Depth-Assisted Rectification of Patches: Using RGB-D consumer devices to improve real-time keypoint matching

João Paulo Lima, Francisco Simões, Hideaki Uchiyama, Veronica Teichrieb, Eric Marchand

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

2 Citations (Scopus)

Abstract

This paper presents a method named Depth-Assisted Rectification of Patches (DARP), which exploits depth information available in RGB-D consumer devices to improve keypoint matching of perspectively distorted images. This is achieved by generating a projective rectification of a patch around the keypoint, which is normalized with respect to perspective distortions and scale. The DARP method runs in real-time and can be used with any local feature detector and descriptor. Evaluations with planar and non-planar scenes show that DARP can obtain better results than existing keypoint matching approaches in oblique poses.

Original languageEnglish
Title of host publicationVISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
Pages651-656
Number of pages6
Publication statusPublished - May 31 2013
Externally publishedYes
Event8th International Conference on Computer Vision Theory and Applications, VISAPP 2013 - Barcelona, Spain
Duration: Feb 21 2013Feb 24 2013

Publication series

NameVISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications
Volume1

Other

Other8th International Conference on Computer Vision Theory and Applications, VISAPP 2013
CountrySpain
CityBarcelona
Period2/21/132/24/13

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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