Some Experiments of Face Annotation Based on Latent Semantic Indexing in FIARS (original) (raw)

Abstract

This paper describes annotation of face images in keywords based on latent semantic indexing, and experimental results in FIARS. Two latent semantic spaces are constructed from visual and symbolic features. These features are corresponding to lengths of some places of a face and keywords. One latent semantic space is constructed from visual features, the other space is constructed from both features. The former space is used for retrieving similar face images, and the latter for seeking keywords to a given face image. Moreover, the two types of visual futures are utilized. One is specified in terms of the lengths of face parts, and the other in terms of points on the outlines of a face and its parts. As an experiment, recall and precision ratios of assigned keywords are measured using the two types of the visual features.

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Authors and Affiliations

  1. School of Information Science and Technology, Chukyo University, 101 Tokodachi, Kaizu-cho, Toyota, Aichi, 470-0393, Japan
    Hideaki Ito & Hiroyasu Koshimizu

Authors

  1. Hideaki Ito
  2. Hiroyasu Koshimizu

Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK
    Bogdan Gabrys
  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK
    Robert J. Howlett
  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia
    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Ito, H., Koshimizu, H. (2006). Some Experiments of Face Annotation Based on Latent Semantic Indexing in FIARS. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004\_153

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