
doi: 10.1145/3658141
Foveated rendering takes advantage of the reduced spatial sensitivity in peripheral vision to greatly reduce rendering cost without noticeable spatial quality degradation. Due to its benefits, it has emerged as a key enabler for real-time high-quality virtual and augmented realities. Interestingly though, a large body of work advocates that a key role of peripheral vision may be motion detection, yet foveated rendering lowers the image quality in these regions, which may impact our ability to detect and quantify motion. The problem is critical for immersive simulations where the ability to detect and quantify movement drives actions and decisions. In this work, we diverge from the contemporary approach towards the goal of foveated graphics, and demonstrate that a loss of high-frequency spatial details in the periphery inhibits motion perception, leading to underestimating motion cues such as velocity. Furthermore, inspired by an interesting visual illusion, we design a perceptually motivated real-time technique that synthesizes controlled spatio-temporal motion energy to offset the loss in motion perception. Finally, we perform user experiments demonstrating our method's effectiveness in recovering motion cues without introducing objectionable quality degradation.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
