Abstract
The continuous improvement in the delivery of advanced video services, along with evolved technical conditions at the client side, contributed to the appearance of new methods for the evaluation of quality of service (QoS) and quality of experience (QoE) from the user’s point of view. This article describes the development of a model that correlates QoS parameters and QoE factors with impact on the variation of the user’s perception of the quality. A quality assessment test was performed with 40 participants that ranked more than 140 videos. The detailed analysis of the collected data from the test allowed to conclude that all the considered factors had significant impact on the perceived quality. Those factors were aggregated in a single model using linear regression techniques to join their behavior and associate adequate weights to each factor. The results from validity tests of the model were encouraging, achieving 99 % of accuracy. This model can be considered a new no-reference metric to infer the perceived quality, applicable in many contexts, but essentially as a tool for service providers to estimate the rank customers may give to a content.
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