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Triangle-Constraint for Finding More Good Features Piero Zamperoni Best Student Paper Award, ICPR 2010 PowerPoint PPT Presentation


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Triangle-Constraint for Finding More Good Features Piero Zamperoni Best Student Paper Award, ICPR 2010. Xiaojie Guo and Xiaochun Cao Computer Vision Laboratory Tianjin University, China. Tianjin University Computer Vision Lab .

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Triangle-Constraint for Finding More Good Features Piero Zamperoni Best Student Paper Award, ICPR 2010

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Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Triangle-Constraint

for Finding More Good Features

Piero Zamperoni Best Student Paper Award, ICPR 2010

XiaojieGuo and Xiaochun Cao

Computer Vision Laboratory

Tianjin University, China

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Motivation

Many tasks in computer vision and pattern

recognition are based on local image features.

Feature Extraction

- Numerous feature extraction schemes have been proposed, like Harris Corner, SIFT etc.

Similarity Measurement

  • However, similarity measurements for features are limited.

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Motivation

For similarity measurement (SM), two factors, i.e.

&

need to be considered.

# correct matches/#total matches

However, recently proposed SMs only improve

the matching score but neglect the importance

of the num of correct matches

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Motivation

The neglect inspires us to propose an effective

similarity measurement for

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Motivation

There are 39 hits (matching score 85.97%))using the original matching method(OMM).

There are 216 hits (matching score 93.11%)using our method(T-CM).

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Triangle-Constraint Measurement

Seed Point Selection – Bi-matching

Illustration of bi-matching method.

The matches (seed points) are those marked by ellipses.

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Triangle-Constraint Measurement

Organization of Seed Points

Seed point

False positive match

Illustration of the Delaunay algorithm

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Triangle-Constraint Measurement

Triangle-Constraint

PA

Pi

PB

=

*

Illustration of the Triangle-Constraint

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Triangle-Constraint Measurement

Triangle-Constraint

S

S

the descriptors for the Pi and the Cj respectively

Radius of candidate area R

A set containing all the temporary matches for PA and PB

the Euclidean distance between the Cj and the Pi

A predefined threshold

Pe

To handle the problem of false positive matches survived from

Bi-matching, an additional step is taken after processing all the

features from PA:

The similarity score between the Pi and the candidate feature Cj

is measured by

If the maximum score of all the features in C is greater than a

predefined threshold τ, the corresponding feature pair is

considered as temporary match.

To decide whether the temporary matches are accepted as final matches or not.

C

Illustration of the Triangle-Constraint

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Experiment Evaluation

Dataset – INRIA dataset

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Experiment Evaluation

Evaluation Criterion

  • The criterion of our evaluation is based on the number of

  • correct matches and the matching score.

  • - A match is defined as correct if the distance between the ac-

  • curate location and the estimated location is less than

  • 6 pixels, incorrect otherwise.

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Experiment Evaluation

Results – Relative image pair matching

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Experiment Evaluation

Results – Relative image pair matching

Due to the huge amount of features that increasesthe possibility of accidentally considering incorrect matches as correct.

Since the matching score is undefined (0/0)

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Experiment Evaluation

Results – Irrelative image pair matching

There are 22 hits by the OMM and 0 hit by our method.

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Conclusion

  • Triangle-Constraint Measurement:

  • Effective technique for similarity measurement to

  • improve both the number of correct matches and

  • the matching score.

  • Invariant to translation, rotation , scale and affine

  • transformations.

  • Robust to partial perspective distortions.

Tianjin University Computer Vision Lab


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

Question

Questions?

Computer Vision Lab @ TJU

Tianjin University Computer Vision Lab

2009-08-11


Triangle constraint for finding more good features piero zamperoni best student paper award icpr 2010

http://cs.tju.edu.cn/orgs/vision

Thank you very much!

Computer Vision Lab @ TJU

Tianjin University Computer Vision Lab

2009-08-11


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