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estimateUncalibratedRectification

Uncalibrated stereo rectification

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Syntax

[T1,T2] = estimateUncalibratedRectification(F,inlierPoints1,inlierPoints2,imagesize)

描述

example

[T1,T2] = estimateUncalibratedRectification(F,inlierPoints1,inlierPoints2,imagesize)returns projective transformations for rectifying stereo images. This function does not require either intrinsic or extrinsic camera parameters.

Examples

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Open Live Script

This example shows how to compute the fundamental matrix from corresponding points in a pair of stereo images.

Load the stereo images and feature points which are already matched.

I1 = imread('yellowstone_left.png'); I2 = imread('yellowstone_right.png'); loadyellowstone_inlier_points;

Display point correspondences. Notice that the matching points are in different rows, indicating that the stereo pair is not rectified.

showMatchedFeatures(I1, I2,inlier_points1,inlier_points2,'montage'); title('Original images and matching feature points');

Figure contains an axes object. The axes object with title Original images and matching feature points contains 4 objects of type image, line.

Compute the fundamental matrix from the corresponding points.

f = estimateFundamentalMatrix(inlier_points1,inlier_points2,...'Method','Norm8Point');

Compute the rectification transformations.

[t1, t2] = estimateUncalibratedRectification(f,inlier_points1,...inlier_points2,size(I2));

Rectify the stereo images using projective transformations t1 and t2.

[I1Rect,I2Rect] = rectifyStereoImages(I1,I2,t1,t2);

Display the stereo anaglyph, which can also be viewed with 3-D glasses.

figure; imshow(stereoAnaglyph(I1Rect,I2Rect));

Figure contains an axes object. The axes object contains an object of type image.

Input Arguments

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Fundamental matrix for the stereo images, specified as a 3-by-3 fundamental matrix. The fundamental matrix satisfies the following criteria:

IfP1, a point in image1, corresponds toP2, a point in image2, then:
[P2,1] *F* [P1,1]' = 0

Fmust be double or single.

Coordinates of corresponding points in image one, specified as anM-by-2 matrix ofMnumber of [x y] coordinates, or as aORBPoints,BRISKPoints,SIFTPoints,SURFPoints,MSERRegions, orcornerPointsobject.

Coordinates of corresponding points in image two, specified as anM-by-2 matrix ofMnumber of [x y] coordinates, or as aORBPoints,BRISKPoints,SIFTPoints,SURFPoints,MSERRegions, orcornerPointsobject.

Second input image size, specified as a double, single, or integer value and in the format returned by thesizefunction. The size of input image2corresponds toinlierPoints2.

Output Arguments

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Projective transformation, returned as a 3-by-3 matrix describing the projective transformations for input imageT1.

Projective transformation, returned as a 3-by-3 matrix describing the projective transformations for input imageT2.

Tips

  • An epipole may be located in the first image or the second image. Applying the output uncalibrated rectification ofT1(orT2) to image1(or image2) may result in an undesired distortion. You can check for an epipole within an image by applying theisEpipoleInImagefunction.

References

[1] Hartley, R. and A. Zisserman.Multiple View Geometry in Computer Vision. Cambridge University Press. 2003.

[2] Pollefeys, M., Koch, R., and Van Gool, L..A Simple and Efficient Rectification Method for General Motion. Proceedings of the Seventh IEEE International Conference on Computer Vision. Volume 1, pages 496-501. 1999. DOI:10.1109/ICCV.1999.791262.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced in R2012b

See Also

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