Graph-Based Shape Similarity of Petroglyphs View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Markus Seidl , Ewald Wieser , Matthias Zeppelzauer , Axel Pinz , Christian Breiteneder

ABSTRACT

Petroglyphs can be found on rock panels all over the world. The possibilities of digital photography and more recently various 3D scanning methods opened a new stage for the documentation and analysis of petroglyphs. The existing work on petroglyph shape similarity has largely avoided the questions of articulation, merged petroglyphs and potentially missing parts of petroglyphs. We aim at contributing to close this gap by applying a novel petroglyph shape descriptor based on the skeletal graph. Our contribution is twofold: First, we provide a real-world dataset of petroglyph shapes. Second, we propose a graph-based shape descriptor for petroglyphs. Comprehensive evaluations show, that the combination of the proposed descriptor with existing ones improves the performance in petroglyph shape similarity modeling. More... »

PAGES

133-148

References to SciGraph publications

  • 1999-11. Shock Graphs and Shape Matching in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2008. A New Accumulator-Based Approach to Shape Recognition in ADVANCES IN VISUAL COMPUTING
  • 2013. A Novel Software Toolkit for Graph Edit Distance Computation in GRAPH-BASED REPRESENTATIONS IN PATTERN RECOGNITION
  • 2011-07. An efficient and effective similarity measure to enable data mining of petroglyphs in DATA MINING AND KNOWLEDGE DISCOVERY
  • 2010. Skeleton Graph Matching Based on Critical Points Using Path Similarity in COMPUTER VISION – ACCV 2009
  • 2013. Combining Unsupervised Clustering with a Non-linear Deformation Model for Efficient Petroglyph Recognition in ADVANCES IN VISUAL COMPUTING
  • Book

    TITLE

    Computer Vision - ECCV 2014 Workshops

    ISBN

    978-3-319-16177-8
    978-3-319-16178-5

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-16178-5_9

    DOI

    http://dx.doi.org/10.1007/978-3-319-16178-5_9

    DIMENSIONS

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