Improving adaptive frameless rendering

摘要

By eliminating the rigid sampling patterns of framed Tenderers and adapting sampling and reconstruction to spatio-temporal changes, combined with sample reprojection, adaptive frameless rendering offers significant potential to generate coherent imagery from sparse set of samples in real-time rendering systems. It capitalizes on the unique feature of ray-based rendering methods the ability to select where to render along with when to render, which is missing in traditional double buffered renderings. With its unique contribution of adaptive partial update of display it has applications in rendering, display, and imaging systems. In this work, we propose alternate data structures and modified algorithms to reduce memory consumption by more than 90%, reduce computation overheads by approximately 50%, and improve sampler response to regions of change by modifying sampling pattern and tracking temporal changes in 3D space, improving the quality of rendering.