Data fusion for photorealistic 3D models

Zsolt Jankó, D. Chetverikov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study aims at building photorealistic 3D models of real-world objects. We discuss the problem of combining a 3D textureless model obtained by 3D scanner, with optical images that provide textural information of the object. Recently, we have proposed a novel method to register an uncalibrated image pair to a 3D surface model. After registration, the images are mapped to the surface. However, as the images show different parts of the objects, partial overlapping textures can only be extracted from them. Combining the images into a complete texture map that covers the entire object is not trivial. We present a method to build photorealistic 3D models that includes algorithms for data registration and for merging multiple texture maps using surface flattening. Experimental results on real and synthetic data are shown.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages240-247
Number of pages8
Volume3691 LNCS
Publication statusPublished - 2005
Event11th International Conference on Computer Analysis of Images and Patterns, CAIP 2005 - Versailles, France
Duration: Sep 5 2005Sep 8 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3691 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other11th International Conference on Computer Analysis of Images and Patterns, CAIP 2005
CountryFrance
CityVersailles
Period9/5/059/8/05

Fingerprint

Data Fusion
Data fusion
3D Model
Textures
Texture
Registration
Merging
Synthetic Data
Scanner
Overlapping
Trivial
Entire
Cover
Partial
Object
Experimental Results

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Jankó, Z., & Chetverikov, D. (2005). Data fusion for photorealistic 3D models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3691 LNCS, pp. 240-247). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3691 LNCS).

Data fusion for photorealistic 3D models. / Jankó, Zsolt; Chetverikov, D.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3691 LNCS 2005. p. 240-247 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3691 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jankó, Z & Chetverikov, D 2005, Data fusion for photorealistic 3D models. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3691 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3691 LNCS, pp. 240-247, 11th International Conference on Computer Analysis of Images and Patterns, CAIP 2005, Versailles, France, 9/5/05.
Jankó Z, Chetverikov D. Data fusion for photorealistic 3D models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3691 LNCS. 2005. p. 240-247. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Jankó, Zsolt ; Chetverikov, D. / Data fusion for photorealistic 3D models. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3691 LNCS 2005. pp. 240-247 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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