Toward Accurate Feature Detectors Performance Evaluation

  • Pavel Smirnov
  • Piotr Semenov
  • Alexander Redkin
  • Anthony Chun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6962)

Abstract

The quality of interest point detectors is crucial for many computer vision applications. One of the frequently used integral methods to compare detectors’ performance is repeatability score. In this work, the authors analyze the existing approach for repeatability score calculation and highlight some important weaknesses and drawbacks of this method. Then we propose a set of criteria toward more accurate integral detector performance measure and introduce a modified repeatability score calculation. We also provide illustrative examples to highlight benefits of the proposed method.

Keywords

Interest Point Interest Point Detector Repeatability Score Neighborhood Criterion Interest Point Location 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pavel Smirnov
    • 1
  • Piotr Semenov
    • 1
  • Alexander Redkin
    • 1
  • Anthony Chun
    • 1
  1. 1.Intel LabsUSA

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