The integration of cognitive capabilities in computer vision systems requires both to
enable high semantic expressiveness and to deal with high computational costs as large
amounts of data are involved in the analysis. This contribution describes a cognitive vision system conceived to automatically provide high-level interpretations of complex real-time situations in outdoor and indoor scenarios, and to eventually maintain communication with casual end users in multiple languages. The main contributions are: (i) the design of an integrative multilevel architecture for cognitive surveillance purposes; (ii) the proposal of a coherent taxonomy of knowledge to guide the process of
interpretation, which leads to the conception of a situation-based ontology; (iii) the use of situational analysis for content detection and a progressive interpretation of semantically rich scenes, by managing incomplete or uncertain knowledge, and (iv) the use of such an
ontological background to enable multilingual capabilities and advanced end-user interfaces. Experimental results are provided to show the feasibility of the proposed approach.
CitationFernández, C. [et al.]. Interpretation of complex situations in a semantic-based surveillance framework. "Signal processing: image communication", 2008, vol. 23, núm. 7, p. 554-569.
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