Direct 3D pose estimation of a planar target

Hung Yu Tseng, Po Chen Wu, Ming Hsuan Yang, Shao Yi Chien

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

6 Citations (Scopus)

Abstract

Estimating 3D pose of a known object from a given 2D image is an important problem with numerous studies for robotics and augmented reality applications. While the state-of-the-art Perspective-n-Point algorithms perform well in pose estimation, the success hinges on whether feature points can be extracted and matched correctly on targets with rich texture. In this work, we propose a robust direct method for 3D pose estimation with high accuracy that performs well on both textured and textureless planar targets. First, the pose of a planar target with respect to a calibrated camera is approximately estimated by posing it as a template matching problem. Next, the object pose is further refined and disambiguated with a gradient descent search scheme. Extensive experiments on both synthetic and real datasets demonstrate the proposed direct pose estimation algorithm performs favorably against state-of-the-art feature-based approaches in terms of robustness and accuracy under several varying conditions.

Original languageEnglish
Title of host publication2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509006410
DOIs
Publication statusPublished - 2016 May 23
EventIEEE Winter Conference on Applications of Computer Vision, WACV 2016 - Lake Placid, United States
Duration: 2016 Mar 72016 Mar 10

Publication series

Name2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016

Conference

ConferenceIEEE Winter Conference on Applications of Computer Vision, WACV 2016
CountryUnited States
CityLake Placid
Period16/3/716/3/10

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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