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Specifically I'd ideally want images with point correspondences and a 'Gold Standard' calculated value of F and left and right epipoles. I could work with an Essential matrix and intrinsic and extrinsic camera properties too.

I know that I can construct F from two projection matrices and then generate left and right projected point coordinates from 3D actual points and apply Gaussian noise but I'd really like to work with someone else's reference data since I'm trying to test the efficacy of my code and writing more code to test the first batch of (possibly bad) code doesn't seem smart.

Thanks for any help

Regards Dave

connectedsoftware
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Dave Durbin
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1 Answers1

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You should work with ground truth datasets for multi-view reconstructions. I recommend to use the Middlebury Multi-View Stereo datasets. Besides the image data in lossless format, they deliver camera parameters, such as camera pose and intrinsic camera calibration as well as the possibility to evaluate your own multi-view reconstruction system.

Perhaps, the results are not computed by "the" gold standard algorithm proposed in the book of Hartley and Zisserman but you can use it to compute the fundamental matrices you require between two views.

To compute the fundamental matrix F from two projection matrices P1 and P2 refer to the code Andrew Zisserman provides.

who9vy
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  • I've marked this as the right answer because there's nothing in it that's wrong (and I have used the Middlebury data sets for testing disparity calculation code) but I couldn't find camera pose data. -- It's possible I didn't search hard enough though. The dissertation is now in so the need has passed. Thanks. – Dave Durbin Oct 13 '13 at 12:35