Temporal integration of face view sequences and recognition of novel views

When faces are learned from rotating view sequences, novel views may be recognized by matching them with an integrated representation of the sequence or with individual views. An integrated-representation process should benefit from short view durations, and thus from the inclusion of views in a short temporal window, allowing the distribution of attention over the entire sequence. A view-matching process should benefit from long view durations, allowing the attention to focus on each view. In a sequential comparison task, we tested the recognition of learned and novel interpolated and extrapolated views after learning faces from rapid and slow sequences (240 ms or 960 ms for each view). We found a superiority of rapid over slow sequences, in favour of the integrated-representation hypothesis. In addition, the recognition pattern for the different viewpoints in the sequence depended on the absence or presence of extrapolated views, showing a bias of the distribution of attention.