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Home/ Questions/Q 6843987
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Editorial Team
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Editorial Team
Asked: May 27, 20262026-05-27T00:19:15+00:00 2026-05-27T00:19:15+00:00

I try to match two overlapping images captured with a camera. To do this,

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I try to match two overlapping images captured with a camera. To do this, I’d like to use OpenCV. I already extracted the features with the SurfFeatureDetector. Now I try to to compute the rotation and translation vector between the two images.

As far as I know, I should use cvFindExtrinsicCameraParams2(). Unfortunately, this method require objectPoints as an argument. These objectPoints are the world coordinates of the extracted features. These are not known in the current context.

Can anybody give me a hint how to solve this problem?

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  1. Editorial Team
    Editorial Team
    2026-05-27T00:19:15+00:00Added an answer on May 27, 2026 at 12:19 am

    The problem of simultaneously computing relative pose between two images and the unknown 3d world coordinates has been treated here:

    Berthold K. P. Horn. Relative orientation revisited. Berthold K. P. Horn. Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 545 Technology …

    EDIT: here is a link to the paper:
    http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.64.4700

    Please see my answer to a related question where I propose a solution to this problem:

    OpenCV extrinsic camera from feature points

    EDIT: You may want to take a look at bundle adjustments too,

    http://en.wikipedia.org/wiki/Bundle_adjustment

    That assumes an initial estimate is available.

    EDIT: I found some code resources you might want to take a look at:

    Resource I:

    http://www.maths.lth.se/vision/downloads/

    Two View Geometry Estimation with Outliers

    C++ code for finding the relative orientation of two calibrated
    cameras in presence of outliers. The obtained solution is optimal in
    the sense that the number of inliers is maximized.

    Resource II:

    http://lear.inrialpes.fr/people/triggs/src/ Relative orientation from
    5 points: a somewhat more polished C routine implementing the minimal
    solution for relative orientation of two calibrated cameras from
    unknown 3D points. 5 points are required and there can be as many as
    10 feasible solutions (but 2-5 is more common). Also requires a few
    CLAPACK routines for linear algebra. There’s also a short technical
    report on this (included with the source).

    Resource III:

    http://www9.in.tum.de/praktika/ppbv.WS02/doc/html/reference/cpp/toc_tools_stereo.html
    vector_to_rel_pose Compute the relative orientation between two
    cameras given image point correspondences and known camera parameters
    and reconstruct 3D space points.

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