%0 Book Section
%T Interactive Visual and Semantic Image Retrieval
%A Joost Van de Weijer
%A Fahad Shahbaz Khan
%A Marc Masana
%E Angel Sappa
%E Jordi Vitria
%B Multimodal Interaction in Image and Video Applications
%D 2013
%V 48
%I Springer Berlin Heidelberg
%@ 1868-4394
%@ 978-3-642-35931-6
%F Joost Van de Weijer2013
%O CIC; 605.203; 600.048
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2284), last updated on Fri, 04 Feb 2022 13:07:50 +0100
%X 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.
%U http://refbase.cvc.uab.es/files/WKC2013.pdf
%U http://dx.doi.org/10.1007/978-3-642-35932-3_3
%P 31-35