Shape Google: A computer vision approach to isometry invariant shape retrieval

Maks Ovsjanikov, Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas

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

Abstract

Feature-based methods have recently gained popularity in computer vision and pattern recognition communities, in applications such as object recognition and image retrieval. In this paper, we explore analogous approaches in the 3D world applied to the problem of non-rigid shape search and retrieval in large databases.

Original languageEnglish
Title of host publication2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
Pages320-327
Number of pages8
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 - Kyoto, Japan
Duration: 27 Sep 20094 Oct 2009

Publication series

Name2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

Conference

Conference2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
Country/TerritoryJapan
CityKyoto
Period27/09/094/10/09

Fingerprint

Dive into the research topics of 'Shape Google: A computer vision approach to isometry invariant shape retrieval'. Together they form a unique fingerprint.

Cite this