Many models of image quality have been developed to predict the visibility of differences between pairs of still images. Various methods have been suggested for combining predictions generated for individual frames of a video sequence. To explore this issue, we have compared the objective quality predictions of three temporal pooling methods against viewer ratings of perceived video quality. The subjective data were obtained from a large group of viewers in an experiment performed by Cable Television Laboratories, Inc., that utilized extended-duration video sequences containing material of significant complexity. Objective quality measures obtained for each field of the sequences were pooled using three simple methods: histogram, Minkowski summation and exponentially-weighted Minkowski summation. The results demonstrated that, for sequence durations on the order of 1 min, the three pooling methods have similar ability to predict overall perceived video quality.