This paper addresses the problem of video summarization through an automatic selection of a single representative keyframe. The proposed solution is based on the mutual reinforcement paradigm, where a keyframe is selected thanks to its highest and most frequent similarity to the rest of considered frames. Two variations of the algorithm are explored: a first one where only frames within the same video are used (intraclip mode) and a second one where the decision also depends on the previously selected keyframes of related videos (interclip mode). These two algorithms were evaluated by a set of
professional documentalists from a broadcaster’s archive, and results concluded that the proposed techniques outperform the semi-manual solution adopted so far in the company.