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2021-02-27 04:35:35 -0500 | received badge | ● Popular Question (source) |

2018-04-14 08:33:41 -0500 | commented question | [OPENCV GPU] How can I convert GpuMat and Vector<Point2f> I'm trying to do the exactly same thing as you, @kjoshi. Have you solved it? |

2018-04-06 12:03:41 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system It works! The concatenated position estimates drifts quite alot, but the whole thing works now, finally! The (major) fix |

2018-04-05 11:27:55 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system Original 2D feature = [73, 149], the projected point from 3D = [149, 73]. Ok, except vector is flipped. But, if origina |

2018-04-05 11:26:57 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system Original 2D feature = [73, 149], the projected point from 3D = [149, 73]. Ok, except vector is flipped. But, if origina |

2018-04-05 11:17:31 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system Nice. Ok, I seem to be making some progress now, most of the projected 2D points (from the 3D features using cv::project |

2018-04-05 08:29:25 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I see, thanks. And then I guess that it's the same for cv::projectPoints(), using P1 and a zeroed distCoeffs matrix? I w |

2018-04-05 08:29:10 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I see, thanks. And then I guess that it's the same for cv::projectPoints(), using P1 and a zeroed distCoeffs matrix? I w |

2018-04-05 08:28:32 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I see, thanks. And then I guess that it's the same for cv::projectPoints(), using P1 and a zeroed distCoeffs matrix? I w |

2018-04-05 08:27:29 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system |

2018-04-05 08:26:58 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I see, thanks. And then I guess that it's the same for 'cv::projectPoints()', using P1 and a zeroed 'distCoeffs' matrix? |

2018-04-05 05:18:52 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:18:36 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8] |

2018-04-05 05:18:22 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:17:52 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:17:38 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system { struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:17:18 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:16:17 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:15:58 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:15:51 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:15:14 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system struct DUO_STEREO { double M1[9], M2[9]; // 3x3 - Camera matrices (left, right) double D1[8], D2[8]; |

2018-04-05 05:14:00 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system Shouldn't the cameraMatrix in solvePnP be the 3x3 cameraMatrix from stereoRectify()? Anyhow, I get the stereo parameters |

2018-04-04 07:08:23 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I've become aware of that the cv::solvePnP function, when having non-empty Q and M input variables, assumes that the fea |

2018-04-04 07:08:11 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I've become aware of that the cv::solvePnP function, when having non-empty Q and M input variables, assumes that the fea |

2018-04-04 07:04:13 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I've become aware of that the cv::solvePnP function, when having non-empty Q and M input variables, assumes that the fea |

2018-03-21 15:16:51 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system Thanks! I still struggle with getting sensible results from my algorithm (the tvec from solvePnP still doesn't make sens |

2018-03-20 09:11:16 -0500 | received badge | ● Supporter (source) |

2018-03-20 09:11:06 -0500 | marked best answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I know that there exists many posts regarding pose estimation using solvePnP/solvePnPRansac, and I've read most of them, but my case differs slightly from what seems to be the standard scenario, and even if I think I've got it I just can't seem to get it to work and would like someone to correct me if I'm doing anything wrong. This post became quite long, but please bear with me. I'm trying to use solvePnPRansac to calculate the motion of a stereo camera from one frame/time instance to the next. I detect features in the first frame and track them to the next frame. I'm also using a stereo camera that comes with a SDK which provides me with the corresponding 3D coordinates of the detected features. I believe that the 3D input points of solvePnPRansac should be wrt a world frame, but since I don't have a world frame, I try to do the following: 1) For the very first frame: I set the initial camera pose as the world frame, since I need a constant reference for computation of relative movement. This means that the 3D points calculated in this frame now equals the world points, and that the movement of the camera is relative to the initial camera pose. 2) Call solvePnPRansac with the world points from the first frame together with the 2D features detected in the second frame as inputs. It returns rvec and tvec
Now I'm a little confused as to which 3D points I should use in the further calculations. Should I transform the 3D points detected in the second frame (which is given wrt the camera) to the world frame? If I combine the tvec and rvec into a homogeneous-transformation matrix T (which would represent the homogeneous transformation from the world frame to the second frame), the transformation should be
If I do this, I can capture a new image (third frame), track the 2D features detected in the second frame to the third frame, compute the corresponding 3D points (which is given wrt the third frame) and call solvePnPRansac with "3Dpoints_at_frame2_in_worldcoordinates" and the ... (more) |

2018-03-20 07:48:20 -0500 | commented answer | composeRT input/output question I see! Thanks! |

2018-03-20 07:45:35 -0500 | marked best answer | composeRT input/output question I have two frame transformations, one from frame 0 to frame 1, and one from frame 1 to frame 2, and I would like to concatenate these into the transformation from frame 0 to frame 2. I'm computing the pose of a moving camera, and the first transformation (0-1) represent the previous pose of the camera (transformation from its initial pose) and the 1-2 transformation is the newest change of pose, represented by tvec and rvec gotten from solvePnPRansac. However, as I cannot just try out different inputs in my code and see if the output seems correct, since my system currently consists of lots of noise, I would like to have the math check out before I implement it into my application. But while I try to use the formulas given in the documentation with different rvecs and tvecs, I can't get the outputs (rvec3/tvec3) I want. These are the formulas: I've tried with the following rvecs/tvecs: - rvec1: Rotation
*from*frame 1*to*frame 0 - tvec1: vector
*from*the origin of frame 0*to*the origin of frame 1, given in*frame 0 coordinates* - rvec2: Rotation
*from*frame 2*to*frame 1 - tvec2: vector
*from*the origin of frame 1*to*the origin of frame 2, given in*frame 1 coordinates*
I want to end up with: - rvec3: Rotation from frame 0 to frame 2 (or inversed, doesn't matter)
- tvec3: vector
*from*frame 0*to*frame 2 given in*frame 0 coordinates*(or negated)
However, with these vectors, I can't get the formula in the documentation to make sense. The rvec3-formula makes sense, and with rvec1/rvec2 I get rvec3=(rvec2*rvec1)⁻¹ to equal the rotation from frame 2 to frame 0. However, the computation of tvec3 doesn't add up: The formula says tvec3 = rvec2 * tvec1 + tvec2, but rvec2 * tvec1 doesn't make sense with my vectors. I mean, it says to rotate a vector given in frame 0 coordinates from frame 2 to frame 1. A vector given in frame 0 coordinates need to be multiplied with a rotation matrix representing the rotation Someone that could help me with these calculcations? Thanks! |

2018-03-20 07:45:35 -0500 | received badge | ● Scholar (source) |

2018-03-15 08:23:20 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system I see, but how should I model/compute that? The paper suggests Gaussian noise, but in that case, with what parameters? B |

2018-03-14 17:03:30 -0500 | commented answer | Stereo camera pose estimation from solvePnPRansac using 3D points given wrt. the camera coordinate system Ok, so numStdDev is an algorithm parameter that is chosen by the user, but what exactly is the pixelError? Is it the ave |

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