ABSTRACT
The lens distortion is essential for displaying VR contents on a head-mounted display (HMD) with a distorted display surface. We propose a novel lens distortion algorithm on an embedded GPU system. To minimize the memory access overhead, we propose a compressed form of a lookup table. We also utilize the integrated memory architecture of the edge GPU system (e.g., NVIDIA’s Jetson devices) to reduce data communication overhead between host and device. As a result, our method shows up to 1.72-times higher performance than prior lookup table-based lens distortion approaches while it consumes up to 28.93% less power. Finally, our algorithm achieved real-time performance for high-resolution images on edge GPU systems (e.g., 94 FPS for 8K image on Jetson NX). These results demonstrate the benefits of our approach from the perspectives of both performance and energy.
Supplemental Material
Available for Download
- Nikolaos Bellas, Sek M Chai, Malcolm Dwyer, and Dan Linzmeier. 2009. Real-time fisheye lens distortion correction using automatically generated streaming accelerators. In 2009 17th IEEE Symposium on Field Programmable Custom Computing Machines. IEEE, 149–156.Google Scholar
Digital Library
- John Cheng, Max Grossman, and Ty McKercher. 2014. Professional CUDA C programming. John Wiley & Sons. 136–199 pages.Google Scholar
- Konstantis Daloukas, Christos D Antonopoulos, Nikolaos Bellas, and Sek M Chai. 2010. Fisheye lens distortion correction on multicore and hardware accelerator platforms. In 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS). IEEE, 1–10.Google Scholar
Cross Ref
- Shehrzad Qureshi. 2013. Computer Vision Acceleration Using GPUs. http://developer.amd.com/wordpress/media/2013/06/2162_final.pdf. AMD Developer Central, Accessed: 2021-07-08.Google Scholar
- Warren Robinett and Jannick P Rolland. 1992. A computational model for the stereoscopic optics of a head-mounted display. Presence: Teleoperators & Virtual Environments 1, 1(1992), 45–62.Google Scholar
Digital Library
- Sam Van der Jeught, Jan AN Buytaert, and Joris JJ Dirckx. 2012. Real-time geometric lens distortion correction using a graphics processing unit. Optical Engineering 51, 2 (2012), 027002.Google Scholar
Cross Ref
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