Detail publikace

CAMERA LOCALIZATION USING INCOMPLETE CHESSBOARD PATTERN

Originální název

CAMERA LOCALIZATION USING INCOMPLETE CHESSBOARD PATTERN

Anglický název

CAMERA LOCALIZATION USING INCOMPLETE CHESSBOARD PATTERN

Jazyk

en

Originální abstrakt

This paper introduces the approach for the real-time camera localization by capturing the plane of chessboard pattern. This task has been already solved by several different approaches, but we present the novel method of the chessboard reconstruction from its incomplete image, that enables successful camera localization even if the captured chessboard plane is partially covered by an unknown object. The camera position and orientation is during the processing of the videosequence tracked with the Kalman filter that enables correct localization also in the closeup views on the pattern.

Anglický abstrakt

This paper introduces the approach for the real-time camera localization by capturing the plane of chessboard pattern. This task has been already solved by several different approaches, but we present the novel method of the chessboard reconstruction from its incomplete image, that enables successful camera localization even if the captured chessboard plane is partially covered by an unknown object. The camera position and orientation is during the processing of the videosequence tracked with the Kalman filter that enables correct localization also in the closeup views on the pattern.

BibTex


@inproceedings{BUT76475,
  author="Marek {Šolony} and Pavel {Žák} and Vítězslav {Beran} and Michal {Španěl}",
  title="CAMERA LOCALIZATION USING INCOMPLETE CHESSBOARD PATTERN",
  annote="This paper introduces the approach for the real-time camera localization by
capturing the plane of chessboard pattern. This task has been already solved by
several different approaches, but we present the novel method of the chessboard
reconstruction from its incomplete image, that enables successful camera
localization even if the captured chessboard plane is partially covered by an
unknown object. The camera position and orientation is during the processing of
the videosequence tracked with the Kalman filter that enables correct
localization also in the closeup views on the pattern.",
  address="Institute for Systems and Technologies of Information, Control and Communication",
  booktitle="VISAPP 2011 - Proceedings of the International Conference on Computer Vision Theory and Application",
  chapter="76475",
  edition="NEUVEDEN",
  howpublished="online",
  institution="Institute for Systems and Technologies of Information, Control and Communication",
  year="2011",
  month="july",
  pages="415--418",
  publisher="Institute for Systems and Technologies of Information, Control and Communication",
  type="conference paper"
}