Abstract
The concept of using multiple deep images, under a variety of different names, has been explored as a possible acceleration approach for finding ray-geometry intersections. We leverage recent advances in deep image processing from order independent transparency for fast building of a compound deep image (CDI) using a coherent memory format well suited for raycasting. We explore the use of a CDI and raycasting for the problem of determining distance between virtual point lights (VPLs) and geometry for indirect lighting, with the key raycasting step being a small fraction of total frametime.
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Jesse Archer is a Ph.D. student at RMIT University, Melbourne. His research interests are real-time computer graphics and GPU computing. He completed his Bachelor of Computer Science degree in 2008, Bachelor of IT (Games and Graphics Programming) degree in 2010, and Honours in Computer Science in 2015 at RMIT.
Geoff Leach is a lecturer in the School of Science at RMIT University. His major research interests include computer graphics, computational science, and GPU computing. He teaches mostly computer graphics, and has been using OpenGL since version 1.1. He holds a M.App.Sci. degree from RMIT.
Pyarelal Knowles is a senior software engineer at nVidia. He completed his Ph.D. degree in computer science at RMIT University in 2015, and has research interests in real-time computer graphics and a background in games programming.
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Archer, J., Leach, G. & Knowles, P. Fast raycasting using a compound deep image for virtual point light range determination. Comp. Visual Media 5, 257–265 (2019). https://doi.org/10.1007/s41095-019-0144-1
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DOI: https://doi.org/10.1007/s41095-019-0144-1