Using Classification for Video Quality Evaluation

This paper presents a methodology for monitoring quality of service in multimedia networks. The proposal consists in the use of a simple and generic classification algorithm that enables classify the quality of a given video. The main purpose is to objectively classify video quality according to the ITU-T continuous scale, faithfully with human judgment on video quality. The challenge is to create a video quality monitoring tool (VQMT) classifying the video quality directly from the available video quality metrics, by matching the quality level of a given video to a class of video quality among the 5 considered video quality classes (Excellent, Good, Fair, Poor and Bad). Promising results are obtained using a k-NN classification tool trained on a dataset of a subjective experience along with fundamental measurable metrics, namely packet loss rate, peak signal to noise ratio, spatial indexes and temporal indexes. A statistical analysis is provided comparing this solution's performance with data-sets obtained through subjective human rating.