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Stereo correspondence

Stereo correspondence

epipolar line. epipolar line. epipolar plane. Stereo correspondence. Determine Pixel Correspondence Pairs of points that correspond to same scene point. Epipolar Constraint Reduces correspondence problem to 1D search along conjugate epipolar lines

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735 views • 73 slides
Disparity Map Computation: Global-Style

Disparity Map Computation: Global-Style

Disparity Map Computation: Global-Style. Presentation by Scott Grauer-Gray. Stereo Overview. Given a reference image and matching (test) image Goal is to find the disparity between each pixel in the reference image and the corresponding pixel in the matching (test) image

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667 views • 43 slides
Stereo

Stereo

Stereo. Binocular Stereo Motivation Epipolar geometry Matching Depth estimation Rectification Calibration (finish up) Next Time Multiview stereo. Public Library, Stereoscopic Looking Room, Chicago, by Phillips, 1923. Teesta suspension bridge-Darjeeling, India.

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560 views • 39 slides
Stereo

Stereo

Stereo. Binocular Stereo Motivation Epipolar geometry Matching Depth estimation Rectification Calibration (finish up) Next Time Multiview stereo. Public Library, Stereoscopic Looking Room, Chicago, by Phillips, 1923. Teesta suspension bridge-Darjeeling, India.

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403 views • 39 slides
Scale and Rotation Invariant Matching Using Linearly Augmented Tree

Scale and Rotation Invariant Matching Using Linearly Augmented Tree

Scale and Rotation Invariant Matching Using Linearly Augmented Tree. Hao Jiang Boston College. Tai-peng Tian, Stan Sclaroff Boston University. Scale and Rotation Invariant Matching. Previous Methods. Hough Transform (Duda & Hart) and RANSAC (Fischler and Bolles)

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340 views • 34 slides
Human Posture Recognition with Convex Programming

Human Posture Recognition with Convex Programming

Human Posture Recognition with Convex Programming. Hao Jiang, Ze-Nian Li and Mark S. Drew School of Computing Science Simon Fraser University Burnaby, BC, V5A 1S6. Human Posture Recognition. Recognizing human postures is very important in vision and multimedia.

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288 views • 28 slides
Summary: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

Summary: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

Summary: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. Matthew Wilhelm CS5331 Mobile Robotics. Goal / Motivation. Provide means of quantitatively gauge progress in the field of Stereo Correspondence as well as judge the value of new approaches

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428 views • 24 slides
Learning Conditional Random Fields for Stereo

Learning Conditional Random Fields for Stereo

Learning Conditional Random Fields for Stereo. paper by Scharstein and Pal 2007, CVPR. The Problem. Trying to map the points in one of the views to the points in the other view. Helps perceive depth The amount of shift of each pixel from one view to the other is called its disparity.

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221 views • 13 slides

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