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Image Registration Lecture 16:Uncertainty-Driven Point-Based Image Registration April 28, 2005

Image Registration Lecture 16:Uncertainty-Driven Point-Based Image Registration April 28, 2005. Prof. Charlene Tsai. Introduction. ICP algorithms and its variants are popular for point-based registration Variants often extend the ICP to include: Surface color Surface normal Curvature

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Image Registration Lecture 16:Uncertainty-Driven Point-Based Image Registration April 28, 2005

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  1. Image Registration Lecture 16:Uncertainty-Driven Point-Based Image RegistrationApril 28, 2005 Prof. Charlene Tsai

  2. Introduction • ICP algorithms and its variants are popular for point-based registration • Variants often extend the ICP to include: • Surface color • Surface normal • Curvature • A new trend is to drive the optimization process using uncertainty (covariance matrix) Lecture 16

  3. Two Algorithms • Both summarized in the book chapter by Charles V. Stewart, “Uncertainty-Driven Point-Based Image Registration” • Stable sampling of ICP constraints, by Gelfand et al (“Geometrically Stable Sampling for the ICP Algorithms”) • Dual-Bootstrap ICP, by Stewart et al (“The Dual-Bootstrap Iterative Closest Point Algorithm with Application to Retinal Image Registration“) Lecture 16

  4. Motivation Problem for Algorithm A • The set of surfaces being aligned differ significantly in size • When a small amount of noise is added to the data, the matches from the grooves are easily mistaken as noise. Lecture 16

  5. Proposed Solution by Gelfand et al. • Using the covariance matrix to sample the correspondences • Resulting in estimate being well-constrained in all directions in parameter space Lecture 16

  6. Motivation Problem for Algorithm B • Complex vascular structure=>high % of mismatches even for small initial misalignment Lecture 16

  7. Proposed Solution by Stewart et al. • Using the covariance matrix to guide • region-growing and • model-selection • Resulting in accurate estimate from low-order initial estimates that are only accurate in small image regions. Lecture 16

  8. Lecture 16

  9. Next Lecture … • We’ll start with DB-ICP algorithm • Please do your best to read the paper by Stewart (stewart-tmi03.pdf) or section 5 of stewart_point_covar.pdf before next Monday. Lecture 16

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