Camera pose estimation for mixed and diminished reality in FTV

Hideo Saito, Toshihiro Honda, Yusuke Nakayama, Francois De Sorbier

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

3 Citations (Scopus)

Abstract

In this paper, we will present methods for camera pose estimation for mixed and diminished reality visualization in FTV application. We first present Viewpoint Generative Learning (VGL) based on 3D scene model reconstructed using multiple cameras including RGB-D camera. In VGL, a database of feature descriptors is generated for the 3D scene model to make the pose estimation robust to viewpoint change. Then we introduce an application of VGL to diminished reality. We also present our novel line feature descriptor, LEHF, which is also be applied to a line-based SLAM and improving camera pose estimation.

Original languageEnglish
Title of host publication3DTV-Conference
Subtitle of host publicationThe True Vision - Capture, Transmission and Display of 3D Video, 3DTV-CON 2014
PublisherIEEE Computer Society
ISBN (Print)9781479947584
DOIs
Publication statusPublished - 2014
Event3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video, 3DTV-CON 2014 - Budapest, Hungary
Duration: 2014 Jul 22014 Jul 4

Publication series

Name3DTV-Conference
ISSN (Print)2161-2021
ISSN (Electronic)2161-203X

Other

Other3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video, 3DTV-CON 2014
CountryHungary
CityBudapest
Period14/7/214/7/4

Keywords

  • augmented reality
  • camera calibration
  • feature descriptor
  • free viewpoint image synthesis
  • see-through vision

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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  • Cite this

    Saito, H., Honda, T., Nakayama, Y., & De Sorbier, F. (2014). Camera pose estimation for mixed and diminished reality in FTV. In 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video, 3DTV-CON 2014 [6874756] (3DTV-Conference). IEEE Computer Society. https://doi.org/10.1109/3DTV.2014.6874756