A Completely Blind Video Integrity Oracle

TLDR

Progress has been made on reference‑free still‑image quality analyzers, but no completely blind video quality assessment models exist. The authors develop a new reference‑free VQA model, the video intrinsic integrity and distortion evaluation oracle (VIIDEO). VIIDEO predicts video quality using only intrinsic statistical regularities of natural videos, without any external reference, distortion model, or human judgments. VIIDEO outperforms the full‑reference MSE metric on the LIVE VQA database and matches the performance of leading human‑judgment‑trained blind VQA models, indicating its potential for real‑time monitoring.

Abstract

Considerable progress has been made toward developing still picture perceptual quality analyzers that do not require any reference picture and that are not trained on human opinion scores of distorted images. However, there do not yet exist any such completely blind video quality assessment (VQA) models. Here, we attempt to bridge this gap by developing a new VQA model called the video intrinsic integrity and distortion evaluation oracle (VIIDEO). The new model does not require the use of any additional information other than the video being quality evaluated. VIIDEO embodies models of intrinsic statistical regularities that are observed in natural vidoes, which are used to quantify disturbances introduced due to distortions. An algorithm derived from the VIIDEO model is thereby able to predict the quality of distorted videos without any external knowledge about the pristine source, anticipated distortions, or human judgments of video quality. Even with such a paucity of information, we are able to show that the VIIDEO algorithm performs much better than the legacy full reference quality measure MSE on the LIVE VQA database and delivers performance comparable with a leading human judgment trained blind VQA model. We believe that the VIIDEO algorithm is a significant step toward making real-time monitoring of completely blind video quality possible.