tailieunhanh - Stereo

Binocular stereo, basic stereo matching algorithm, essential matrix for parallel images, depth from disparity, depth from disparity, stereo matching as energy minimization,. As the main contents of the lecture "Stereo". Each of your content and references for additional lectures will serve the needs of learning and research. | Stereo Many slides adapted from Steve Seitz Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image image 1 image 2 Dense depth map Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image Humans can do it Stereograms: Invented by Sir Charles Wheatstone, 1838 Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image Humans can do it Autostereograms: Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image Humans can do it Autostereograms: Basic stereo matching algorithm For each pixel in the first image Find corresponding epipolar line in the right image Examine all pixels on the epipolar line and pick the best match Triangulate the matches to get depth information Simplest case: epipolar lines are scanlines When does this happen? Simplest Case: Parallel images Image planes of cameras are parallel to each other and to the baseline Camera centers are at same height Focal lengths are the same Simplest Case: Parallel images Image planes of cameras are parallel to each other and to the baseline Camera centers are at same height Focal lengths are the same Then, epipolar lines fall along the horizontal scan lines of the images Essential matrix for parallel images R = I t = (T, 0, 0) Epipolar constraint: t x x’ Essential matrix for parallel images Epipolar constraint: R = I t = (T, 0, 0) The y-coordinates of corresponding points are the same! t x x’ Depth from disparity f x x’ Baseline B z O O’ X f Disparity is inversely proportional to depth! Stereo image rectification Stereo image rectification reproject image planes onto a common plane parallel to the line between optical centers pixel motion is horizontal after this transformation two homographies (3x3 transform), one for each input image reprojection C. Loop and Z. Zhang. Computing Rectifying . | Stereo Many slides adapted from Steve Seitz Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image image 1 image 2 Dense depth map Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image Humans can do it Stereograms: Invented by Sir Charles Wheatstone, 1838 Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image Humans can do it Autostereograms: Binocular stereo Given a calibrated binocular stereo pair, fuse it to produce a depth image Humans can do it Autostereograms: Basic stereo matching algorithm For each pixel in the first image Find corresponding epipolar line in the right image Examine all pixels on the epipolar line and pick the best match Triangulate the matches to get depth information Simplest case: epipolar lines are scanlines When does this happen? Simplest Case: Parallel images Image planes of cameras are

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