SO dynamic deformation for building of 3-D models

Sei Wang Chen*, George C. Stockman, Kuo En Chang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Three-dimensional (3-D) modeling based on an ensemble of multilayer self-organizing (SO) neural networks is described. Our objective for 3-D modeling is to construct a representation of a 3-D object shape from sensed surface points acquired from the object. Current modeling techniques can be classified into two categories: the static and the dynamic approaches, the former grounded in computational geometry, and the latter rooted in the mechanics of elastic materials. In this paper, a neural-based dynamic modeling approach is presented. The method used is proved to converge and experimental results are shown which support its applicability to real problems.

Original languageEnglish
Pages (from-to)374-387
Number of pages14
JournalIEEE Transactions on Neural Networks
Issue number2
Publication statusPublished - 1996

ASJC Scopus subject areas

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


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