3D articulated model retrieval using depth image input

Jun Yang Lin, May Fang She, Ming Han Tsai*, I. Chen Lin, Yo Chung Lau, Hsu Hang Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a novel framework to retrieve 3D articulated models from a database based on one or few depth images is presented. Existing state-of-the-arts retrieval approaches usually constrain the view points of query images or assume that the target models are rigid-body. When they are applied to retrieving articulated models, the retrieved results are substantially influenced by the model postures. In our work, we extracts the limbs and torso regions from projections and analyzes the features of local regions. The use of both global and local features can alleviate the disturbance of model postures in model retrieval. Experiments show that the proposed method can efficiently retrieve relevant models within a second, and provides higher retrieval accuracy than those of compared methods for not only rigid body 3D models but also models with articulated limbs.

Original languageEnglish
Title of host publicationComputer Vision, Imaging and Computer Graphics Theory and Applications - 13th International Joint Conference, VISIGRAPP 2018, Revised Selected Papers
EditorsDominique Bechmann, Manuela Chessa, Ana Paula Cláudio, Francisco Imai, Andreas Kerren, Paul Richard, Alexandru Telea, Alain Tremeau
PublisherSpringer Verlag
Pages25-47
Number of pages23
ISBN (Print)9783030267551
DOIs
StatePublished - 1 Jan 2019
Event13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018 - Funchal, Madeira, Portugal
Duration: 27 Jan 201829 Jan 2018

Publication series

NameCommunications in Computer and Information Science
Volume997
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018
CountryPortugal
CityFunchal, Madeira
Period27/01/1829/01/18

Keywords

  • 3D object retrieval
  • Depth image analysis
  • Shape matching

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