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Affine invariance of interest points

Affine invariance of interest points. Overview. Scale invariance is not sufficient for large baseline changes State of the art on affine invariant points/regions Affine invariant interest points Application to recognition. Scale invariant Harris points.

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Affine invariance of interest points

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  1. Affine invariance of interest points

  2. Overview • Scale invariance is not sufficient for large baseline changes • State of the art on affine invariant points/regions • Affine invariant interest points • Application to recognition

  3. Scale invariant Harris points • Multi-scale extraction of Harris interest points • Selection of points at characteristic scale in scale space Chacteristic scale : - maximum in scale space - scale invariant Laplacian

  4. Scale invariant interest points invariant points + associated regions [Mikolajczyk & Schmid’01] multi-scale Harris points selection of points at the characteristic scale with Laplacian

  5. Viewpoint changes • Locally approximated by an affine transformation detected scale invariant region projected region

  6. State of the art • Affine invariant regions (Tuytelaars et al.’00) • ellipses fitted to intensity maxima • parallelogram formed by interest points and edges

  7. Isotropicneighborhoodsrelated by rotation State of the art • Theory for affine invariant neighborhood (Lindeberg’94)

  8. State of the art • Localization & scale influence affine neighhorbood => affine invariant Harris points (Mikolajczyk & Schmid’02) • Iterative estimation of these parameters • localization– local maximum of the Harris measure • scale – automatic scale selection with the Laplacian • affine neighborhood – normalization with second moment matrix Repeat estimation until convergence • Initialization with multi-scale interest points

  9. Affine invariant Harris points • Iterative estimation of localization, scale, neighborhood Initial points

  10. Affine invariant Harris points • Iterative estimation of localization, scale, neighborhood Iteration #1

  11. Affine invariant Harris points • Iterative estimation of localization, scale, neighborhood Iteration #2

  12. Affine invariant Harris points • Iterative estimation of localization, scale, neighborhood Iteration #3, #4, ...

  13. Affine invariant Harris points • Initialization with multi-scale interest points • Iterative modification of location, scale and neighborhood

  14. affine Harris Harris-Laplace Harris-Laplace + affine regions Affine invariant Harris points

  15. Affine invariant neighborhhood affine Harris detector affine Laplace detector

  16. Image retrieval … > 5000 images change in viewing angle

  17. Matches 22 correct matches

  18. Image retrieval … > 5000 images change in viewing angle + scale change

  19. Matches 33 correct matches

  20. 3D Recognition

  21. 3D Recognition 3D object modeling and recognition using affine-invariant patches and multi-view spatial constraints, F. Rothganger, S. Lazebnik, C. Schmid, J. Ponce, CVPR 2003

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