d0\u53d6<\/h3>\n

    2.1 \u4e3a\u4ec0\u4e48\u662f\u89d2\u70b9？<\/h4>\n

    \u7279\u5f81\u8ddf\u8e2a\u4f9d\u8d56\u300c\u90bb\u57df\u7eb9\u7406\u300d\u3002\u5e73\u5766\u533a\u57df（\u5982\u767d\u5899）\u5404\u65b9\u5411\u68af\u5ea6\u90fd\u5c0f，\u65e0\u6cd5\u5b9a\u4f4d；\u8fb9\u7f18（\u5982\u684c\u6cbf）\u53ea\u6709\u4e00\u4e2a\u65b9\u5411\u6709\u68af\u5ea6，\u6cbf\u8fb9\u7f18\u65b9\u5411\u5b58\u5728\u5b54\u5f84\u95ee\u9898（\u5149\u6d41\u53ea\u80fd\u6c42\u51fa\u4e00\u4e2a\u5206\u91cf）；\u53ea\u6709\u89d2\u70b9（\u5982\u5899\u89d2）\u4e24\u4e2a\u65b9\u5411\u90fd\u6709\u5f3a\u68af\u5ea6，\u624d\u80fd\u88ab\u552f\u4e00\u3001\u7a33\u5b9a\u5730\u8ddf\u8e2a\u3002<\/p>\n

    2.2 \u7ed3\u6784\u5f20\u91cf\u4e0e\u89d2\u70b9\u54cd\u5e94<\/h4>\n

    \u5bf9\u6bcf\u4e2a\u50cf\u7d20\u53d6\u90bb\u57df\u7a97\u53e3，\u8ba1\u7b97\u56fe\u50cf\u68af\u5ea6 Ix,IyI_x, I_y<\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>，\u6784\u9020\u7ed3\u6784\u5f20\u91cf（\u4e8c\u9636\u77e9\u77e9\u9635）：<\/p>\n

    M=\u2211(x,y)\u2208W[Ix2IxIyIxIyIy2]
    \nM = \\\\sum_{(x,y)\\\\in W} \\\\begin{bmatrix} I_x^2 & I_x I_y \\\\\\\\ I_x I_y & I_y^2 \\\\end{bmatrix}
    \n<\/span><\/span>M<\/span><\/span>=<\/span><\/span><\/span><\/span><\/span>(<\/span>x<\/span>,<\/span>y<\/span>)<\/span>\u2208<\/span>W<\/span><\/span><\/span><\/span><\/span>\u2211<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>[<\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>]<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

    MM<\/span><\/span>M<\/span><\/span><\/span><\/span><\/span> \u7684\u4e24\u4e2a\u7279\u5f81\u503c \u03bb1,\u03bb2\\\\lambda_1, \\\\lambda_2<\/span><\/span>\u03bb<\/span><\/span>1<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>\u03bb<\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span> \u63cf\u8ff0\u4e86\u7a97\u53e3\u5728\u4e24\u4e2a\u4e3b\u65b9\u5411\u4e0a\u7684\u7070\u5ea6\u53d8\u5316\u5f3a\u5ea6：<\/p>\n\n\u533a\u57df\u03bb1,\u03bb2\\\\lambda_1, \\\\lambda_2<\/span><\/span>\u03bb<\/span><\/span>1<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>\u03bb<\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u542b\u4e49<\/tr>\n\n\n\n\n
    \u5e73\u5766<\/td>\n\u90fd\u5f88\u5c0f<\/td>\n\u65e0\u7eb9\u7406，\u4e0d\u53ef\u8ddf\u8e2a<\/td>\n<\/tr>\n
    \u8fb9\u7f18<\/td>\n\u4e00\u5927\u4e00\u5c0f<\/td>\n\u5355\u5411\u68af\u5ea6，\u5b54\u5f84\u95ee\u9898<\/td>\n<\/tr>\n
    \u89d2\u70b9<\/td>\n\u90fd\u5f88\u5927<\/td>\n\u53cc\u5411\u68af\u5ea6，\u53ef\u7a33\u5b9a\u8ddf\u8e2a<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Harris \u89d2\u70b9\u54cd\u5e94\u4e3a R=\u03bb1\u03bb2\u2212k(\u03bb1+\u03bb2)2R = \\\\lambda_1\\\\lambda_2 – k(\\\\lambda_1+\\\\lambda_2)^2<\/span><\/span>R<\/span><\/span>=<\/span><\/span><\/span><\/span>\u03bb<\/span><\/span>1<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u03bb<\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2212<\/span><\/span><\/span><\/span>k<\/span>(<\/span>\u03bb<\/span><\/span>1<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>+<\/span><\/span><\/span><\/span>\u03bb<\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>)<\/span><\/span>2<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>，\u4f9d\u8d56\u7ecf\u9a8c\u53c2\u6570 kk<\/span><\/span>k<\/span><\/span><\/span><\/span><\/span>\u3002Shi-Tomasi（\u5373 goodFeaturesToTrack \u7528\u7684 cv::GOODS_FROM_EIGEN）\u76f4\u63a5\u53d6\u66f4\u7a33\u5065\u7684\u5224\u636e：<\/p>\n

    R=min\u2061(\u03bb1,\u03bb2)>\u03c4
    \nR = \\\\min(\\\\lambda_1, \\\\lambda_2) > \\\\tau
    \n<\/span><\/span>R<\/span><\/span>=<\/span><\/span><\/span><\/span>min<\/span>(<\/span>\u03bb<\/span><\/span>1<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>\u03bb<\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>)<\/span><\/span>><\/span><\/span><\/span><\/span>\u03c4<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

    \u65e0\u9700\u8c03 kk<\/span><\/span>k<\/span><\/span><\/span><\/span><\/span>，\u4e14\u4e0e\u300c\u6700\u5c0f\u7279\u5f81\u503c\u8d8a\u5927\u8d8a\u7a33\u5b9a\u300d\u7684\u76f4\u89c9\u4e00\u81f4\u3002\u4ee3\u7801\u91cc：<\/p>\n

