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Robust Wide Baseline Stereo from Maximally Stable Extremal Region. J. Matas, O Chum, M. Urban, T. Pajdle BMVC 2002. Introduction. Objective : Finding correspondences in two images. An enabling step toward many applications. Distinguished Regions. Maximally Stable Extremal Regions. - PowerPoint PPT Presentation
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Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
Page 1
Robust Wide Baseline Stereofrom
Maximally Stable Extremal Region
J. Matas, O Chum, M. Urban, T. Pajdle
BMVC 2002
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
Page 2
Introduction
Objective:
Finding correspondences in two images.
An enabling step toward many applications.
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
Page 3
Distinguished Regions
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
Page 4
Maximally Stable Extremal Regions
Distinguished Regions
o Stabilityo Adjacency preservingo Invariance to affineo Multi-scale detection
Dept. of Electrical and Computer EngineeringUniversity 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 EngineeringUniversity of Missouri, Columbia, MO
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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 EngineeringUniversity 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 EngineeringUniversity of Missouri, Columbia, MO
Page 8
Maximally Stable Extremal Regions
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
Page 9
Maximally Stable Extremal Regions
Dept. of Electrical and Computer EngineeringUniversity 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 EngineeringUniversity of Missouri, Columbia, MO
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Epipolar Geometry (EG)
Region Matching
Rough Affine
Refine EG
Saliency Detection
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
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Applications
Estimation of Epipolar Geometry
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
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Applications
Tracking of license plates
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
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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 EngineeringUniversity of Missouri, Columbia, MO
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Remarks
Stable salient point/regions detection.
Application in epipolar geometry and tracking.
Potential feature transform descriptor.
Dept. of Electrical and Computer EngineeringUniversity of Missouri, Columbia, MO
Page 16
Thank you
