Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 1 Robust Wide Baseline Stereo from Maximally Stable Extremal Region.

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Presentation transcript:

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 1 Robust Wide Baseline Stereo from Maximally Stable Extremal Region J. Matas, O Chum, M. Urban, T. Pajdle BMVC 2002

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 2 Introduction Objective: Finding correspondences in two images.  An enabling step toward many applications.

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 3 Distinguished Regions

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 4 Maximally Stable Extremal Regions Distinguished Regions oStability oAdjacency preserving oInvariance to affine oMulti-scale detection

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 5 Extremal/Maximal Regions Definition: A set of all connected components (pixels) below all thresholds. g=0.2 g=0.4 g=0.9

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 6 Extremal/Minimal Regions Definition: A set of all connected components (pixels) above all thresholds. g=0.2 g=0.4 g=0.9

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 7 Maximally Stable Extremal Regions Stable Regions: An extremal region stays virtually unchanged over a range threshold.

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 8 Maximally Stable Extremal Regions

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 9 Maximally Stable Extremal Regions

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 10 Maximally Stable Extremal Regions Descriptor Location of intensity maximum/minimum, Threshold. Measurement region Ellipse, circle, rectangular image patches, contours. Similarity Mohalanobis distance, correlation, etc.

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 11 Epipolar Geometry (EG) Region Matching Rough Affine Refine EG Saliency Detection

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 12 Applications Estimation of Epipolar Geometry

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 13 Applications Tracking of license plates

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 14 Applications Face tracking Pixels of color image are ordered by Mahananobis distance to the estimated skin-tone Gaussian distribution in R-G space.

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 15 Remarks  Stable salient point/regions detection.  Application in epipolar geometry and tracking.  Potential feature transform descriptor.

Dept. of Electrical and Computer Engineering University of Missouri, Columbia, MO Page 16 Thank you