DROPS

Document

DOI: 10.4230/OASIcs.VLUDS.2010.36

Detection and Identification Techniques for Markers Used in Computer Vision

Authors: Johannes Köhler, Alain Pagani, and Didier Stricker

Published in: OASIcs, Volume 19, Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop) (2011)

Abstract

This paper summarizes and compares techniques for detecting and identifying markers in the context of computer vision. Existing approaches either use correlation, digital or topological methods for marker identification. The comparison points out, that all marker processing algorithms which employ sophisticated digital codes perform more robust and reliable. Existing bit representation schemes for these codes and marker designs are compared with each other. In the overall context it is illustrated, why the marker processing algorithm is the best performer regarding marker occlusion and minimal detectable pattern size.

Cite as

Johannes Köhler, Alain Pagani, and Didier Stricker. Detection and Identification Techniques for Markers Used in Computer Vision. In Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop). Open Access Series in Informatics (OASIcs), Volume 19, pp. 36-44, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

Copy BibTex To Clipboard

@InProceedings{kohler_et_al:OASIcs.VLUDS.2010.36,
  author =	{K\"{o}hler, Johannes and Pagani, Alain and Stricker, Didier},
  title =	{{Detection and Identification Techniques for Markers Used in Computer Vision}},
  booktitle =	{Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop)},
  pages =	{36--44},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-29-3},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{19},
  editor =	{Middel, Ariane and Scheler, Inga and Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2010.36},
  URN =		{urn:nbn:de:0030-drops-30951},
  doi =		{10.4230/OASIcs.VLUDS.2010.36},
  annote =	{Keywords: Marker Identification, Computer Vision}
}

Document

DOI: 10.4230/OASIcs.VLUDS.2010.45

Markerless Camera Pose Estimation - An Overview

Authors: Tobias Nöll, Alain Pagani, and Didier Stricker

Published in: OASIcs, Volume 19, Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop) (2011)

Abstract

As shown by the human perception, a correct interpretation of a 3D scene on the basis of a 2D image is possible without markers. Solely by identifying natural features of different objects, their locations and orientations on the image can be identified. This allows a three dimensional interpretation of a two dimensional pictured scene. The key aspect for this interpretation is the correct estimation of the camera pose, i.e. the knowledge of the orientation and location a picture was recorded. This paper is intended to provide an overview of the usual camera pose estimation pipeline as well as to present and discuss the several classes of pose estimation algorithms.

Cite as

Tobias Nöll, Alain Pagani, and Didier Stricker. Markerless Camera Pose Estimation - An Overview. In Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop). Open Access Series in Informatics (OASIcs), Volume 19, pp. 45-54, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

Copy BibTex To Clipboard

@InProceedings{noll_et_al:OASIcs.VLUDS.2010.45,
  author =	{N\"{o}ll, Tobias and Pagani, Alain and Stricker, Didier},
  title =	{{Markerless Camera Pose Estimation - An Overview}},
  booktitle =	{Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop)},
  pages =	{45--54},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-29-3},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{19},
  editor =	{Middel, Ariane and Scheler, Inga and Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2010.45},
  URN =		{urn:nbn:de:0030-drops-30960},
  doi =		{10.4230/OASIcs.VLUDS.2010.45},
  annote =	{Keywords: Pose Estimation}
}

Search Results

Documents authored by Pagani, Alain

Detection and Identification Techniques for Markers Used in Computer Vision

Abstract

Cite as

Markerless Camera Pose Estimation - An Overview

Abstract

Cite as

Thanks for your feedback!

Could not send message