PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Keyword-detection approach to automatic image annotation
Ville Viitaniemi and Jorma Laaksonen
In: 2nd European Workshop on the Integration of Knowledge, Semantic and Digital Media Technologies, 30 Nov - 01 Dec 2005, London, United Kingdom.

Abstract

In this paper we consider the problem of automatically annotating images with keywords. We first discuss performance measures for the problem in some length. We propose a new information-theory based measure -- de-symmetrised mutual information (DTMI). We then describe a straightforward solution to the annotation problem. We first train a set of classifiers to detect the presence of each individual keyword in the set of training images. For this we use the PicSOM image analysis framework. We then describe a method of converting the classifier outputs back into keyword annotations for the test set. We compare the performance of the proposed method experimentally to that of other methods presented in the literature. For the experiments we use data from the Corel database. The result of the comparison is favourable to the proposed method.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Machine Vision
Learning/Statistics & Optimisation
Information Retrieval & Textual Information Access
ID Code:1733
Deposited By:Jorma Laaksonen
Deposited On:28 November 2005