Three-DoF pose estimation of asteroids by appearance-based linear regression with divided parameter space

Naoki Kobayashi, Yuji Oyamada, Yoshihiko Mochizuki, Hiroshi Ishikawa

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

1 Citation (Scopus)

Abstract

We present an appearance-based linear regression method for pose estimation from a single image of an asteroid, which can have any pose in the full space of three degree-of-freedom rotation parameters. The method is characterized by its division of the parameter space into multiple regions. Given a large number of training images with known pose parameters, we learn the relationship between the images and the pose parameters, separately for each parameter region, using the standard linear pose estimation. We also create a common subspace such that, when projected to it, the difference between images in the same parameter region tends to collapse. In estimating the pose of an input image, we project it onto the common subspace to determine the parameter region. We apply the method for pose estimation from asteroid images and report the experimental results.

Original languageEnglish
Title of host publicationProceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages551-554
Number of pages4
ISBN (Print)9784901122153
DOIs
Publication statusPublished - 2015 Jul 8
Event14th IAPR International Conference on Machine Vision Applications, MVA 2015 - Tokyo, Japan
Duration: 2015 May 182015 May 22

Other

Other14th IAPR International Conference on Machine Vision Applications, MVA 2015
CountryJapan
CityTokyo
Period15/5/1815/5/22

    Fingerprint

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Kobayashi, N., Oyamada, Y., Mochizuki, Y., & Ishikawa, H. (2015). Three-DoF pose estimation of asteroids by appearance-based linear regression with divided parameter space. In Proceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015 (pp. 551-554). [7153252] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MVA.2015.7153252