Triangulation - Combining Data from Multiple Cameras

asked 2020-09-11 15:06:37 -0600

ConnorM gravatar image

I have a setup with 8 synchronized cameras and I am trying to perform some 3D reconstruction of keypoints on a persons body. I am wondering if there is a way for me improve my triangulation results from OpenCV by performing some sensor fusion or other technique.

Currently I am just pairing the cameras to create stereo pairs, calculating the 3D points with triangulatePoints (and other data like intrinsic/extrinsics from chessboard calibration), and then I’m left with multiple estimates (one estimate of the point from each pair) of the same keypoints that I can average out for example.

If anyone has any ideas or knows of any papers that may help with this it would be really appreciated!

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berak gravatar imageberak ( 2020-09-12 03:35:05 -0600 )edit

From what I've seen of other SFM work is that people are generally using feature detectors/matchers like ORB/SIFT etc. in order to get the scene points and then use those points to perform bundle adjustment. Are there any examples of people using chessboard calibration for intrinsic/extrinsic parameters and then using SFM with the already obtained camera matrices/distortion coefficients and other parameters?

ConnorM gravatar imageConnorM ( 2020-09-13 15:50:59 -0600 )edit