PREDICTING AN AVERAGE END-USER’S EXPERIENCE OF VIDEO PLAYBACK

Abstract

The end-user experience of a given platform or product with respect to video performance is an increasingly important aspect for engineers and product planners to understand. Testing real world situations in an objective and repeatable fashion is complex. The video Gross Error Detector (GED) provides a quick and cost-efficient way to evaluate video and predict an average end-user’s perception of video smoothness. The video GED allows an automated, quantitative, and reliable measurement of the number of large errors; such as dropped, repeated, or out of sequence frames that may be present in the video program. These errors can be mapped to end-user subjective ratings to estimate perceptibility and annoyance associated with playback errors. The video GED can be used to monitor errors in video for quality control, benchmark video processing and algorithms, and can be rooted into the video processing system to optimize algorithms and limit settings. 1