Study on Viewing Time with Regards to Quality Factors in Adaptive Bitrate Video Streaming

In this work, the evaluation of user engagement's characteristics in adaptive bitrate video streaming is addressed. To this aim, the viewing time and its relation with video quality is studied in two carefully designed subjective tests. Video quality and viewing time were addressed in distinct experiments. In case of viewing time, users were allowed to stop watching the videos when they desired. It was found that for low-quality videos, the number of users dropping the video increases logarithmically as a function of time. In addition, when a stalling event occurs, users start dropping video playback after a waiting period of 5 seconds. Then, when the stalling ends, the dropping rate returns to its baseline rate (which depends on video quality). The number of users stopping watching video after a stalling event was found to be a function of stalling position, stalling duration, and the quality affected by coding. A baseline model considering only stalling features is defined. Finally, a model for predicting the video completion rate is proposed that achieves a Pearson correlation of 0.96 and a root-mean-square error (RMSE) of 0.064.