Energy efficient perceptual video quality measurement (VMAF) at scale

Ajayshyam .; Jay N. Shingala; Naveen Kumar Thangudu; Preethi Konda; Vijayakumar G. R.

doi:10.1117/12.2569106

21 August 2020 Energy efficient perceptual video quality measurement (VMAF) at scale

Ajayshyam ., Jay N. Shingala, Naveen Kumar Thangudu, Preethi Konda, Vijayakumar G. R.

Proceedings Volume 11510, Applications of Digital Image Processing XLIII; 115100G (2020) https://doi.org/10.1117/12.2569106
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Abstract

Over The Top (OTT) video industry has witnessed exponential growth in recent years with introduction of number of streaming services. Better video quality, at optimum encoding parameters like bitrates, resolutions is must to meet the demand of cost effective solution. Hence an objective and efficient method to measure the perceptual video quality is extremely vital for customer satisfaction and retention. VMAF is one such full reference quality metric which provides consistent, accurate assessment of video quality. It uses an internally trained ML based SVR model to fuse spatial and temporal quality features such as VIF (Visual Information Fidelity), ADM (or Detail Loss Metric DLM) and motion scores. We analyzed the complexity of such metrics in terms of core mathematical floating operations and number of loads and stores. In this paper, we propose replacing the existing floating point operations by optimal fixed point (integer) implementation without drop in accuracy. This is achieved by optimally selecting precision requirements at every stage of processing, which helps in efficient memory usage and improved performance. The proposed change will significantly help in VMAF’s usability for deployment at scale, application in low power devices and live streaming without compromising accuracy.

Conference Presentation

Citation Download Citation

Ajayshyam ., Jay N. Shingala, Naveen Kumar Thangudu, Preethi Konda, and Vijayakumar G. R. "Energy efficient perceptual video quality measurement (VMAF) at scale", Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115100G (21 August 2020); https://doi.org/10.1117/12.2569106

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