Fuzzy Conceptual Graphs for Handling Uncertainty in Semantic Video Retrieval

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 classification but also to the extended range of user queries. In this paper, an extension 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. An extension of fuzzy spatial and temporal relationships is defined to capture imprecision in video content spatiotemporal descriptions. Moreover, similarity measures and matching algorithms are defined to assess the degree of match between the descriptions of video objects and the event model and then to detect events within video segments.