Parametric Quality-Estimation Model for Adaptive-Bitrate-Streaming Services

The use of adaptive-bitrate-streaming services over networks has been increasing in recent years. The quality of adaptive-bitrate-streaming services is primarily affected by the video resolution, the audio and video bitrate, bitrate adaptation, stalling due to a lack of playout buffer, and the content length. Therefore, service providers should monitor quality in real time to confirm the normality of their services. To accurately monitor quality, a model that can be used for quality estimation should be developed. To develop such a model, we first conducted extensive subjective quality assessment tests. We then developed a model using the subjective data obtained in the tests. Finally, we verified the performance of the proposed model by applying it to unknown datasets (different from the training datasets used to develop the model) and confirmed its high quality-estimation accuracy.