{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Cylinder fitting with RANSAC\n", "\n", "Last time we fitted a sphere with RANSAC. Now consider fitting a right circular cylinder to given points. Coordinates of the points are stored in [file](./dat/cyl.dat) `dat\\cyl.dat`.\n", "\n", "The most difficult problem here is to find the parameters of the cylinder(s) passing through a given set of 5 points. It can be shown that 4 points are not enough, but for 5 points there are even number (0, 2, 4, 6) of solutions. \n", "\n", "Our solution follows the [paper](http://www.heldermann-verlag.de/jgg/jgg10/j10h2zsom.pdf) by Paul Zsombor-Murray, Sawsan El Fashny (2006). Unfortunately two formulas in the paper have typos, hence we had the task to find and correct them. Fortunately by using the published numerical example 2.1 of the paper and by a computer algebra system we were successful to manage it. One such formula is the second equation under number (5), where the second term is $p_1^2a_2^2$ instead of $p_1a_2^2$. The second typo we found in the coefficient of $d_5$ in equation (10). The third term of the equation of the coefficient should be $-b_1c_2$ instead of $-b_1c_1$. The published method is based on the solution of a 6-degree algebraic equation, therefore it is relatively fast. This is important in RANSAC, since this calculation must be repeated many times.\n", "\n", "The solution proceeds along the following steps:\n", "* the given set of 5 points is transformed to a special frame\n", "* a sixth-degree polynomial is assembled for one component of the direction vector of the cylinder derived from a basic formula of the points of the cylinder\n", "* the second component is solved from a linear equation\n", "\n", "Basic formula of the points of the cylinder:\n", "\n", "$$(\\mathbf{x}\\times\\mathbf{a})^2 -2\\mathbf{a}^2(\\mathbf{x}\\cdot\\mathbf{a}) = 0 ,$$\n", "\n", "where $\\mathbf{x}$ denotes the position of an arbitrary point of the cylinder, $\\mathbf{a}$ denotes a vector along the axis of the cylinder. Vector $\\mathbf{f}$ points from the origin $O$ to a point on the axis of the cylinder and is perpendicular to vector $\\mathbf{a}$ ($\\mathbf{a}\\cdot\\mathbf{f}=0$).\n", "\n", "One such equation can be written for each given point, but since the origin $O$ of our coordinate frame can be chosen arbitrarily (e.g. it may be identical with the first point), we have only 4 such equations for the 6 unknowns (these are the components of $\\mathbf{a}$ and $\\mathbf{f}$). The 5th equation is the condition of perpendicularity.\n", "\n", "The length of vector $\\mathbf{a}$ is arbitrary (can be set to unit, for example, $\\mathbf{a}^2=1$; only its direction is relevant), hence there are only 5 unknowns and 5 equations are enough for the solution. Length of vector $\\mathbf{f}$ is the radius of the cylinder.\n", "\n", "First we implement in Python the function for calculating parameters of the right circular cylinder from 5 points. Arguments of the function are coordinates of the 5 points, output is a matrix, where the columns contain parameters for each of the solutions: radius $r$ and components of vectors $\\mathbf{a}$ and $\\mathbf{f}$." