Texture-less planar object detection and pose estimation using Depth-Assisted Rectification of Contours

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

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

7 Citations (Scopus)

Abstract

This paper presents a method named Depth-Assisted Rectification of Contours (DARC) for detection and pose estimation of texture-less planar objects using RGB-D cameras. It consists in matching contours extracted from the current image to previously acquired template contours. In order to achieve invariance to rotation, scale and perspective distortions, a rectified representation of the contours is obtained using the available depth information. DARC requires only a single RGB-D image of the planar objects in order to estimate their pose, opposed to some existing approaches that need to capture a number of views of the target object. It also does not require to generate warped versions of the templates, which is commonly needed by existing object detection techniques. It is shown that the DARC method runs in real-time and its detection and pose estimation quality are suitable for augmented reality applications.

Original languageEnglish
Title of host publicationISMAR 2012 - 11th IEEE International Symposium on Mixed and Augmented Reality 2012, Science and Technology Papers
Pages297-298
Number of pages2
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event11th IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2012 - Atlanta, GA, United States
Duration: Nov 5 2012Nov 8 2012

Publication series

NameISMAR 2012 - 11th IEEE International Symposium on Mixed and Augmented Reality 2012, Science and Technology Papers

Other

Other11th IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2012
CountryUnited States
CityAtlanta, GA
Period11/5/1211/8/12

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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