'Line fitting' presentation slideshows

Fitting & Matching

1.12k views • 91 slides

CS 558 Computer Vision

CS 558 Computer Vision. Fitting, RANSAC, and Hough Transfrom. Adapted from S. Lazebnik. Outline. Fitting: concept and basics Least square fitting: line fitting example Random sample consensus (RANSAC) Hough transform: line fitting example Hough transform: applications in vision. Outline.

862 views • 85 slides

Caracteristicas de Imagens II

Caracteristicas de Imagens II. Fitting. Etapas. Borda=cadeia de pixels. Borda=tem um modelo. p ?Borda. Finding Connected Components. Fitting. Finding Connected Components (Sequential Algorithm 4-connectivity). Scan the binary image left to right top to bottom

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Perception

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Computer Vision

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Fitting and Registration

02/14/12. Fitting and Registration. Computer Vision CS 543 / ECE 549 University of Illinois Derek Hoiem. Announcements. HW 1 due today Early feedback form. Fitting: find the parameters of a model that best fit the data

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Fitting

595 views • 48 slides

Model Fitting

10/03/11. Model Fitting. Computer Vision CS 143, Brown James Hays. Slides from Silvio Savarese , Svetlana Lazebnik, and Derek Hoiem. Fitting: find the parameters of a model that best fit the data Alignment: find the parameters of the transformation that best align matched points.

678 views • 43 slides

Model Fitting

10/03/11. Model Fitting. Computer Vision CS 143, Brown James Hays. Slides from Silvio Savarese , Svetlana Lazebnik, and Derek Hoiem. Fitting: find the parameters of a model that best fit the data Alignment: find the parameters of the transformation that best align matched points.

440 views • 43 slides

RANSAC Recap

RANSAC Recap. RANSAC - Setup. Given A dataset Example 1: Line fitting: Example 2: Homography fitting: A set of parameters that need to be fitted Line fitting: Homography estimation , A cost function Line fitting: Homography estimation (Reprojection error)

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Fitting

624 views • 39 slides

EE 7700

EE 7700. Geometric Transformations. Geometric Transformation. translation. Rotation matrix. scale. Scale matrix. rotation & scale. Rigid flow. Affine Flow. Perspective Flow. EE 7730. RANSAC: RANdom SAmple Consensus. Outliers. Consider the least squares fit for optical flow:.

516 views • 39 slides

L10. Laser Scanners

L10. Laser Scanners. EECS 598-2: Algorithms for Robotics. Administrative. PS2 is due today PS3 posted later tonight. Last Time. Topological Mapping Key ideas Data Association Nearest Neighbor Joint Compatibility RANSAC. Today. Finish up Data Association Laser scanners

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Least Square

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3D Geometry for Computer Graphics

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Fitting

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Fitting

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Fitting a Model to Data Reading: 15.1, 15.5.2

Fitting a Model to Data Reading: 15.1, 15.5.2. Cluster image parts together by fitting a model to some selected parts Examples: A line fits well to a set of points. This is unlikely to be due to chance, so we represent the points as a line.

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Using MCMC

Using MCMC. Separating MCMC from Bayesian Inference? Line fitting revisited A toy equaliser problem Some lessons A problem in film restoration/retouching. Articulate Probabilities [Bayesian Inference]. Try to see if you can integrate out nuisances. Derive the Posterior.

331 views • 18 slides

SPIRE Spectrometer Data Reduction: Spectral Line Fitting

SPIRE Spectrometer Data Reduction: Spectral Line Fitting. Nanyao Lu NHSC / IPAC (On behalf of the SPIRE ICC). Goals. Briefly discuss the SPIRE FTS instrumental line shape. Demos on how to fit lines and derive line fluxes in SPIRE FTS spectra:

270 views • 9 slides