Abstract
One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results.
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van de Weijer, J., Khan, F., Masana, M. (2013). Interactive Visual and Semantic Image Retrieval. In: Multimodal Interaction in Image and Video Applications. Intelligent Systems Reference Library, vol 48. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35932-3_3
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DOI: https://doi.org/10.1007/978-3-642-35932-3_3
Publisher Name: Springer, Berlin, Heidelberg
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