Data Driven 2-D-To-3-D Video Conversion for Soccer

Kiana Calagari, Mohamed Elgharib, Piotr Didyk, Alexandre Kaspar, Wojciech Matusik, Mohamed Hefeeda

Research output: Contribution to journalArticle

2 Citations (Scopus)


A wide adoption of 3-D videos is hindered by the lack of high-quality 3-D content. One promising solution to this problem is through data-driven 2-D-To-3-D video conversion. Such approaches are based on learning depth maps from a large dataset of 2-D+Depth images. However, current conversion methods, while general, produce low-quality results with artifacts that are not acceptable to many viewers. We propose a novel, data-driven method for 2-D-To-3-D video conversion. Our method transfers the depth gradients from a large database of 2-D+Depth images. Capturing 2-D+Depth databases, however, are complex and costly, especially for outdoor sports games. We address this problem by creating a synthetic database from computer games and showing that this synthetic database can effectively be used to convert real videos. We propose a spatio-Temporal method to ensure the smoothness of the generated depth within individual frames and across successive frames. In addition, we present an object boundary detection method customized for 2-D-To-3-D conversion systems, which produces clear depth boundaries for players. We implement our method and validate it by conducting user studies that evaluate depth perception and visual comfort of the converted 3-D videos. We show that our method produces high-quality 3-D videos that are almost indistinguishable from videos shot by stereo cameras. In addition, our method significantly outperforms the current state-of-The-Art methods. For example, up to 20% improvement in the perceived depth is achieved by our method, which translates to improving the mean opinion score from good to excellent.

Original languageEnglish
Pages (from-to)605-619
Number of pages15
JournalIEEE Transactions on Multimedia
Issue number3
Publication statusPublished - 1 Mar 2018



  • 2-D-To-3-D conversion
  • depth estimation
  • three-dimensional (3-D) video

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Calagari, K., Elgharib, M., Didyk, P., Kaspar, A., Matusik, W., & Hefeeda, M. (2018). Data Driven 2-D-To-3-D Video Conversion for Soccer. IEEE Transactions on Multimedia, 20(3), 605-619.