Shape recognition and pose estimation for mobile augmented reality

Nate Hagbi, Oriel Bergig, Jihad El-Sana, Mark Billinghurst

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

51 Scopus citations

Abstract

In this paper we present Nestor, a system for real-time recognition and camera pose estimation from planar shapes. The system allows shapes that carry contextual meanings for humans to be used as Augmented Reality (AR) tracking fiducials. The user can teach the system new shapes at runtime by showing them to the camera. The learned shapes are then maintained by the system in a shape library. Nestor performs shape recognition by analyzing contour structures and generating projective invariant signatures from their concavities. The concavities are further used to extract features for pose estimation and tracking. Pose refinement is carried out by minimizing the reprojection error between sample points on each image contour and its library counterpart. Sample points are matched by evolving an active contour in real time. Our experiments show that the system provides stable and accurate registration, and runs at interactive frame rates on a Nokia N95 mobile phone.

Original languageEnglish
Title of host publicationScience and Technology Proceedings - IEEE 2009 International Symposium on Mixed and Augmented Reality, ISMAR 2009
Pages65-71
Number of pages7
DOIs
StatePublished - 1 Dec 2009
Event8th IEEE 2009 International Symposium on Mixed and Augmented Reality, ISMAR 2009 - Science and Technology - Orlando, FL, United States
Duration: 19 Oct 200922 Oct 2009

Publication series

NameScience and Technology Proceedings - IEEE 2009 International Symposium on Mixed and Augmented Reality, ISMAR 2009

Conference

Conference8th IEEE 2009 International Symposium on Mixed and Augmented Reality, ISMAR 2009 - Science and Technology
Country/TerritoryUnited States
CityOrlando, FL
Period19/10/0922/10/09

Keywords

  • 3D pose estimation
  • Free-hand sketching
  • Geometric projective invariance
  • Handheld AR
  • In-place augmented reality
  • Shape dual perception
  • Shape recognition
  • Vision-based tracking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

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