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

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

研究成果: 著書/レポートタイプへの貢献会議での発言

抜粋

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.

元の言語英語
ホスト出版物のタイトルTwelfth International Conference on Quality Control by Artificial Vision
出版者SPIE
9534
ISBN(電子版)9781628416992
DOI
出版物ステータス出版済み - 2015
イベント12th International Conference on Quality Control by Artificial Vision - Le Creusot, フランス
継続期間: 6 3 20156 5 2015

その他

その他12th International Conference on Quality Control by Artificial Vision
フランス
Le Creusot
期間6/3/156/5/15

All Science Journal Classification (ASJC) codes

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

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  • これを引用

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