    \/\/ feature_tracker.cpp:184<\/span><\/p>\n

    cv::<\/span>goodFeaturesToTrack<\/span>(<\/span>cur_img,<\/span> n_pts,<\/span> MAX_CNT –<\/span> cur_pts.<\/span>size<\/span>(<\/span>)<\/span>,<\/span> 0.01<\/span>,<\/span> MIN_DIST,<\/span> mask)<\/span>;<\/span><\/p>\n

    \u53c2\u6570\u4f9d\u6b21：\u56fe\u50cf\u3001\u8f93\u51fa\u70b9\u3001\u6700\u5927\u6570\u91cf（MAX_CNT=150 \u51cf\u53bb\u5df2\u8ddf\u8e2a\u6570）\u3001\u8d28\u91cf\u7b49\u7ea7 0.01\u3001\u70b9\u95f4\u6700\u5c0f\u8ddd\u79bb MIN_DIST=30\u3001\u63a9\u819c mask\u3002\u63a9\u819c\u7684\u4f5c\u7528\u4e0b\u4e00\u8282\u8bb2\u3002<\/p>\n

    \n

    \u4e09\u3001KLT \u7a00\u758f\u5149\u6d41\u8ddf\u8e2a<\/h3>\n

    3.1 \u4eae\u5ea6\u6052\u5b9a\u5047\u8bbe<\/h4>\n

    Lucas-Kanade \u5149\u6d41\u7684\u6838\u5fc3\u5047\u8bbe：\u540c\u4e00\u4e2a\u70b9\u5728\u76f8\u90bb\u5e27\u95f4\u4eae\u5ea6\u4e0d\u53d8，\u4e14\u90bb\u57df\u5185\u6240\u6709\u70b9\u8fd0\u52a8\u4e00\u81f4：<\/p>\n

    I(x,y,t)=I(x+u,y+v,t+1)
    \nI(x, y, t) = I(x+u, y+v, t+1)
    \n<\/span><\/span>I<\/span>(<\/span>x<\/span>,<\/span><\/span>y<\/span>,<\/span><\/span>t<\/span>)<\/span><\/span>=<\/span><\/span><\/span><\/span>I<\/span>(<\/span>x<\/span><\/span>+<\/span><\/span><\/span><\/span>u<\/span>,<\/span><\/span>y<\/span><\/span>+<\/span><\/span><\/span><\/span>v<\/span>,<\/span><\/span>t<\/span><\/span>+<\/span><\/span><\/span><\/span>1<\/span>)<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

    \u5bf9\u53f3\u8fb9\u505a\u4e00\u9636\u6cf0\u52d2\u5c55\u5f00：<\/p>\n

    I(x+u,y+v,t+1)\u2248I(x,y,t)+Ixu+Iyv+It
    \nI(x+u,y+v,t+1) \\\\approx I(x,y,t) + I_x u + I_y v + I_t
    \n<\/span><\/span>I<\/span>(<\/span>x<\/span><\/span>+<\/span><\/span><\/span><\/span>u<\/span>,<\/span><\/span>y<\/span><\/span>+<\/span><\/span><\/span><\/span>v<\/span>,<\/span><\/span>t<\/span><\/span>+<\/span><\/span><\/span><\/span>1<\/span>)<\/span><\/span>\u2248<\/span><\/span><\/span><\/span>I<\/span>(<\/span>x<\/span>,<\/span><\/span>y<\/span>,<\/span><\/span>t<\/span>)<\/span><\/span>+<\/span><\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>u<\/span><\/span>+<\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>v<\/span><\/span>+<\/span><\/span><\/span><\/span>I<\/span><\/span>t<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

    \u4ee3\u5165\u6052\u7b49\u5f0f\u5f97 Lucas-Kanade \u65b9\u7a0b：<\/p>\n

    [IxIy][uv]=\u2212It
    \n\\\\begin{bmatrix} I_x & I_y \\\\end{bmatrix} \\\\begin{bmatrix} u \\\\\\\\ v \\\\end{bmatrix} = -I_t
    \n<\/span><\/span>[<\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>]<\/span><\/span><\/span><\/span>[<\/span><\/span><\/span>u<\/span><\/span><\/span><\/span>v<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>]<\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>\u2212<\/span>I<\/span><\/span>t<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

    \u90bb\u57df\u5185 nn<\/span><\/span>n<\/span><\/span><\/span><\/span><\/span> \u4e2a\u70b9\u53e0\u52a0（\u6bcf\u4e2a\u70b9\u4e00\u4e2a\u65b9\u7a0b），\u5f97\u5230\u8d85\u5b9a\u65b9\u7a0b Ad=bA\\\\mathbf{d} = \\\\mathbf{b}<\/span><\/span>A<\/span>d<\/span><\/span>=<\/span><\/span><\/span><\/span>b<\/span><\/span><\/span><\/span><\/span>，\u5176\u4e2d d=[u,v]T\\\\mathbf{d}=[u,v]^T<\/span><\/span>d<\/span><\/span>=<\/span><\/span><\/span><\/span>[<\/span>u<\/span>,<\/span><\/span>v<\/span>]<\/span><\/span>T<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>，AA<\/span><\/span>A<\/span><\/span><\/span><\/span><\/span> \u7684\u6bcf\u884c\u662f [Ix,Iy][I_x, I_y]<\/span><\/span>[<\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>]<\/span><\/span><\/span><\/span><\/span>，\u6700\u5c0f\u4e8c\u4e58\u89e3\u4e3a：<\/p>\n

    d=(ATA)\u22121ATb,ATA=\u2211[Ix2IxIyIxIyIy2]=M
    \n\\\\mathbf{d} = (A^T A)^{-1} A^T \\\\mathbf{b}, \\\\qquad A^T A = \\\\sum \\\\begin{bmatrix} I_x^2 & I_x I_y \\\\\\\\ I_x I_y & I_y^2 \\\\end{bmatrix} = M
    \n<\/span><\/span>d<\/span><\/span>=<\/span><\/span><\/span><\/span>(<\/span>A<\/span><\/span>T<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>A<\/span>)<\/span><\/span>\u2212<\/span>1<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>A<\/span><\/span>T<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>b<\/span>,<\/span><\/span><\/span>A<\/span><\/span>T<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>A<\/span><\/span>=<\/span><\/span><\/span><\/span>\u2211<\/span><\/span>[<\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>x<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>I<\/span><\/span>y<\/span><\/span><\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>]<\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>M<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

