Light-Field DVR on GPU for Streaming Time-Varying Data

Abstract

Direct Volume Rendering (DVR) of volume data can be a memory intensive task in terms of footprint and cache-coherency. Rayguided methods may not be the best option to interactively render to light-fields due to feedback loops and sporadic sampling, and pre-computation can rule out time-varying data. We present a pipelined approach to schedule the rendering of sub-regions of streaming time-varying volume data while minimising intermediate sub-buffers needed, sharing the work load between CPU and GPU. We show there is significant advantage to using such an approach.