Mr. Yize Jin Profile

Yize Jin

at Univ of Texas at Austin

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Proceedings Article | 21 August 2020 Presentation + Paper

Study of 2D foveated video quality in virtual reality

Yize Jin, Meixu Chen, Todd Goodall Bell, Zhaolin Wan, Alan Bovik

Proceedings Volume 11510, 1151007 (2020) https://doi.org/10.1117/12.2568883

KEYWORDS: Video, Video compression, Virtual reality, Databases, Algorithm development, Video acceleration, Eye, Image quality, Head-mounted displays

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In Virtual Reality (VR), the necessity of immersive videos leads to greater challenges in compression and communication owing to the much higher spatial resolution, rapid, and the often real-time changes in viewing direction. Foveation in displays exploits the space-variant density of the retinal photoreceptors, which decreases exponentially with increasing eccentricity, to reduce the amount of data from the visual periphery. Foveated compression is gaining relevance and popularity for Virtual Reality. Likewise, being able to predict the quality of displayed foveated and compressed content has become more important. Towards advancing the development of objective quality assessment algorithms for foveated and compressed measurements of VR video contents, we built a new VR database of foveated/compressed videos, and conducted a human study of perceptual quality on it. A foveated video player having low motion-to-photon latency (~50ms) was designed to meet the requirements of smooth playback, while an eye tracker was deployed to provide gaze direction in real time. We generated 180 distorted videos from 10 pristine 8K videos (30fps) having varying levels and combinations of foveation and compression distortions. These contents were viewed and quality-rated by 36 subjects in a controlled VR setting. Both the subject ratings and the eye tracking data are being made available along with the rest of the database.

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