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opencv3d-reconstructionpose-estimationaruco

How to increase aruco detection accuracy?

I have filmed an object on aruco board from two positions with the same camera. I've undistorted images and calibrated camera before work. I take one red point on one shot and calculate 3d line, which corresponds to this point 3D space, and then project it to another image:

p1

p2

The problem is that there is some discrepancy (~5px-15px) between line and point on another image. I also observed the same problem with opengl-generated images, so it doesn't seem to be a problem of my camera. I use this piece of code to detect board position:

MarkerMapPoseTracker MSPoseTracker;  // tracks the pose of the marker map
MSPoseTracker.setParams(camParam, theMarkerMapConfig);
MSPoseTracker.estimatePose(ret.markers);

Is it possible to increase tolerance somehow? I've also found function which has some sort of tolerance parameter:

bool estimatePose(Marker& m, const CameraParameters& cam_params, float markerSize, float minErrorRatio = 4 /*tau_e in paper*/)

but I don't know how to pass this parameter to MSPoseTracker.estimatePose. How can I improve precision, if I believe its possible to do it at least theory?

Solution

  • I have ended up with brute-force solution, which I have implemented in lack of time. I've taken coordinates of markers borders on the calibration board with getMarker3DInfo, found coordinates of the points being projected with cv::projectPoints, then found a homography between these two groups of four points. This allowed me to calculate L2 norm between original photo and projected calibration board. Then I have connected bobyqa algorithm, which is opensource GNU optimisation libraty, specialised for multidimensional optimisation with no derivatives for heavy-calculating discrepancy function. This gives pretty good result:

    enter image description here