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "\n", "def cyl5fit(X1,X2,X3,X4,X5):\n", " ## cyl5fit(X1,...,X5) fit cylinders to points X1..X5\n", " ## Reference: Paul(2006): A Cylinder of revolution on Five Points\n", "\n", " ## shift to O:\n", " o=X1-X1\n", " pt=X2-X1\n", " qt=X3-X1\n", " rt=X4-X1\n", " st=X5-X1\n", "\n", " ## rotation such that OP=x and OQ is in the xy-plane\n", " ## transformed x\n", " x = pt/np.linalg.norm(pt)\n", " ## transformed y\n", " y = qt-(np.inner(qt,pt))/np.linalg.norm(pt)*x\n", " y = y/np.linalg.norm(y)\n", " ## transformed z\n", " z = np.array([(x[1]*y[2]-x[2]*y[1]),(x[2]*y[0]-x[0]*y[2]),(x[0]*y[1]-x[1]*y[0])])\n", " R = np.zeros((3,3))\n", " R[0,:] = x\n", " R[1,:] = y\n", " R[2,:] = z\n", " p = R.dot(pt)\n", " q = R.dot(qt)\n", " r = R.dot(rt)\n", " s = R.dot(st)\n", "\n", " p1=p[0];q1=q[0];q2=q[1];r1=r[0];r2=r[1];r3=r[2]\n", " s1=s[0];s2=s[1];s3=s[2]\n", "\n", " ## Eq. 11.\n", " b1=2*q2*r2*(q1-r1); \n", " b2=q2*r3*(p1-2*q1)\n", " b3=q2*r3*(p1-2*r1)\n", " b4=q2*(r1*(r1-p1)+r2*(r2-q2))+q1*r2*(p1-q1)\n", " b5=r3*(q2*(q2-2*r2)+q1*(q1-p1)); b6=q2**2*r3\n", " b7=q1*r3*(q1-p1)\n", " b8=q2*(r2*(r2-q2)+r3**2)\n", " b9=q2*(r1*(r1-p1)+r3**2)+q1*r2*(p1-q1)\n", " ##\n", " c1=q2*(r2*s3*(r2-q2)+r3*s2*(q2-s2)+r3*s3*(r3-s3))\n", " c2=q2*r3*s3*(r3-s3)+q1**2*(r3*s2-r2*s3)+p1*(q2*(r3*s1-r1*s3)+q1*(r2*s3-r3*s2)) \\\n", " +q2*(r1**2*s3-r3*s1**2)\n", " c3=q2*(p1*(s1*r3-s3*r1)-r3*(s1**2+s2**2)+s3*(r1**2+r2**2)) \\\n", " +(r2*s3-r3*s2)*(q1*(p1-q1)-q2**2)\n", " c4=2*q2*r3*s3*(s2-r2); c5=2*q2*r3*s3*(s1-r1)\n", " c6=2*q2*(r3*s2*(s1-q1)+r2*s3*(q1-r1))\n", "\n", " ## Eq. 10.\n", " d1=c1*b2-b6*c6; d2=c6*b7-b2*c2; d3=c1*b7-b6*c2; d4=c1*b1-b8*c6-b6*c5\n", " d5=c5*b7+c6*b9-b1*c2-b2*c4; d6=c5*b9+c6*b5-b3*c2-b1*c4-b2*c3\n", " d7=c1*b5-b8*c4-b6*c3; d8=c1*b9-b8*c2-b6*c4; d9=c1*b3-b8*c5\n", " d10=c5*b5+c6*b4-b3*c4-b1*c3; d11=c1*b4-b8*c3; d12=c5*b4-b3*c3\n", "\n", " ## Eq. 9.\n", " D1=d1*d2-d3**2; D2=d4*d2+d1*d5-2*d8*d3; D3=d9*d2+d4*d5+d1*d6-2*d7*d3-d8**2\n", " D4=d9*d5+d4*d6+d1*d10-2*d11*d3-2*d7*d8\n", " D5=d9*d6+d4*d10+d1*d12-2*d11*d8-d7**2\n", " D6=d9*d10+d4*d12-2*d11*d7; D7=d9*d12-d11**2\n", "\n", " ## Eq. 8.\n", " pol6=np.array([D1,D2,D3,D4,D5,D6,D7])\n", " r6=np.roots(pol6)\n", "\n", " ## real roots\n", " a2 = r6.real[np.abs(r6.imag)<1e-12]\n", "\n", " ## number of roots\n", " n = a2.shape[0]\n", " ## no solution: \n", " if n == 0:\n", " return 0\n", " \n", " ## calculate a1\n", " e1=c1*(b2*a2**2+b1*a2+b3)-(b6*a2+b8)*(c6*a2+c5)\n", " e2=c1*(b7*a2**3+b9*a2**2+b5*a2+b4)-(b6*a2+b8)*(c2*a2**2+c4*a2+c3)\n", " a1=-e2/e1\n", " a = np.vstack((a1,a2,np.ones((1,n)))) \n", " norma = np.sqrt(a[0,:]**2+a[1,:]**2+a[2,:]**2)\n", " \n", " ## calculate vector f from equations (5)\n", " asq = a1**2+a2**2+1\n", " ##\"f1, f2, f3\"\n", " f1=p1*(1+a2**2)/asq/2\n", " f2=(q1**2+q2**2+(q1*a2-q2*a1)**2)/2/asq\n", " f2=(f2-q1*f1)/q2\n", " f3=-(a1*f1+a2*f2)\n", " f = np.vstack((f1,f2,f3))\n", " ## length of vector f is the radius of the cylinder: r=norm(f)\n", " radius = np.sqrt(f[0,:]**2+f[1,:]**2+f[2,:]**2)\n", "\n", " ## inverse transformation - rotation\n", " a = (R.T).dot(a)\n", " f = (R.T).dot(f)\n", " ## shift vector f\n", " f = (f.T + X1).T\n", "\n", " return np.vstack((radius,a/norma,f))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is compulsory to test such a complicated function. Let us check it with data of example 2.1 in the paper Paul Zsombor-Murray, Sawsan El Fashny (2006):" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Results of test 1. of cylinder fitting:\n", "[[ 1.55079 1.52273]\n", " [ 0.01138 -0.32165]\n", " [ 0.36146 -0.01544]\n", " [ 0.93232 0.94673]\n", " [ 1.49981 1.34481]\n", " [ 0.36118 0.54156]\n", " [-0.15834 0.46572]]\n" ] } ], "source": [ "## Paul Zsombor-Murray (2009): A Cylinder of Revolution on Five Points example 2.1\n", "O=np.array([0,0,0]); P=np.array([3,0,0]); Q=np.array([2,2,0]); R=np.array([0,2,4]); S=np.array([2,0,3]); \n", "cyl=cyl5fit(O,P,Q,R,S)\n", "print(\"Results of test 1. of cylinder fitting:\")\n", "np.set_printoptions(precision=5)\n", "np.set_printoptions(suppress=True)\n", "print(cyl)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We found only vectors $\\mathbf{a}$ in the paper and these are not normalized to 1, but the components $a_3$ are set to 1. Therefore recalculate our solution vectors $\\mathbf{a}$ such that their 3rd component is 1. The following values are reported in the paper (for us only the 2 real solutions are of interest):\n", "\n", "\n", "Transform and print vectors like this:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Our solution: \n", "[[ 1. 0.3876994216 0.0122101721]\n", " [ 1. -0.0163069808 -0.339744343 ]]\n" ] } ], "source": [ "a = cyl[1:4,:]; an = a/a[2,:]\n", "np.set_printoptions(precision=10)\n", "print(\"Our solution: \")\n", "print(np.fliplr(an.T))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that our results are identical with those of the example in the paper." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we have already mentioned the [scikit-image](http://scikit-image.org/) library can be imported with the statement\n", "```python\n", "import sm\n", "```\n", "or we can import the necessary functions from the `sm.py` module:\n", "```python\n", "import sm\n", "```\n", "and then we can use the function `ransac()`:\n", "```python\n", "sm.ransac(data, model_class, min_samples, residual_threshold) \n", "```\n", "which has got four required parameters. \n", "1. data matrix `data(N, D)` where `N` denotes the number and `D` is dimension of data,\n", "2. Python implementation of the class with required member functions `success = estimate(*data)` and `residuals(*data)`,\n", "3. integer `min_samples`, which is the same as $n$.\n", "4. `residual_threshold`, maximum distance (residual) of conform data.\n", "\n", "First we create the class which implements our model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### CylModel Python class\n", "\n", "Class `CylModel`, which is used for RANSAC, consists of a simple constructor and two member functions (`estimate` és `residuals`). Member variable `params` is a vector of 7 components that contain parameters of the cylinder." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "class CylModel:\n", " \"\"\"model for right circular cylinder fitting \n", " \"\"\"\n", "\n", " def __init__(self):\n", " self.params = np.zeros(7)\n", "\n", " def estimate(self, X):\n", " \"\"\"\n", " cyl5fit(X) fits cylinders to 5 points stored as rows of matrix X\n", " Reference: Paul(2006): A Cylinder of revolution on Five Points\n", " Results: parameters stored in a vector of 7 components \n", " params: [r,ax,ay,az,fx,fy,fz], where:\n", " r: radius of the cylinder\n", " ax,ay,az: unit vector of the