Is cv::triangulatePoints() returning 3D points in world coordinate system?

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It depends on used projection matrices to call the function.

Where to look for projection matrices?

As OpenCV documentation suggests you can use stereoRectify() which needs results from calibrateCamera and stereoCalibration. As far as I know, it chooses new coordinate system which has an origin between the cameras.

Another way to get projection matrices is to compute it by yourself. Let's assume that first camera position creates your world coordinate system. Projection matrix could be computed as A * [R | T], where A is a instristic matrix for the camera and R is rotation vector and T translation vector. So for the first position you set as rotation matrix identity and as a translation vector [0,0,0,1]^T. For the second projection matrix use the output of R, T from the stereoCalibrate.

I am working on locating an object in stereo vision, so far this approach gives me reasonable results. Please let me know if there is somewhere a problem.

Also I recommend to take a look at this question at StackOverflow

The function cv::triangulatePoints() will compute, reconstruct the 3D points in the camera frame (the left camera frame should be the reference, to be checked).

Also, from my knowledge, this function should work only for a stereo camera setup where the two image views are fronto-parallel (the images are rectified with cv::stereoRectify()):

One last thing, cv::triangulatePoints() needs the two projection matrices of the two cameras, that is the transformation between the left and right camera frames. In case of I am wrong and it is possible to use cv::triangulatePoints() with non fronto-parallel views, you will still need to have the relationship, the transformation matrix between the two camera frames (the intrinsic matrix and the pairs of points are not sufficient).