A neural network strategy for 3D surface registration

Heng Liu, Jingqi Yan, Dapeng Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


3D surface registration is commonly used in shape analysis, surface representation, and medical image aided surgery. This technique is extremely computationally expensive and sometimes will lead to bad result configured with unstructured mass data for its' iterative searching procedure and ill-suited distance function. In this paper, we propose a novel neural network strategy for surface registration. Before that, a typical preprocessing procedure-mesh PCA is used for coordinate direction normalization. The results and comparisons show such neural network method is a promising approach for 3D shape matching.
Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2006
Subtitle of host publicationInternational Conference, Proceedings - Part I
PublisherSpringer Verlag
Number of pages9
ISBN (Print)354034070X, 9783540340706
Publication statusPublished - 1 Jan 2006
EventICCSA 2006: International Conference on Computational Science and Its Applications - Glasgow, United Kingdom
Duration: 8 May 200611 May 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3980 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceICCSA 2006: International Conference on Computational Science and Its Applications
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'A neural network strategy for 3D surface registration'. Together they form a unique fingerprint.

Cite this