    \u6ce8\u610f ATAA^TA<\/span><\/span>A<\/span><\/span>T<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>A<\/span><\/span><\/span><\/span><\/span> \u6b63\u662f\u4e0a\u4e00\u8282\u7684\u7ed3\u6784\u5f20\u91cf MM<\/span><\/span>M<\/span><\/span><\/span><\/span><\/span>\u2013\u89d2\u70b9\u5904 MM<\/span><\/span>M<\/span><\/span><\/span><\/span><\/span> \u53ef\u9006，\u5149\u6d41\u53ef\u89e3；\u8fb9\u7f18\/\u5e73\u5766\u5904 MM<\/span><\/span>M<\/span><\/span><\/span><\/span><\/span> \u5947\u5f02，\u5149\u6d41\u4e0d\u53ef\u9760\u3002\u8fd9\u5c31\u662f\u300c\u8ddf\u8e2a\u8981\u9009\u89d2\u70b9\u300d\u7684\u6570\u5b66\u6839\u56e0\u3002<\/p>\n

    3.2 \u56fe\u50cf\u91d1\u5b57\u5854：\u89e3\u51b3\u5927\u4f4d\u79fb<\/h4>\n

    \u5355\u5c42\u5149\u6d41\u5047\u8bbe\u4f4d\u79fb\u5c0f（\u4e00\u9636\u6cf0\u52d2\u6709\u6548）\u3002\u76f8\u673a\u5feb\u901f\u8fd0\u52a8\u65f6\u7279\u5f81\u4f4d\u79fb\u51e0\u5341\u50cf\u7d20，\u5355\u5c42\u76f4\u63a5\u5931\u8d25\u3002\u91d1\u5b57\u5854\u5149\u6d41（calcOpticalFlowPyrLK）\u4ece\u6700\u7c97\u5c42\u5f00\u59cb\u4f30\u8ba1\u5927\u4f4d\u79fb，\u9010\u5c42\u7ec6\u5316\u5230\u539f\u56fe，\u628a\u300c\u5927\u4f4d\u79fb\u300d\u62c6\u6210\u591a\u6b21\u300c\u5c0f\u4f4d\u79fb\u300d\u3002<\/p>\n

    \u4ee3\u7801\u91cc\u7b2c\u4e09\u4e2a\u91d1\u5b57\u5854\u5c42\u6570\u53c2\u6570\u662f\u5173\u952e：<\/p>\n

    \/\/ feature_tracker.cpp:133 \u5e38\u89c4\u8ddf\u8e2a：3 \u5c42\u91d1\u5b57\u5854<\/span>
    \ncv::<\/span>calcOpticalFlowPyrLK<\/span>(<\/span>prev_img,<\/span> cur_img,<\/span> prev_pts,<\/span> cur_pts,<\/span> status,<\/span> err,<\/span> cv::<\/span>Size<\/span>(<\/span>21<\/span>,<\/span>21<\/span>)<\/span>,<\/span> 3<\/span>)<\/span>;<\/span><\/p>\n

    \u7a97\u53e3 21\u00d721，\u91d1\u5b57\u5854 3 \u5c42\u3002<\/p>\n

    3.3 \u6b63\u53cd\u5411\u6821\u9a8c：\u5254\u9664\u5916\u70b9<\/h4>\n

    \u5149\u6d41\u53ef\u80fd\u8ddf\u4e22\u6216\u8ddf\u9519（\u5982\u8fd0\u52a8\u6a21\u7cca\u3001\u906e\u6321）\u3002VINS \u7528\u524d\u5411+\u53cd\u5411\u53cc\u5411\u5149\u6d41\u6821\u9a8c（FLOW_BACK=1，yaml:41）：<\/p>\n

    \/\/ feature_tracker.cpp:135-151<\/span>
    \nif<\/span>(<\/span>FLOW_BACK)<\/span> {<\/span>
    \n vector<<\/span>cv::<\/span>Point2f><\/span> reverse_pts =<\/span> prev_pts;<\/span>
    \n cv::<\/span>calcOpticalFlowPyrLK<\/span>(<\/span>cur_img,<\/span> prev_img,<\/span> cur_pts,<\/span> reverse_pts,<\/span> .<\/span>.<\/span>.<\/span>)<\/span>;<\/span> \/\/ \u53cd\u5411<\/span>
    \n for<\/span>(<\/span>size_t i =<\/span> 0<\/span>;<\/span> i <<\/span> status.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> i++<\/span>)<\/span>
    \n if<\/span>(<\/span>status[<\/span>i]<\/span> &&<\/span> reverse_status[<\/span>i]<\/span> &&<\/span> distance<\/span>(<\/span>prev_pts[<\/span>i]<\/span>,<\/span> reverse_pts[<\/span>i]<\/span>)<\/span> <=<\/span> 0.5<\/span>)<\/span>
    \n status[<\/span>i]<\/span> =<\/span> 1<\/span>;<\/span> \/\/ \u6b63\u5411\u5230\u5f53\u524d\u5e27，\u518d\u53cd\u5411\u56de\u4e0a\u4e00\u5e27，\u82e5\u56de\u5230\u539f\u4f4d\u5219\u53ef\u4fe1<\/span>
    \n else<\/span>
    \n status[<\/span>i]<\/span> =<\/span> 0<\/span>;<\/span> \/\/ \u5426\u5219\u5224\u4e3a\u5916\u70b9\u5254\u9664<\/span>
    \n}<\/span><\/p>\n

    \u76f4\u89c9：\u4ece A \u8ddf\u5230 B，\u518d\u4ece B \u53cd\u5411\u8ddf\u56de，\u82e5\u843d\u5728 A \u9644\u8fd1（\u9608\u503c 0.5 \u50cf\u7d20）\u5219\u8be5\u5339\u914d\u81ea\u6d3d\u53ef\u4fe1\u3002\u8fd9\u662f\u4e00\u4e2a\u96f6\u6210\u672c\u7684\u5916\u70b9\u5254\u9664\u6280\u5de7，\u6bd4 RANSAC \u8f7b\u91cf\u3002<\/p>\n

