A self-diagnosis under 2D projectivity for local descriptor base template matching

Hidehiro Ohki, Rin-Ichiro Taniguchi, Tokihiro Kimura, Naomichi Sueda, Keiji Gyohten

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

2D projectivity is an invertible mapping to present the perspective imaging of a world plane by projective translation, called homography. Good image feature have to be robust under 2D projectivity caused by any camera movements. In the standard performance evaluation of template matching, many real captured images of many scenes are ordinarily used. However it is not enough to evaluate the robustness under 2D projectivity in detail because the variations of real camera pose and position in the 3D world are limited and the capturing cost is expensive. During the early stage of the template matching development, an easy performance evaluation method is required to examine the behavior. We propose a self-diagnosis method to measure the robustness of local descriptor base template matching between a template image and reference images which are created by projective translation of the template image. We focus on the template matching consisting of a feature point extraction and a local descriptor matching. The proposed method evaluates the spatial accuracy of the feature points and the estimated template positions in the reference images with local descriptor matchings. Four metrics, feature point precision (PP), feature point recall (PR), local descriptor matching precision (MP) and local descriptor matching recall (MR) are introduced to evaluate the performance. The experiment results will be appeared in the final manuscript to show the effectiveness of our method.

Original languageEnglish
Title of host publicationTwelfth International Conference on Quality Control by Artificial Vision
PublisherSPIE
Volume9534
ISBN (Electronic)9781628416992
DOIs
Publication statusPublished - 2015
Event12th International Conference on Quality Control by Artificial Vision - Le Creusot, France
Duration: Jun 3 2015Jun 5 2015

Other

Other12th International Conference on Quality Control by Artificial Vision
CountryFrance
CityLe Creusot
Period6/3/156/5/15

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All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Ohki, H., Taniguchi, R-I., Kimura, T., Sueda, N., & Gyohten, K. (2015). A self-diagnosis under 2D projectivity for local descriptor base template matching. In Twelfth International Conference on Quality Control by Artificial Vision (Vol. 9534). [95340W] SPIE. https://doi.org/10.1117/12.2182925