Fuzzy Conceptual Graphs for Handling Uncertainty in Semantic Video Retrieval
Résumé
Uncertainty is one of the major challenges related to the semantic gap in multimedia data description and retrieval. It is due not only to errors and imprecisions in content classifications but also to the extended range of user queries and navigation habits. In this paper, a new variant of fuzzy conceptual graphs, suitable for handling uncertainty in visual event description and retrieval, is presented. We deal with two types of graphs according to the sources of uncertainty. New variant of fuzzy spatial and temporal relationships are defined to capture imprecision in video content spatiotemporal features. Moreover, similarity measures and matching algorithms are defined to assess the degree of match between the components of video and the event model and then to localize events within video segments.