    \u4ee3\u7801\u7ec6\u8282：feature_tracker.cpp:169 \u7684 rejectWithF()（\u57fa\u7840\u77e9\u9635 RANSAC）\u88ab\u6ce8\u91ca\u6389\u4e86，VINS-Fusion \u9ed8\u8ba4\u53ea\u9760\u53cc\u5411\u5149\u6d41\u5254\u70b9，\u4e0d\u518d\u505a F \u77e9\u9635 RANSAC\u3002rejectWithF \u51fd\u6570\u4f53（:308）\u4ecd\u4fdd\u7559，\u9700\u8981\u65f6\u53ef\u6253\u5f00\u3002\u8fd9\u662f VINS-Fusion \u76f8\u5bf9\u539f\u7248\u7684\u7b80\u5316\u3002<\/p>\n

    \n

    \u56db\u3001\u7279\u5f81\u5747\u5300\u5316：Mask \u63a9\u819c\u6cd5<\/h3>\n

    \u5982\u679c\u4e0d\u52a0\u7ea6\u675f，goodFeaturesToTrack \u4f1a\u5728\u7eb9\u7406\u5bc6\u96c6\u5904\u624e\u5806\u63d0\u53d6，\u5bfc\u81f4\u7279\u5f81\u5206\u5e03\u4e0d\u5747\u3001\u67d0\u4e9b\u533a\u57df\u65e0\u89c2\u6d4b\u3002VINS \u7528\u63a9\u819c\u89e3\u51b3，\u4e14\u505a\u5f97\u66f4\u806a\u660e\u2013\u4f18\u5148\u4fdd\u7559\u8ddf\u8e2a\u5bff\u547d\u957f\u7684\u70b9\u3002<\/p>\n

    \u3010\u51fd\u6570\u3011feature_tracker.cpp:55 void setMask()<\/h4>\n

    \u4f5c\u7528：\u6784\u5efa\u63a9\u819c，\u8ba9\u65b0\u68c0\u6d4b\u7684\u89d2\u70b9\u65e2\u4e0d\u4e0e\u5df2\u6709\u70b9\u8fc7\u8fd1，\u53c8\u4f18\u5148\u4fdd\u7559\u957f\u5bff\u547d\u70b9\u3002<\/p>\n

    \u6838\u5fc3\u4ee3\u7801：<\/p>\n

    \/\/ feature_tracker.cpp:57<\/span><\/p>\n

    mask =<\/span> cv::<\/span>Mat<\/span>(<\/span>row,<\/span> col,<\/span> CV_8UC1,<\/span> cv::<\/span>Scalar<\/span>(<\/span>255<\/span>)<\/span>)<\/span>;<\/span> \/\/ \u5168 255=\u5141\u8bb8\u68c0\u6d4b<\/span><\/p>\n

    \/\/ :60-68 \u6309 track_cnt \u964d\u5e8f\u6392\u5217 (\u8ddf\u8e2a\u6b21\u6570, (\u70b9\u5750\u6807, id))<\/span><\/p>\n

    vector<<\/span>pair<<\/span>int<\/span>,<\/span> pair<<\/span>cv::<\/span>Point2f,<\/span> int<\/span>>><\/span>><\/span> cnt_pts_id;<\/span><\/p>\n

    for<\/span> (<\/span>unsigned<\/span> int<\/span> i =<\/span> 0<\/span>;<\/span> i <<\/span> cur_pts.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> i++<\/span>)<\/span><\/p>\n

    cnt_pts_id.<\/span>push_back<\/span>(<\/span>make_pair<\/span>(<\/span>track_cnt[<\/span>i]<\/span>,<\/span> make_pair<\/span>(<\/span>cur_pts[<\/span>i]<\/span>,<\/span> ids[<\/span>i]<\/span>)<\/span>)<\/span>)<\/span>;<\/span><\/p>\n

    sort<\/span>(<\/span>cnt_pts_id.<\/span>begin<\/span>(<\/span>)<\/span>,<\/span> cnt_pts_id.<\/span>end<\/span>(<\/span>)<\/span>,<\/span><\/p>\n

    [<\/span>]<\/span>(<\/span>const<\/span> auto<\/span> &<\/span>a,<\/span> const<\/span> auto<\/span> &<\/span>b)<\/span>{<\/span> return<\/span> a.<\/span>first ><\/span> b.<\/span>first;<\/span> }<\/span>)<\/span>;<\/span><\/p>\n

    \/\/ :70-83 \u6e05\u7a7a\u540e\u6309\u5bff\u547d\u4ece\u957f\u5230\u77ed\u91cd\u65b0\u653e\u56de，\u6bcf\u4e2a\u70b9\u5468\u56f4 MIN_DIST \u8303\u56f4\u5185\u7f6e 0<\/span><\/p>\n

    cur_pts.<\/span>clear<\/span>(<\/span>)<\/span>;<\/span> ids.<\/span>clear<\/span>(<\/span>)<\/span>;<\/span> track_cnt.<\/span>clear<\/span>(<\/span>)<\/span>;<\/span><\/p>\n

    for<\/span> (<\/span>auto<\/span> &<\/span>it :<\/span> cnt_pts_id)<\/span> {<\/span><\/p>\n

    if<\/span> (<\/span>mask.<\/span>at<\/span><<\/span>uchar><\/span><\/span><\/span>(<\/span>it.<\/span>second.<\/span>first)<\/span> ==<\/span> 255<\/span>)<\/span> {<\/span> \/\/ \u8be5\u4f4d\u7f6e\u4ecd\u5141\u8bb8<\/span><\/p>\n

    cur_pts.<\/span>push_back<\/span>(<\/span>it.<\/span>second.<\/span>first)<\/span>;<\/span><\/p>\n

    ids.<\/span>push_back<\/span>(<\/span>it.<\/span>second.<\/span>second)<\/span>;<\/span><\/p>\n

    track_cnt.<\/span>push_back<\/span>(<\/span>it.<\/span>first)<\/span>;<\/span><\/p>\n

    cv::<\/span>circle<\/span>(<\/span>mask,<\/span> it.<\/span>second.<\/span>first,<\/span> MIN_DIST,<\/span> 0<\/span>,<\/span> –<\/span>1<\/span>)<\/span>;<\/span> \/\/ \u5468\u56f4\u753b\u9ed1，\u7981\u6b62\u518d\u6324\u5165<\/span><\/p>\n