cylinder's axis\n", " fx,fy,fz: coordinates of a point on the axis\n", " Remark: When there is no good solution, the function returns False\n", " \"\"\"\n", "\n", " ## shift to O:\n", " o=X[0,:]-X[0,:]\n", " pt=X[1,:]-X[0,:]\n", " qt=X[2,:]-X[0,:]\n", " rt=X[3,:]-X[0,:]\n", " st=X[4,:]-X[0,:]\n", "\n", " ## rotation such that OP=x and OQ is in the xy-plane\n", " x = pt/np.linalg.norm(pt)\n", " y = qt-(np.inner(qt,pt))/np.linalg.norm(pt)*x\n", " y = y/np.linalg.norm(y)\n", " z = np.array([(x[1]*y[2]-x[2]*y[1]),(x[2]*y[0]-x[0]*y[2]),(x[0]*y[1]-x[1]*y[0])])\n", " R = np.zeros((3,3))\n", " R[0,:] = x; R[1,:] = y; R[2,:] = z\n", " p = R.dot(pt)\n", " q = R.dot(qt)\n", " r = R.dot(rt)\n", " s = R.dot(st)\n", "\n", " p1=p[0];q1=q[0];q2=q[1];r1=r[0];r2=r[1];r3=r[2]\n", " s1=s[0];s2=s[1];s3=s[2]\n", "\n", " ## Eq. 11.\n", " b1=2*q2*r2*(q1-r1); \n", " b2=q2*r3*(p1-2*q1)\n", " b3=q2*r3*(p1-2*r1)\n", " b4=q2*(r1*(r1-p1)+r2*(r2-q2))+q1*r2*(p1-q1)\n", " b5=r3*(q2*(q2-2*r2)+q1*(q1-p1)); b6=q2**2*r3\n", " b7=q1*r3*(q1-p1)\n", " b8=q2*(r2*(r2-q2)+r3**2)\n", " b9=q2*(r1*(r1-p1)+r3**2)+q1*r2*(p1-q1)\n", " ##\n", " c1=q2*(r2*s3*(r2-q2)+r3*s2*(q2-s2)+r3*s3*(r3-s3))\n", " c2=q2*r3*s3*(r3-s3)+q1**2*(r3*s2-r2*s3)+p1*(q2*(r3*s1-r1*s3)+q1*(r2*s3-r3*s2)) \\\n", " +q2*(r1**2*s3-r3*s1**2)\n", " c3=q2*(p1*(s1*r3-s3*r1)-r3*(s1**2+s2**2)+s3*(r1**2+r2**2)) \\\n", " +(r2*s3-r3*s2)*(q1*(p1-q1)-q2**2)\n", " c4=2*q2*r3*s3*(s2-r2); c5=2*q2*r3*s3*(s1-r1)\n", " c6=2*q2*(r3*s2*(s1-q1)+r2*s3*(q1-r1))\n", "\n", " ## Eq. 10.\n", " d1=c1*b2-b6*c6; d2=c6*b7-b2*c2; d3=c1*b7-b6*c2; d4=c1*b1-b8*c6-b6*c5\n", " d5=c5*b7+c6*b9-b1*c2-b2*c4; d6=c5*b9+c6*b5-b3*c2-b1*c4-b2*c3\n", " d7=c1*b5-b8*c4-b6*c3; d8=c1*b9-b8*c2-b6*c4; d9=c1*b3-b8*c5\n", " d10=c5*b5+c6*b4-b3*c4-b1*c3; d11=c1*b4-b8*c3; d12=c5*b4-b3*c3\n", "\n", " ## Eq. 9.\n", " D1=d1*d2-d3**2; D2=d4*d2+d1*d5-2*d8*d3; D3=d9*d2+d4*d5+d1*d6-2*d7*d3-d8**2\n", " D4=d9*d5+d4*d6+d1*d10-2*d11*d3-2*d7*d8\n", " D5=d9*d6+d4*d10+d1*d12-2*d11*d8-d7**2\n", " D6=d9*d10+d4*d12-2*d11*d7; D7=d9*d12-d11**2\n", "\n", " ## Eq. 8.\n", " pol6=np.array([D1,D2,D3,D4,D5,D6,D7])\n", " r6=np.roots(pol6)\n", "\n", " ## real roots\n", " a2 = r6.real[np.abs(r6.imag)<1e-12]\n", "\n", " ## number of roots\n", " n = a2.shape[0]\n", " ## no solution: \n", " if n == 0:\n", " return False\n", "\n", " ## calculate a1\n", " e1=c1*(b2*a2**2+b1*a2+b3)-(b6*a2+b8)*(c6*a2+c5)\n", " e2=c1*(b7*a2**3+b9*a2**2+b5*a2+b4)-(b6*a2+b8)*(c2*a2**2+c4*a2+c3)\n", " a1=-e2/e1\n", " a = np.vstack((a1,a2,np.ones((1,n)))) \n", " norma = np.sqrt(a[0,:]**2+a[1,:]**2+a[2,:]**2)\n", " \n", " ## calculate vector f from equations (5)\n", " asq = a1**2+a2**2+1\n", " ##\"f1, f2, f3\"\n", " f1=p1*(1+a2**2)/asq/2\n", " f2=(q1**2+q2**2+(q1*a2-q2*a1)**2)/2/asq\n", " f2=(f2-q1*f1)/q2\n", " f3=-(a1*f1+a2*f2)\n", " f = np.vstack((f1,f2,f3))\n", " ## length of vector f is the radius of the cylinder: r=norm(f)\n", " radius = np.sqrt(f[0,:]**2+f[1,:]**2+f[2,:]**2)\n", "\n", " ## inverse transformation - rotation\n", " a = (R.T).dot(a)\n", " f = (R.T).dot(f)\n", " ## shift vector f\n", " f = (f.T + X[0,:]).T\n", " ## all solutions\n", " p = np.vstack((radius,a/norma,f))\n", " ## use only the first solution\n", " self.params = p[:,0]\n", "\n", " return True\n", " \n", " def residuals(self, X, pos=1):\n", " \"\"\"\n", " residuals(X) calculate