Model matching in robot vision by subgraph isomorphism

E. K. Wong

    Research output: Contribution to journalArticle

    Abstract

    In this paper, we describe a systematic method for three-dimensional (3D) model matching in robot vision by using subgraph matching techniques. 3D objects are modeled as attributed graphs, called model graphs, where the nodes correspond to object vertices and the branches correspond to object edges. The 2D projections of a 3D object are modeled as subgraph isomorphisms of the object's model graph. Recognition is done by searching whether a 2D projection graph, constructed from the 2D projection of a 3D object, is a subgraph isomorphism of the object's model graph.

    Original languageEnglish (US)
    Pages (from-to)287-303
    Number of pages17
    JournalPattern Recognition
    Volume25
    Issue number3
    DOIs
    StatePublished - Mar 1992

      Fingerprint

    Keywords

    • Attributed graphs
    • Camera transform
    • Junction types
    • Recognition
    • Subgraph matching

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Computer Vision and Pattern Recognition
    • Artificial Intelligence

    Cite this