Using region semantics and visual context for scene classification

In this paper we focus on scene classification and detection of high-level concepts within multimedia documents, by introducing an intermediate contextual approach as a means of exploiting the visual context of images. More specifically, we introduce and model a novel relational knowledge representation, founded on topological and semantic relations between the concepts of an image. We further develop an algorithm to address computationally efficient handling of visual context and extraction of mid-level region characteristics. Based on the proposed knowledge model, we combine the notion of visual context with region semantics, in order to exploit their efficacy in dealing with scene classification problems. Finally, initial experimental results are presented, in order to demonstrate possible applications of the proposed methodology.