Abstract
Combining multiple features is an empirically validated approach in the literature, which increases the accuracy in querying. However, it entails processing intrinsic high-dimensionality of features and complicates realizing an efficient system. Two primary problems can be discussed for efficient querying: representation of images and selection of features. In this paper, a class-specific feature selection approach with a dissimilarity based representation method is proposed. The class-specific features are determined by using the representativeness and discriminativeness of features for each image class. The calculations are based on the statistics on the dissimilarity values of training images.
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Yilmaz, T., Yazici, A., Yildirim, Y. (2011). Exploiting Class-Specific Features in Multi-feature Dissimilarity Space for Efficient Querying of Images. In: Christiansen, H., De Tré, G., Yazici, A., Zadrozny, S., Andreasen, T., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 2011. Lecture Notes in Computer Science(), vol 7022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24764-4_14
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DOI: https://doi.org/10.1007/978-3-642-24764-4_14
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