    }<\/span><\/p>\n

    }<\/span><\/p>\n

    \u9010\u884c\u6ce8\u91ca：<\/p>\n

      \n
    • \n

      \u63a9\u819c\u521d\u59cb\u5168\u767d（255），\u8868\u793a\u300c\u5168\u56fe\u5141\u8bb8\u68c0\u6d4b\u65b0\u70b9\u300d；<\/p>\n<\/li>\n

    • \n

      \u6309 track_cnt \u964d\u5e8f\u6392\u5e8f\u662f\u5173\u952e\u8bbe\u8ba1：\u8ddf\u8e2a\u6b21\u6570\u591a = \u5bff\u547d\u957f = \u8d28\u91cf\u9ad8，\u4f18\u5148\u5360\u4f4d\u3002\u5bff\u547d\u77ed\u7684\u70b9\u82e5\u843d\u5728\u957f\u5bff\u547d\u70b9\u7684 MIN_DIST \u90bb\u57df\u5185，\u4f1a\u88ab\u6324\u6389；<\/p>\n<\/li>\n

    • \n

      cv::circle(mask, pt, MIN_DIST, 0, -1) \u5728\u5df2\u4fdd\u7559\u70b9\u5468\u56f4\u753b\u534a\u5f84 MIN_DIST=30 \u7684\u9ed1\u5706（0=\u7981\u6b62），\u4fdd\u8bc1\u540e\u7eed\u65b0\u70b9\u4e0e\u4e4b\u81f3\u5c11\u76f8\u8ddd 30 \u50cf\u7d20，\u5b9e\u73b0\u7a7a\u95f4\u5747\u5300\u3002<\/p>\n<\/li>\n<\/ul>\n

      \u8fd9\u6837 goodFeaturesToTrack \u4f20\u5165\u8be5 mask \u540e，\u53ea\u4f1a\u5728\u300c\u672a\u88ab\u5360\u7528\u300d\u7684\u533a\u57df\u8865\u65b0\u70b9，\u4e14\u8865\u7684\u70b9\u5929\u7136\u8fdc\u79bb\u8001\u70b9\u3002<\/p>\n

      \n

      \u4e94\u3001\u4ee3\u7801\u7cbe\u8bfb：trackImage \u5168\u6d41\u7a0b<\/h3>\n

      trackImage（feature_tracker.cpp:94）\u662f\u524d\u7aef\u552f\u4e00\u5bf9\u5916\u63a5\u53e3，\u8f93\u5165\u4e00\u5e27（\u53cc\u76ee\u53ef\u9009\u7b2c\u4e8c\u5e27）+ \u65f6\u95f4\u6233，\u8f93\u51fa featureFrame\u3002\u6574\u4f53\u6d41\u7a0b\u5982\u4e0b：<\/p>\n

      \u56fe 1 \u00b7 trackImage \u5168\u6d41\u7a0b<\/p>\n

      \u524d\u7aef\u552f\u4e00\u5bf9\u5916\u63a5\u53e3 trackImage \u7684\u7aef\u5230\u7aef\u6d41\u7a0b：\u4ece\u8bfb\u5165\u56fe\u50cf\u51fa\u53d1，\u7ecf\u5149\u6d41\u8ddf\u8e2a\u3001\u53cd\u5411\u6821\u9a8c\u5254\u5916\u70b9\u3001\u63a9\u819c\u5747\u5300\u5316\u3001\u8865\u5145\u65b0\u70b9，\u518d\u5230\u53bb\u7578\u53d8\u5f52\u4e00\u5316\u3001\u8ba1\u7b97\u901f\u5ea6\u5e76\u6784\u5efa 7 \u7ef4 featureFrame \u8f93\u51fa\u3002<\/p>\n

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.edgeLabel{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-ATUGTkoJK9CZT3Dk .edgeLabel p{background-color:rgba(232,232,232, 0.8);}#mermaid-svg-ATUGTkoJK9CZT3Dk .edgeLabel rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-ATUGTkoJK9CZT3Dk .labelBkg{background-color:rgba(232, 232, 232, 0.5);}#mermaid-svg-ATUGTkoJK9CZT3Dk .cluster rect{fill:#ffffde;stroke:#aaaa33;stroke-width:1px;}#mermaid-svg-ATUGTkoJK9CZT3Dk .cluster text{fill:#333;}#mermaid-svg-ATUGTkoJK9CZT3Dk .cluster span{color:#333;}#mermaid-svg-ATUGTkoJK9CZT3Dk div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;font-size:12px;background:hsl(80, 100%, 96.2745098039%);border:1px solid #aaaa33;border-radius:2px;pointer-events:none;z-index:100;}#mermaid-svg-ATUGTkoJK9CZT3Dk .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#333;}#mermaid-svg-ATUGTkoJK9CZT3Dk rect.text{fill:none;stroke-width:0;}#mermaid-svg-ATUGTkoJK9CZT3Dk .icon-shape,#mermaid-svg-ATUGTkoJK9CZT3Dk .image-shape{background-color:rgba(232,232,232, 0.8);text-align:center;}#mermaid-svg-ATUGTkoJK9CZT3Dk .icon-shape p,#mermaid-svg-ATUGTkoJK9CZT3Dk .image-shape p{background-color:rgba(232,232,232, 0.8);padding:2px;}#mermaid-svg-ATUGTkoJK9CZT3Dk .icon-shape .label rect,#mermaid-svg-ATUGTkoJK9CZT3Dk .image-shape .label rect{opacity:0.5;background-color:rgba(232,232,232, 0.8);fill:rgba(232,232,232, 0.8);}#mermaid-svg-ATUGTkoJK9CZT3Dk .label-icon{display:inline-block;height:1em;overflow:visible;vertical-align:-0.125em;}#mermaid-svg-ATUGTkoJK9CZT3Dk .node .label-icon path{fill:currentColor;stroke:revert;stroke-width:revert;}#mermaid-svg-ATUGTkoJK9CZT3Dk :root{–mermaid-font-family:\\”trebuchet ms\\”,verdana,arial,sans-serif;}#mermaid-svg-ATUGTkoJK9CZT3Dk .input>*{fill:#eef!important;stroke:#88f!important;}#mermaid-svg-ATUGTkoJK9CZT3Dk .input span{fill:#eef!important;stroke:#88f!important;}#mermaid-svg-ATUGTkoJK9CZT3Dk .branch>*{fill:#ffe!important;stroke:#fc6!important;}#mermaid-svg-ATUGTkoJK9CZT3Dk .branch span{fill:#ffe!important;stroke:#fc6!important;}#mermaid-svg-ATUGTkoJK9CZT3Dk .out>*{fill:#efe!important;stroke:#3c3!important;}#mermaid-svg-ATUGTkoJK9CZT3Dk .out span{fill:#efe!important;stroke:#3c3!important;}<\/span><\/p>\n

