A Hierarchical Multiple-View Approach to Three-Dimensional Object Recognition

Wei Chung Lin, Fong Yuan Liao, Chen Kuo Tsao, Theresa Lingutla

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


This paper proposes a hierarchical approach to solving the surface and vertex correspondence problems in multiple-view-based three-dimensional object recognition systems. The proposed scheme is a coarse-to-fine search process and a Hopfield network is employed at each stage. Compared with conventional object matching schemes, the proposed technique provides a more general and compact formulation of the problem and a solution more suitable for parallel implementation. At the coarse search stage, the surface matching scores between the input image and each object model in the database are computed through a Hopfield network and are used to select the candidates for further consideration. At the fine search stage, the object models selected from the previous stage are fed into another Hopfield network for vertex matching. The object model that has the best surface and vertex correspondences with the input image is finally singled out as the best matched model. Experimental results are reported using both synthetic and real range images to corroborate the proposed theory.

Original languageEnglish (US)
Pages (from-to)84-92
Number of pages9
JournalIEEE Transactions on Neural Networks
Issue number1
StatePublished - Jan 1991

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence


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