View Synthesis from multi-view RGB data using multilayered representation and volumetric estimation

Zhaoqi Su, Tiansong Zhou, Kun Li, David Brady, Yebin Liu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Background: Aiming at free-view exploration of complicated scenes, this paper presents a method for interpolating views among multi RGB cameras. Methods: In this study, we combine the idea of cost volume, which represent 3D information, and 2D semantic segmentation of the scene, to accomplish view synthesis of complicated scenes. We use the idea of cost volume to estimate the depth and confidence map of the scene, and use a multi-layer representation and resolution of the data to optimize the view synthesis of the main object. Results: /Conclusions By applying different treatment methods on different layers of the volume, we can handle complicated scenes containing multiple persons and plentiful occlusions. We also propose the view-interpolation→multi-view reconstruction→view interpolation pipeline to iteratively optimize the result. We test our method on varying data of multi-view scenes and generate decent results.

Original languageEnglish (US)
Pages (from-to)43-55
Number of pages13
JournalVirtual Reality and Intelligent Hardware
Volume2
Issue number1
DOIs
StatePublished - Feb 2020
Externally publishedYes

Keywords

  • Cost volume
  • Iterative optimization
  • Multi-layer processing
  • Multi-view reconstruction
  • View interpolation

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction

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