A GPU-based Framework for Real-time Free Viewpoint Television

• Author / Creator

  Shegeda, Kyrylo

• Thesis addresses two main problems of Free Viewpoint TV: generation of arbitrary viewpoint in real-time and its delivery to end-user. For the first problem a GPU-based algorithm capable of generating free viewpoints from a network of fixed HD video cameras was developed. We used a space-sweep algorithm to estimate depth information. The view generation sub-system uses it to render new synthetic images for an arbitrary viewpoint. We show how the computations can be divided from each other and parallelized using CUDA. The tests for publicly available Microsoft sequence are provided.

  For the second problem, we proposed an open-source browser-based Free Viewpoint Video player. The player is implemented using WebGL where rendering is performed solely on a GPU. It is completely asynchronous - data retrieval from the server and rendering do not block the browser. The player fits perfectly into the presented framework and can greatly improve scalability.

• Subjects / Keywords

  • CUDA
  • GPU-accelerated algorithms
  • Real-time Free Viewpoint Television
  • WebGL

• Graduation date

  Spring 2014

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3DX18

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.