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Evaluation of interest points and descriptors

Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

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Page 1: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Evaluation of interest points and descriptors

Page 2: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Introduction

• Quantitative evaluation of interest point detectors– points / regions at the same relative location

=> repeatability rate

• Quantitative evaluation of descriptors– distinctiveness

=> detection rate with respect to false positives

Page 3: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Quantitative evaluation of detectors

• Repeatability rate : percentage of corresponding points

• Two points are corresponding if1. The location error is less than 1.5 pixel

2. The intersection error is less than 20%

homography

Page 4: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Comparison of different detectors

[Comparing and Evaluating Interest Points, Schmid, Mohr & Bauckhage, ICCV 98]

repeatability - image rotation

Page 5: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Comparison of different detectors

[Comparing and Evaluating Interest Points, Schmid, Mohr & Bauckhage, ICCV 98]

repeatability – perspective transformation

Page 6: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Harris detector + scale changes

Page 7: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Harris detector – adaptation to scale

Page 8: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Evaluation of scale invariant detectors

repeatability – scale changes

Page 9: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Evaluation of affine invariant detectors

0

40

60

70

repeatability – perspective transformation

Page 10: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Quantitative evaluation of descriptors

• Evaluation of different local features– SIFT, steerable filters, differential invariants, moment invariants,

cross-correlation

• Measure : distinctiveness– receiver operating characteristics of detection rate with respect to false positives

– detection rate = correct matches / possible matches– false positives = false matches / (database points * query points)

[A performance evaluation of local descriptors, Mikolajczyk & Schmid, CVPR’03]

Page 11: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Experimental evaluation

Page 12: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Scale change (factor 2.5)

Harris-Laplace DoG

Page 13: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Viewpoint change (60 degrees)

Harris-Affine (Harris-Laplace)

Page 14: Evaluation of interest points and descriptors. Introduction Quantitative evaluation of interest point detectors –points / regions at the same relative

Descriptors - conclusion

• SIFT + steerable perform best

• Performance of the descriptor independent of the detector

• Errors due to imprecision in region estimation, localization