Recognition and pose estimation of primitive shapes from depth images for spatial augmented reality

Ryo Hachiuma, Hideo Saito

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

Abstract

In this paper, we propose a method for recognition and pose estimation of primitive shapes from depth images for spatial augmented reality (SAR). To use SAR in our everyday life, technology to recognize and estimate the pose of projected objects in the room is necessary. However, it is not a simple task to recognize primitive shapes because of their low 3D feature values. Hence, we focused on the gradient of normal vector map to extract surfaces and used the information of the surfaces of each object to recognize target objects. With our method, it becomes possible to recognize and estimate the pose of target objects in various scenes. Additionally; we projected an image onto each of the surfaces of the physical objects.

Original languageEnglish
Title of host publication2016 IEEE 2nd Workshop on Everyday Virtual Reality, WEVR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages32-35
Number of pages4
ISBN (Electronic)9781509008407
DOIs
Publication statusPublished - 2017 Feb 21
Event2nd IEEE Workshop on Everyday Virtual Reality, WEVR 2016 - Greenville, United States
Duration: 2016 Mar 20 → …

Other

Other2nd IEEE Workshop on Everyday Virtual Reality, WEVR 2016
CountryUnited States
CityGreenville
Period16/3/20 → …

Keywords

  • Object recognition
  • Pose estimation
  • RGB-D camera
  • Spatial augmented reality

ASJC Scopus subject areas

  • Media Technology

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    Hachiuma, R., & Saito, H. (2017). Recognition and pose estimation of primitive shapes from depth images for spatial augmented reality. In 2016 IEEE 2nd Workshop on Everyday Virtual Reality, WEVR 2016 (pp. 32-35). [7859541] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WEVR.2016.7859541