TECHNIQUES FOR PREDICTING PERCEPTUAL VIDEO QUALITY

摘要

In one embodiment of the present invention, a quality trainer and quality calculator collaborate to establish a consistent perceptual quality metric via machine learning. In a training phase, the quality trainer leverages machine intelligence techniques to create a perceptual quality model that combines objective metrics to optimally track a subjective metric assigned during viewings of training videos. Subsequently, the quality calculator applies the perceptual quality model to values for the objective metrics for a target video, thereby generating a perceptual quality score for the target video. In this fashion, the perceptual quality model judiciously fuses the objective metrics for the target video based on the visual feedback processed during the training phase. Since the contribution of each objective metric to the perceptual quality score is determined based on empirical data, the perceptual quality score is a more accurate assessment of observed video quality than conventional objective metrics.

主权项

1. A computer-implemented method for estimating perceptual video quality, the method comprising:
selecting a set of objective metrics that represent a plurality of deterministic video characteristics; for each training video included in a set of training videos, receiving a data set that describes the training video, wherein the data set includes a subjective value for a perceptual video quality metric and a set of objective values for the set of objective metrics; from the data sets, deriving a composite relationship that determines a value for the perceptual video quality metric based on a set of values for the set of objective metrics; for a target video, calculating a first set of values for the set of objective metrics; and applying the composite relationship to the first set of values to generate an output value for the perceptual video quality metric.