Quality variations of different priority-based temporal video adaptation algorithms

If videos are streamed over heterogeneous networks like the Internet, severe bandwidth fluctuations can emerge which hamper the seamless transmission to the end user. To overcome this issue, a video´s quality and, as a consequence, its bandwidth requirements can be reduced. Quality reduction in the temporal domain (i.e., frame dropping) turned out to be a promising approach because it is fast and easy to perform. In this paper, we present different approaches for temporal video adaptation and we investigate their performance in terms of the achieved visual quality when applied on several videos. The results show that our QCTVA approach (quality controlled temporal video adaptation), based on PSNR evaluation of frames, yields superior quality.