      \u662f<\/p>\n

      <\/span><\/span><\/p>\n

      \u5426<\/p>\n

      <\/span><\/span><\/p>\n

      \u662f<\/p>\n

      <\/span><\/span><\/p>\n

      \u5426<\/p>\n

      <\/span><\/span><\/span><\/span><\/span><\/p>\n

      \u662f<\/p>\n

      <\/span><\/span><\/p>\n

      \u5426<\/p>\n

      <\/span><\/span><\/span><\/span><\/p>\n

      \u8f93\u5165\u56fe\u50cf + \u65f6\u95f4\u6233<\/p>\n

      <\/span><\/p>\n

      IMU \u9884\u6d4b?hasPrediction<\/p>\n

      <\/span><\/p>\n

      IMU \u8f85\u52a9\u9884\u6d4b1 \u5c42\u91d1\u5b57\u5854\u521d\u503c<\/p>\n

      <\/span><\/p>\n

      \u5149\u6d41\u8ddf\u8e2acalcOpticalFlowPyrLK 3 \u5c42<\/p>\n

      <\/span><\/p>\n

      FLOW_BACK?<\/p>\n

      <\/span><\/p>\n

      \u6b63\u53cd\u5411\u6821\u9a8c\u53cd\u5411\u5149\u6d41\u9608\u503c 0.5<\/p>\n

      <\/span><\/p>\n

      \u5254\u9664\u5931\u8d25\u70b9\/\u5916\u70b9reduceVector \u540c\u6b65\u5254<\/p>\n

      <\/span><\/p>\n

      \u8fb9\u754c\u68c0\u67e5\u5254\u9664\u8d8a\u754c\u70b9<\/p>\n

      <\/span><\/p>\n

      \u5bff\u547d\u52a0\u4e00track_cnt++<\/p>\n

      <\/span><\/p>\n

      \u63a9\u819c\u5747\u5300\u5316 setMask\u6309\u5bff\u547d\u964d\u5e8f + MIN_DIST<\/p>\n

      <\/span><\/p>\n

      \u9700\u8865\u65b0\u70b9?<\/p>\n

      <\/span><\/p>\n

      \u8865\u5145\u65b0\u70b9goodFeaturesToTrack \u5206\u914d ID<\/p>\n

      <\/span><\/p>\n

      \u53bb\u7578\u53d8\u5f52\u4e00\u5316undistortedPts \/ liftProjective<\/p>\n

      <\/span><\/p>\n

      \u8ba1\u7b97\u5f52\u4e00\u5316\u5e73\u9762\u901f\u5ea6ptsVelocity<\/p>\n

      <\/span><\/p>\n

      \u6784\u5efa\u7279\u5f81\u5e27 featureFrame7 \u7ef4 x,y,z,u,v,vx,vy<\/p>\n

      <\/span><\/p>\n

      \u8f93\u51fa featureFrame\u4ea4\u7ed9\u540e\u7aef processMeasurements<\/p>\n

      <\/span><\/p>\n

      5.1 \u8ddf\u8e2a\u4e0e\u5254\u9664（:112-162）<\/h4>\n

      \/\/ feature_tracker.cpp:164-165 \u8ddf\u8e2a\u6210\u529f\u8005\u5bff\u547d +1<\/span><\/p>\n

      for<\/span> (<\/span>auto<\/span> &<\/span>n :<\/span> track_cnt)<\/span> n++<\/span>;<\/span><\/p>\n

      \u8ddf\u8e2a\u5931\u8d25\u7684\u70b9\u5df2\u5728\u524d\u9762 reduceVector \u4e2d\u4e0e prev_pts\/cur_pts\/ids\/track_cnt \u540c\u6b65\u5254\u9664（:156-159）\u2013\u56db\u4e2a vector \u7528\u540c\u4e00\u4e2a status，\u4fdd\u8bc1\u4e0b\u6807\u5bf9\u9f50\u3002\u8fd9\u662f VINS \u524d\u7aef\u7ba1\u7406\u591a\u7ec4\u5e76\u884c\u6570\u636e\u7684\u6838\u5fc3\u7ea6\u5b9a，\u540e\u7eed feature_manager \u4e5f\u6cbf\u7528\u3002<\/p>\n

      5.2 \u8865\u5145\u65b0\u70b9（:167-197）<\/h4>\n

      \/\/ feature_tracker.cpp:177-195<\/span><\/p>\n

      int<\/span> n_max_cnt =<\/span> MAX_CNT –<\/span> static_cast<\/span><<\/span>int<\/span>><\/span><\/span><\/span>(<\/span>cur_pts.<\/span>size<\/span>(<\/span>)<\/span>)<\/span>;<\/span><\/p>\n

      if<\/span> (<\/span>n_max_cnt ><\/span> 0<\/span>)<\/span><\/p>\n

      cv::<\/span>goodFeaturesToTrack<\/span>(<\/span>cur_img,<\/span> n_pts,<\/span> n_max_cnt,<\/span> 0.01<\/span>,<\/span> MIN_DIST,<\/span> mask)<\/span>;<\/span><\/p>\n

      for<\/span> (<\/span>auto<\/span> &<\/span>p :<\/span> n_pts)<\/span> {<\/span><\/p>\n

      cur_pts.<\/span>push_back<\/span>(<\/span>p)<\/span>;<\/span><\/p>\n

      ids.<\/span>push_back<\/span>(<\/span>n_id++<\/span>)<\/span>;<\/span> \/\/ \u65b0\u70b9\u5206\u914d\u5168\u5c40\u552f\u4e00\u9012\u589e id<\/span><\/p>\n

      track_cnt.<\/span>push_back<\/span>(<\/span>1<\/span>)<\/span>;<\/span> \/\/ \u521d\u59cb\u5bff\u547d=1<\/span><\/p>\n

