Frame-loss adaptive temporal pooling for video quality assessment

In this paper a frame-loss adaptive temporal pooling method for video quality assessment is proposed. Extensive subjective tests have been carried out to determine the duration of successive frames based on which steady quality judgment can be made by human observers. The resulting duration is applied to the determination of the length of Group of Frames (GOF), where a flexible algorithm is used to separate the input video into variable sized GOFs. Short-term temporal pooling is first performed for each of the GOF to get the GOF quality, where quality contribution of each frame is incorporated with the context and frame loss well taken into account. The video quality is then obtained by long-term temporal pooling of the GOF quality considering the fact that perceptual video quality is predominately determined by the worst parts of the video. Extensive experimental results have demonstrated the effectiveness of the proposed method both for regular and irregular frame loss.