This work addresses the problem of correspondence matching in multiview video sequences when co-acquired depth maps are available, as in the novel Multiview Video plus Depth (MVD) format. For the purpose of activity-based correspondence matching, we exploit the view depth information, allowing a thorough geometrical analysis of the video scene, and the statistical analysis of the inter-frame differences. In this paper we outline a correspondence matching procedure exploiting mutual information

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... etween active areas in different sequences. For activity detection we make use of the depth information and the estimated Higher Order Statistics of the inter-frame differences, which are resilient to luminance variations. The procedure encompasses two steps, namely: i) a selection of points candidate for matching search, and ii) the search of the most similar points; this procedure does not require any preliminar activity detection or segmentation stage.