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A Statistical Framework for Mental Targets Search Using Mixture Models

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Artificial Intelligence Applications in Information and Communication Technologies

Part of the book series: Studies in Computational Intelligence ((SCI,volume 607))

Abstract

Image retrieval is usually based on specific user needs that are expressed under the form of explicit queries that lead to retrieve target images. In many cases, a given user does not possess the adequate tools and semantics to express what he/she is looking for, thus, his/her target image resides in his/her mind while he/she can visually identify it. We propose in this work, a statistical framework that enables users to start a search process and interact with the system in order to find their target “mental image”, using visual features only. Our bayesian formulation provides the possibility of searching multi target classes within the same search process. Data are modeled by a generalized inverted Dirichlet mixture that also serves to quantify the similarities between images. We run experiments including real users and we present a case study of a search process that gives promising results in terms of number of iterations needed to find the mental target classes within a given dataset.

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Acknowledgments

The completion of this research was made possible thanks to the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada

    Taoufik Bdiri

  2. Concordia Institute for Information Systems Engineering, Concordia University, Montreal, QC, Canada

    Nizar Bouguila

  3. DI, Faculté des Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada

    Djemel Ziou

Authors
  1. Taoufik Bdiri
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  2. Nizar Bouguila
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  3. Djemel Ziou
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Corresponding author

Correspondence to Taoufik Bdiri .

Editor information

Editors and Affiliations

  1. Taif University, Taif, Saudi Arabia

    Yacine Laalaoui

  2. Faculty of Engineering and Computer Science, Concordia Univ.,Concordia Institute for Information Systems Engineering, Montreal, Québec, Canada

    Nizar Bouguila

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Bdiri, T., Bouguila, N., Ziou, D. (2015). A Statistical Framework for Mental Targets Search Using Mixture Models. In: Laalaoui, Y., Bouguila, N. (eds) Artificial Intelligence Applications in Information and Communication Technologies. Studies in Computational Intelligence, vol 607. Springer, Cham. https://doi.org/10.1007/978-3-319-19833-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-19833-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19832-3

  • Online ISBN: 978-3-319-19833-0

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