      }<\/span><\/p>\n

      \u65b0\u70b9\u7528 n_id++ \u5206\u914d\u552f\u4e00 ID，\u8fd9\u662f\u7279\u5f81\u5728\u5168\u751f\u547d\u5468\u671f\u7684\u8eab\u4efd\u6807\u8bc6，\u540e\u7aef\u9760\u5b83\u505a\u6570\u636e\u5173\u8054\u3002n_id \u662f FeatureTracker \u7684\u6210\u5458（feature_tracker.h:82），\u5355\u8c03\u9012\u589e\u4e0d\u56de\u6536\u3002<\/p>\n

      5.3 IMU \u8f85\u52a9\u9884\u6d4b（\u8fdb\u9636，:117-131）<\/h4>\n

      \u82e5 hasPrediction（\u540e\u7aef\u4f18\u5316\u540e\u7531 setPrediction \u8bbe\u7f6e），\u524d\u7aef\u7528 IMU \u9884\u6d4b\u7684\u4f4d\u59ff\u628a\u7279\u5f81\u70b9\u6295\u5f71\u5230\u5f53\u524d\u5e27\u4f5c\u4e3a\u5149\u6d41\u521d\u503c，\u4ec5\u7528 1 \u5c42\u91d1\u5b57\u5854\u5373\u53ef\u5feb\u901f\u6536\u655b；\u82e5\u9884\u6d4b\u6210\u529f\u6570 <10（\u9884\u6d4b\u4e0d\u53ef\u9760），\u964d\u7ea7\u56de 3 \u5c42\u3002\u8fd9\u662f VIO\u300c\u89c6\u89c9-\u60ef\u6027\u8026\u5408\u300d\u5728\u524d\u7aef\u7684\u4f53\u73b0\u2013IMU \u4e0d\u662f\u53ea\u5728\u540e\u7aef\u7528，\u4e5f\u63d0\u524d\u5e2e\u89c6\u89c9\u7f29\u5c0f\u641c\u7d22\u8303\u56f4\u3002\u8be5\u673a\u5236\u6d89\u53ca\u540e\u7aef predictPtsInNextFrame，\u7b2c 15 \u7bc7\u518d\u5c55\u5f00\u3002<\/p>\n

      \n

      \u516d\u3001featureFrame \u7684 7 \u7ef4\u542b\u4e49<\/h3>\n

      \u6211\u4eec\u8bf4 featureFrame \u88c5\u7740\u300c7 \u7ef4\u89c2\u6d4b\u300d\u4f46\u6ca1\u5c55\u5f00，\u73b0\u5728\u8865\u4e0a\u3002\u6784\u5efa\u903b\u8f91\u5728 trackImage \u672b\u5c3e（:260-279）：<\/p>\n

      \/\/ feature_tracker.cpp:263-278<\/span><\/p>\n

      double<\/span> x,<\/span> y,<\/span> z;<\/span><\/p>\n

      x =<\/span> cur_un_pts[<\/span>i]<\/span>.<\/span>x;<\/span> \/\/ \u53bb\u7578\u53d8\u540e\u7684\u5f52\u4e00\u5316\u5750\u6807<\/span><\/p>\n

      y =<\/span> cur_un_pts[<\/span>i]<\/span>.<\/span>y;<\/span><\/p>\n

      z =<\/span> 1<\/span>;<\/span> \/\/ \u5f52\u4e00\u5316\u5e73\u9762 z=1<\/span><\/p>\n

      double<\/span> p_u,<\/span> p_v;<\/span><\/p>\n

      p_u =<\/span> cur_pts[<\/span>i]<\/span>.<\/span>x;<\/span> \/\/ \u539f\u59cb\u50cf\u7d20\u5750\u6807（\u542b\u7578\u53d8）<\/span><\/p>\n

      p_v =<\/span> cur_pts[<\/span>i]<\/span>.<\/span>y;<\/span><\/p>\n

      double<\/span> velocity_x,<\/span> velocity_y;<\/span><\/p>\n

      velocity_x =<\/span> pts_velocity[<\/span>i]<\/span>.<\/span>x;<\/span><\/p>\n

      velocity_y =<\/span> pts_velocity[<\/span>i]<\/span>.<\/span>y;<\/span><\/p>\n

      Eigen::<\/span>Matrix<<\/span>double<\/span>,<\/span> 7<\/span>,<\/span> 1<\/span>><\/span> xyz_uv_velocity;<\/span><\/p>\n

      xyz_uv_velocity <<<\/span> x,<\/span> y,<\/span> z,<\/span> p_u,<\/span> p_v,<\/span> velocity_x,<\/span> velocity_y;<\/span><\/p>\n

      featureFrame[<\/span>feature_id]<\/span>.<\/span>emplace_back<\/span>(<\/span>camera_id,<\/span> xyz_uv_velocity)<\/span>;<\/span><\/p>\n

      \u9010\u5b57\u6bb5\u542b\u4e49<\/h4>\n\n\u7ef4\u5ea6\u53d8\u91cf\u542b\u4e49\u6765\u6e90<\/tr>\n\n\n\n\n
      0-2<\/td>\nx, y, z<\/td>\n\u53bb\u7578\u53d8\u5f52\u4e00\u5316\u76f8\u673a\u5750\u6807，z=1<\/td>\nundistortedPts<\/td>\n<\/tr>\n
      3-4<\/td>\np_u, p_v<\/td>\n\u539f\u59cb\u50cf\u7d20\u5750\u6807（\u542b\u7578\u53d8）<\/td>\ncur_pts<\/td>\n<\/tr>\n
      5-6<\/td>\nvelocity_x, velocity_y<\/td>\n\u5f52\u4e00\u5316\u5e73\u9762\u901f\u5ea6<\/td>\nptsVelocity<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u53bb\u7578\u53d8：undistortedPts（:391-402）<\/h4>\n

