This paper proposes a subjective model for estimating the quality of video streaming services with dynamic bit-rate control. In a subjective quality assessment test, we clarify users' perceptions of distributed video signals whose quality is time-variant due to dynamic bit-rate control. Using this result, we constructed an estimation model considering the following three characteristics: 1) the influence of the video section where quality degradation is large will strongly affect the overall quality, 2) the impression of a past quality weakens with the passage of time, and 3) the range of evaluation scores becomes wider when the time duration of an evaluation is longer. We found that the proposed model enables the accuracy of estimating overall subjective quality to be dramatically improved compared with that of a model that averages segmental quality. The estimation error of the proposed model is less than the statistical reliability of the subjective score even for verification data. We also show that our findings are applicable to QoS design/management issues for video streaming services with dynamic bit-rate control.

This paper introduces a new frame-based bit-rate control scheme for bandwidth-adaptive video coding. Proposed method can accurately adapt to the rapid varying scene characteristics by reducing the number of occurrences of the extrapolations while updating the rate-distortion model used for determine the appropriate quantization steps.