distance of points X from cylinder cyl\n", " params: vector of 7 components: [r, a, f]\n", " r: radius of the cylinder\n", " a: unit vector of the cylinder's axis\n", " f: position of one point along the axis\n", " X: (n,3) matrix, coordinates of n points\n", " pos: if pos=0, calculate signed distances (else unsigned)\n", " \"\"\"\n", " r = self.params[0]\n", " a = self.params[1:4]\n", " f = self.params[4:]\n", " xf = X-f\n", " # norm squared\n", " nxf = xf[:,0]**2+xf[:,1]**2+xf[:,2]**2\n", " if pos==1:\n", " dist = np.abs(np.sqrt(nxf - ((X-f).dot(a))**2) - r)\n", " else:\n", " dist = np.sqrt(nxf - ((X-f).dot(a))**2) - r\n", " return dist" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Test data\n", "\n", "We use test [data](./dat/cyl.dat). Read and plot point cloud." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import sm\n", "from mpl_toolkits.mplot3d import Axes3D\n", "import matplotlib.pyplot as plt\n", "\n", "## test data (1000 points)\n", "X1=np.loadtxt(\"./dat/cyl.dat\")\n", "\n", "## make plot\n", "fig = plt.figure(figsize=(8,8))\n", "ax = fig.add_subplot(111, projection='3d')\n", "ax.scatter(X1[:,0], X1[:,1], X1[:,2], s=2)\n", "ax.set_xlabel('X')\n", "ax.set_ylabel('Y')\n", "ax.set_zlabel('Z')\n", "ax.view_init(elev=40, azim=210)\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "After reading and plotting data we estimate cylinder parameters with RANSAC. In this case `min_samples = 5`. Value of `residual_threshold` is set to `10.0`." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 100.6527872169 0.5315482736 0.6334361259 -0.5623300696\n", " 114.4770058482 186.0931126367 -159.2797358391]\n", "number of points : 1000\n", "number of outliers: 138\n" ] } ], "source": [ "ransac_model, inliers = sm.ransac(X1, CylModel, 5, 10.0)\n", "\n", "np.set_printoptions(suppress=True)\n", "print(ransac_model.params)\n", "print(\"number of points : \", X1.shape[0])\n", "print(\"number of outliers: \", X1.shape[0]-np.sum(inliers))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We again find that by repeating the above calculation we get slightly different parameters and number of outliers due to the random nature of RANSAC.\n", "\n", "Plot consensus set and outliers with another color:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(8,8))\n", "ax = fig.add_subplot(111, projection='3d')\n", "ax.scatter(X1[inliers,0], X1[inliers,1], X1[inliers,2], s=2)\n", "outliers = np.invert(inliers)\n", "ax.scatter(X1[outliers,0], X1[outliers,1], X1[outliers,2], s=2)\n", "ax.set_xlabel('X')\n", "ax.set_ylabel('Y')\n", "ax.set_zlabel('Z')\n", "ax.view_init(elev=40, azim=210)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Fit residuals\n", "Plot histogram of fit residuals" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mean : -0.61 %\n", "std : 13.25 %\n", "max : 39.27 %\n" ] }, { "data": { "image/png": "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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def cyldist(cyl,X,pos=1):\n", " \"\"\"\n", " cyldist(cyl,X) calculates unsigned distances of points in X from cylinder cyl\n", " cyl: 7-component vector:\n", " r: radius\n", " a: unit vector of cylinder axis\n", " f: position of a point on the cylinder axis\n", " X: (n,3) matrix of coordinates of n points\n", " pos: if pos=0, calculate