Learning Distance Functions for Automatic Annotation of Images

  • Josip Krapac
  • Frédéric Jurie
Conference paper

DOI: 10.1007/978-3-540-79860-6_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4918)
Cite this paper as:
Krapac J., Jurie F. (2008) Learning Distance Functions for Automatic Annotation of Images. In: Boujemaa N., Detyniecki M., Nürnberger A. (eds) Adaptive Multimedia Retrieval: Retrieval, User, and Semantics. AMR 2007. Lecture Notes in Computer Science, vol 4918. Springer, Berlin, Heidelberg

Abstract

This paper gives an overview of recent approaches towards image representation and image similarity computation for content-based image retrieval and automatic image annotation (category tagging). Additionaly, a new similarity function between an image and an object class is proposed. This similarity function combines various aspects of object class appearance through use of representative images of the class. Similarity to a representative image is determined by weighting local image similarities, where weights are learned from training image pairs, labeled “same” and “different”, using linear SVM. The proposed approach is validated on a challenging dataset where it performed favorably.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Josip Krapac
    • 1
  • Frédéric Jurie
    • 1
  1. 1.INRIA Rhône-AlpesSaint Ismier CedexFrance

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