Abstract
In this paper, we present an approach for the retrieval of natural scenes based on a semantic modeling step. Semantic modeling stands for the classification of local image regions into semantic classes such as grass, rocks or foliage and the subsequent summary of this information in so-called concept-occurrence vectors. Using this semantic representation, images from the scene categories coasts, rivers/lakes, forests, plains, mountains and sky/clouds are retrieved. We compare two implementations of the method quantitatively on a visually diverse database of natural scenes. In addition, the semantic modeling approach is compared to retrieval based on low-level features computed directly on the image. The experiments show that semantic modeling leads in fact to better retrieval performance.
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Vogel, J., Schiele, B. (2004). Natural Scene Retrieval Based on a Semantic Modeling Step. In: Enser, P., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A.F., Smeulders, A.W.M. (eds) Image and Video Retrieval. CIVR 2004. Lecture Notes in Computer Science, vol 3115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27814-6_27
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DOI: https://doi.org/10.1007/978-3-540-27814-6_27
Publisher Name: Springer, Berlin, Heidelberg
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