Method for Efficient CPU-GPU Streaming for Walkthrough of Full Motion Lightfield Video
In this paper, we propose a scalable method for streaming lightfield video, parameterized on viewer location and time, that efficiently handles RAM-to-GPU memory transfers of lightfield video in a compressed form, utilizing the GPU architecture for reduction of latency.
December 11, 2017
European Conference on Visual Media Production (CVMP) 2017
Authors
Floyd Chitalu (University of Edinburgh)
Babis Koniaris (Disney Research)
Kenny Mitchell (Disney Research)
Method for Efficient CPU-GPU Streaming for Walkthrough of Full Motion Lightfield Video
Lightfield video, as a high-dimensional function, is very demanding in terms of storage. As such, lightfield video data, even in a compressed form, do not typically fit in GPU or main memory unless the capture area, resolution or duration is sufficiently small. Additionally, latency minimization–critical for viewer comfort in use-cases such as virtual reality–places further constraints in many compression schemes. In this paper, we propose a scalable method for streaming lightfield video, parameterized on viewer location and time, that efficiently handles RAM-to-GPU memory transfers of lightfield video in a compressed form, utilizing the GPU architecture for reduction of latency. We demonstrate the effectiveness of our method in a variety of compressed animated lightfield datasets.
