Abstract
This paper describes a system to annotate and to retrieve face images in impressive words representing their visual impressions. When a face image is given, impressive words are assigned by annotation. When some impressive words are given, face images are obtained by retrieval. In order to achieve them, latent semantic spaces, association rules and decision trees are utilized, which are constructed from a set of face image descriptions. The face image is described in visual and symbolic features. Visual features are sizes and/or lengths of the face parts, symbolic features are impressive words, respectively. Two types of visual feature are defined, which are 24 places and minimum bounding rectangles. In the former, the lengths of 24 places in a face are measured. In the latter, minimum bounding rectangles of the face parts are made, and lengths between the rectangles are measured. Efficiency of annotation and retrieval are evaluated using these two types of visual feature. Experimental results using minimum bounding rectangles are better than ones using 24 places in both annotation and retrieval.
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© 2011 Springer-Verlag Berlin Heidelberg
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Ito, H., Koshimizu, H. (2011). Face Image Annotation and Retrieval in Impressive Words Using Minimum Bounding Rectangles of Face Parts. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6884. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23866-6_4
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DOI: https://doi.org/10.1007/978-3-642-23866-6_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23865-9
Online ISBN: 978-3-642-23866-6
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