2026-07-20T05:24:47Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:3095 2024-03-06T10:28:53Z ddc:004 open_access

Detection and Identification Techniques for Markers Used in Computer Vision Köhler, Johannes Pagani, Alain Stricker, Didier Marker Identification Computer Vision 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Johannes Köhler and Alain Pagani and Didier Stricker 2011 Is Part Of OASIcs, Volume 19, Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop) (2011) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.VLUDS.2010.36 urn:nbn:de:0030-drops-30951 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.VLUDS.2010.36 eng https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode