Pose estimation: solvePnP and epipolar geometry do not agree

问题

I have a relative camera pose estimation problem where I am looking at a scene with differently oriented cameras spaced a certain distance apart. Initially, I am computing the essential matrix using the 5 point algorithm and decomposing it to get the R and t of camera 2 w.r.t camera 1.

I thought it would be a good idea to do a check by triangulating the two sets of image points into 3D, and then running solvePnP on the 3D-2D correspondences, but the result I get from solvePnP is way off. I am trying to do this to "refine" my pose as the scale can change from one frame to another. Anyway, In one case, I had a 45 degree rotation between camera 1 and camera 2 along the Z axis, and the epipolar geometry part gave me this answer:

Relative camera rotation is [1.46774, 4.28483, 40.4676]
Translation vector is [-0.778165583410928;  -0.6242059242696293;  -0.06946429947410336]

solvePnP, on the other hand..

Camera1: rvecs [0.3830144497209735;   -0.5153903947692436;  -0.001401186630803216]
         tvecs [-1777.451836911453;  -1097.111339375749;  3807.545406775675]
Euler1 [24.0615, -28.7139, -6.32776]

Camera2: rvecs [1407374883553280; 1337006420426752; 774194163884064.1] (!!)
         tvecs[1.249151852575814;  -4.060149502748567;  -0.06899980661249146]
Euler2 [-122.805, -69.3934, 45.7056]

Something is troublingly off with the rvecs of camera2 and tvec of camera 1. My code involving the point triangulation and solvePnP looks like this:

points1.convertTo(points1, CV_32F);
points2.convertTo(points2, CV_32F);

 // Homogenize image points

points1.col(0) = (points1.col(0) - pp.x) / focal;
points2.col(0) = (points2.col(0) - pp.x) / focal;
points1.col(1) = (points1.col(1) - pp.y) / focal;
points2.col(1) = (points2.col(1) - pp.y) / focal;

points1 = points1.t();      points2 = points2.t();

cv::triangulatePoints(P1, P2, points1, points2, points3DH);

cv::Mat points3D;
convertPointsFromHomogeneous(Mat(points3DH.t()).reshape(4, 1), points3D);

cv::solvePnP(points3D, points1.t(), K, noArray(), rvec1, tvec1, 1, CV_ITERATIVE );
cv::solvePnP(points3D, points2.t(), K, noArray(), rvec2, tvec2, 1, CV_ITERATIVE );

And then I am converting the rvecs through Rodrigues to get the Euler angles: but since rvecs and tvecs themselves seem to be wrong, I feel something's wrong with my process. Any pointers would be helpful. Thanks!

来源：https://stackoverflow.com/questions/31898698/pose-estimation-solvepnp-and-epipolar-geometry-do-not-agree

标签

OpenCV

computer-vision

pose-estimation