Rotational contour signatures for robust local surface description

Jiaqi Yang, Qian Zhang, Ke Xian, Yang Xiao, Zhiguo Cao

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

12 Scopus citations

Abstract

This paper presents a novel local surface descriptor called rotational contour signatures (RCS) for 3D rigid objects. RCS comprises several signatures that characterize the 2D contour information derived from 3D-to-2D projection of the local surface. The inspiration of our encoding technique comes from that, viewing towards an object, its contour is an effective and robust cue for representing its shape. In order to achieve a comprehensive geometry encoding, the local surface is continually rotated in a predefined local reference frame (LRF) so that multi-view information is obtained. Experiments on two publicly available datasets demonstrate the effectiveness and robustness of the proposed descriptor. Further, comparisons with five state-of-the-art descriptors show the superiority of our RCS descriptor.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages3598-3602
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - 3 Aug 2016
Externally publishedYes
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 25 Sep 201628 Sep 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Conference

Conference23rd IEEE International Conference on Image Processing, ICIP 2016
Country/TerritoryUnited States
CityPhoenix
Period25/09/1628/09/16

Keywords

  • Contour signatures
  • Local reference frame
  • Local surface descriptor
  • Rotation

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