Model matching in robot vision by subgraph isomorphism

E. K. Wong

    Research output: Contribution to journalArticlepeer-review


    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
    Issue number3
    StatePublished - Mar 1992


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

    ASJC Scopus subject areas

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


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