signed, otherwise unsigned distances\n", " \"\"\"\n", "\n", " r = cyl[0]\n", " a = cyl[1:4]\n", " f = cyl[4:]\n", " xf = X-f\n", " ## norm squared\n", " nxf = xf[:,0]**2+xf[:,1]**2+xf[:,2]**2\n", " if pos==1:\n", " dist = np.abs(np.sqrt(nxf - ((X-f).dot(a))**2) - r)\n", " else:\n", " dist = np.sqrt(nxf - ((X-f).dot(a))**2) - r\n", " return dist\n", "\n", "# calculate signed distances\n", "v = cyldist(ransac_model.params,X1,0)\n", "\n", "# residuals relative to the radius (mean, std)\n", "print( \"mean : %.2f %%\" % (100*np.mean(v)/ransac_model.params[0]))\n", "print( \"std : %.2f %%\" % (100*np.std(v)/ransac_model.params[0]))\n", "\n", "# max. percent residual\n", "print( \"max : %.2f %%\" % (100*np.max(np.abs((v)))/ransac_model.params[0]))\n", "\n", "# histogram of relative residuals\n", "fig = plt.figure()\n", "n, bins, patches = plt.hist(v, 30, density=True, facecolor='green', alpha=0.75)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Least squares parameter estimation based on RANSAC output\n", "\n", "Optimum RANSAC estimation of cylinder parameters was based on elements of the maximal consensus set. As an additional step, this estimation can be refined using elements of this maximal consensus set, for example by least squares. The [procedure](https://www.researchgate.net/profile/Da-chuan_Cheng/publication/221114886_A_Novel_Parameter_Decomposition_Approach_to_Faithful_Fitting_of_Quadric_Surfaces/links/0912f5089d11534155000000.pdf) by Jiang és Cheng can be used for this estimation.\n", "\n", "This procedure essentially determines first the direction of the best fitting cylinder's axis, since squared sum of residuals from the superficies of the cylinder remains the same after projecting all points onto a plane perpendicular to the cylinder's axis in a direction that is parallel with the axis. This squared residual sum depends on the axis' direction and is implemented in function `acfit(X,a)`, where array `X` contains an arbitrary number of points in its rows. Direction of the projection is given by two angles: spherical polar distance $\\vartheta$ and longitude $\\lambda$, which are elements of vector `a`.\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "from scipy.optimize import minimize\n", "\n", "def acfit(X, a, sonly=False):\n", " ## acfit(X, a, sonly=False) fits a circle to points given as rows of X \n", " ## projected along the direction given by 'a' \n", " ## Input: X: nx3 matrix, [x,y,z] coordinates of n points stored as rows\n", " ## a=[theta, lambda]: polar coordinates of projection direction\n", " ## sonly: if True, return s only\n", " ## Output: s, r, c where:\n", " ## r: radius of circle\n", " ## c=[x0, y0, z0]: center of circle in the projection plane\n", " ## s: sum of squared fit residuals\n", "\n", " # projection to a plane passing through the origin\n", " n=X.shape[0]\n", " t=a[0]\n", " l=a[1]\n", " # unit vector of projection direction\n", " au = np.array([np.sin(t)*np.cos(l), np.sin(t)*np.sin(l), np.cos(t)])\n", " # unit vectors in the projection plane\n", " ath = np.array([np.cos(t)*np.cos(l), np.cos(t)*np.sin(l), -np.sin(t)])\n", " ala = np.array([-np.sin(l), np.cos(l), 0])\n", " # coordinates of projected points\n", " x = np.sum(X*np.tile(ala,(n,1)),axis=1)\n", " y = np.sum(X*np.tile(ath,(n,1)),axis=1)\n", " Xs = np.vstack((x,y)).T\n", "\n", " # matrix M\n", " M=np.hstack((-2*Xs,np.ones((n,1))))\n", " # vector h\n", " h=-np.sum(Xs**2,axis=1)\n", " p,re,ra,ev=np.linalg.lstsq(M,h,rcond=None)\n", " # radius of sphere\n", " r=np.sqrt(p[0]**2+p[1]**2-p[2])\n", " # coordinates of centre in projection plane\n", " cs=p[0:2]\n", " # inverse transformed centre in xyz-frame\n", " TR=np.vstack((ala, ath, au)).T\n", " c=TR.dot(np.hstack((cs, 0)))\n", " # squared sum of residuals\n", " s=np.sum((M.dot(p)-h)**2)\n", " if sonly:\n", " return s\n", " else:\n", " return s, r, c\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To calculate the best fitting cylinder we minimize a one-line function `sqsum` defined with the help of the above defined `acfit` function by using the `minimize` function in module `scipy.optimize`. After axis direction was determined points are projected and other parameters of the best fitting cylinder are calculated. All these steps are implemented in function `cylinder(X)`:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def cylinder(X):\n", " ## cylinder(X) fits a right circular cylinder into the points stored as rows of X\n", " ## Input: X: nx3 matrix, its rows are [x,y,z] coordinates of points\n", " ## Output: [c, r, a] where:\n", " ## r: radius of cylinder\n", " ## c=[x0, y0, z0]: position of one point along the cylinder axis\n", " ## a=[theta, lambda]: direction of axis (spherical polar coordinates)\n", "\n", " # subtract mean from coordinates\n", " Xm=np.mean(X,axis=0)\n", " Xs=X-Xm\n", " # number of points\n", " n=X.shape[0]\n", "\n", " # search of minimum\n", " #\n", " # one-line cost function to be minimized\n", " sqsum = lambda x: acfit(X,x,True)\n", " x0 = np.array([0.1, 0.1])\n", " res = minimize(sqsum, x0, method='BFGS')\n", " x = res.x\n", " # parameters\n", " a = x\n", " au = np.array([np.sin(x[0])*np.cos(x[1]), np.sin(x[0])*np.sin(x[1]), np.cos(x[0])])\n", " print(\"axis unit vector: [ %.5f, %.5f, %.5f ]\" % (au[0], au[1], au[2]))\n", " # unit vectors in the projection plane\n", " ath = np.array([np.cos(x[0])*np.cos(x[1]), np.cos(x[0])*np.sin(x[1]), -np.sin(x[0])])\n", " ala = np.array([-np.sin(x[1]), np.cos(x[1]), 0])\n", " # coordinates of projected points\n", " x = np.sum(X*np.tile(ala,(n,1)),axis=1)\n", " y = np.sum(X*np.tile(ath,(n,1)),axis=1)\n", " # other parameters:\n", " s, r, c = acfit(Xs, a)\n", " c = c + Xm\n", " return c, r, a\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Elements of the consensus set are in `X1[inliers,:]`. These are used in least squares estimation of parameters of the best fitting cylinder." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "axis unit vector: [ -0.42194, -0.69629, 0.58065 ]\n", "point on the axis : [ 66.8591081647 108.0224500592 -90.4356440426]\n", "radius : 100.26781589054922\n" ] } ], "source": [ "c, r, a = cylinder(X1[inliers,:])\n", "print(\"point on the axis : \", c)\n", "print(\"radius : \", r)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Our previous values were these:\n", "\n", " [ 100.6527872169 0.5315482736 0.6334361259 -0.5623300696\n", " 114.4770058482 186.0931126367 -159.2797358391]\n", "\n", "It can be seen that radius is slightly different and axis unit vector is in the opposite direction." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 1 }