      \/\/ feature_tracker.cpp:396-399<\/span><\/p>\n

      Eigen::<\/span>Vector2d a<\/span>(<\/span>pts[<\/span>i]<\/span>.<\/span>x,<\/span> pts[<\/span>i]<\/span>.<\/span>y)<\/span>;<\/span> \/\/ \u50cf\u7d20<\/span><\/p>\n

      Eigen::<\/span>Vector3d b;<\/span><\/p>\n

      cam-><\/span>liftProjective<\/span>(<\/span>a,<\/span> b)<\/span>;<\/span> \/\/ \u50cf\u7d20 -> \u5f52\u4e00\u5316\u5c04\u7ebf (\u53bb\u7578\u53d8)<\/span><\/p>\n

      un_pts.<\/span>push_back<\/span>(<\/span>cv::<\/span>Point2f<\/span>(<\/span>b.<\/span>x<\/span>(<\/span>)<\/span> \/<\/span> b.<\/span>z<\/span>(<\/span>)<\/span>,<\/span> b.<\/span>y<\/span>(<\/span>)<\/span> \/<\/span> b.<\/span>z<\/span>(<\/span>)<\/span>)<\/span>)<\/span>;<\/span> \/\/ \u6295\u5f71\u5230 z=1 \u5e73\u9762<\/span><\/p>\n

      liftProjective \u662f\u76f8\u673a\u6a21\u578b（\u9488\u5b54\/MEI）\u7684\u9006\u6295\u5f71：\u628a\u5e26\u7578\u53d8\u7684\u50cf\u7d20 (u,v)(u,v)<\/span><\/span>(<\/span>u<\/span>,<\/span><\/span>v<\/span>)<\/span><\/span><\/span><\/span><\/span> \u8fd8\u539f\u6210\u76f8\u673a\u5750\u6807\u7cfb\u7684\u5f52\u4e00\u5316\u5c04\u7ebf (X\/Z,Y\/Z,1)(X\/Z, Y\/Z, 1)<\/span><\/span>(<\/span>X<\/span>\/<\/span>Z<\/span>,<\/span><\/span>Y<\/span>\/<\/span>Z<\/span>,<\/span><\/span>1<\/span>)<\/span><\/span><\/span><\/span><\/span>\u3002\u540e\u7aef\u89c6\u89c9\u6b8b\u5dee\u7528\u7684\u662f\u8fd9\u7ec4\u5f52\u4e00\u5316\u5750\u6807（\u7b2c 12 \u7bc7），\u56e0\u4e3a\u5b83\u4e0e\u76f8\u673a\u5185\u53c2\u89e3\u8026，\u51e0\u4f55\u610f\u4e49\u5e72\u51c0\u3002EuRoC \u7528 MEI \u6a21\u578b（cam0_mei.yaml），liftProjective \u4f1a\u6309 MEI \u7684\u5168\u5411\u6a21\u578b\u53bb\u7578\u53d8\u3002<\/p>\n

      \u901f\u5ea6：ptsVelocity（:404-442）\u2013\u4e00\u4e2a\u6613\u8bef\u89e3\u70b9<\/h4>\n

      \/\/ feature_tracker.cpp:425-426<\/span><\/p>\n

      double<\/span> v_x =<\/span> (<\/span>pts[<\/span>i]<\/span>.<\/span>x –<\/span> it-><\/span>second.<\/span>x)<\/span> \/<\/span> dt;<\/span> \/\/ pts \u662f cur_un_pts（\u5f52\u4e00\u5316\u5750\u6807！）<\/span><\/p>\n

      double<\/span> v_y =<\/span> (<\/span>pts[<\/span>i]<\/span>.<\/span>y –<\/span> it-><\/span>second.<\/span>y)<\/span> \/<\/span> dt;<\/span><\/p>\n

      \u6ce8\u610f trackImage:200 \u4f20\u5165 ptsVelocity \u7684\u662f cur_un_pts（\u5f52\u4e00\u5316\u5750\u6807），\u4e0d\u662f\u50cf\u7d20\u5750\u6807\u3002\u6240\u4ee5\u7b2c 5\u30016 \u7ef4\u867d\u5e38\u88ab\u79f0\u4f5c\u300c\u50cf\u7d20\u901f\u5ea6\u300d，\u5b9e\u9645\u662f\u5f52\u4e00\u5316\u5e73\u9762\u4e0a\u7684\u901f\u5ea6 \u0394(x\/z,y\/z)\/\u0394t\\\\Delta(x\/z, y\/z)\/\\\\Delta t<\/span><\/span>\u0394<\/span>(<\/span>x<\/span>\/<\/span>z<\/span>,<\/span><\/span>y<\/span>\/<\/span>z<\/span>)<\/span>\/\u0394<\/span>t<\/span><\/span><\/span><\/span><\/span>\u3002\u5b83\u7528\u4e8e setPrediction\/fastPredictIMU \u7684\u7279\u5f81\u8fd0\u52a8\u9884\u6d4b\u3002\u540e\u7eed\u7bc7\u4ee5\u672c\u7bc7\u4e3a\u51c6\u3002<\/p>\n

      featureFrame \u7684\u5916\u5c42\u7ed3\u6784\u662f map<feature_id, vector<pair<camera_id, 7\u7ef4>>>：key \u662f\u7279\u5f81 ID，value \u662f\u5b83\u5728\u5404\u76f8\u673a\u7684\u89c2\u6d4b\u5217\u8868（\u5355\u76ee\u53ea\u6709 camera_id=0 \u4e00\u9879，\u53cc\u76ee\u8fd8\u6709 camera_id=1）\u3002\u8fd9\u5c31\u662f featureBuf \u91cc\u90a3\u4e32\u5413\u4eba\u6a21\u677f\u7684\u771f\u5b9e\u8bed\u4e49\u3002<\/p>\n

      \n

      \u5c0f\u7ed3<\/h3>\n

      \u672c\u7bc7\u62c6\u89e3\u4e86 VINS \u524d\u7aef\u4e09\u4ef6\u5957：<\/p>\n

        \n
      • \n

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