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A multi-modal approach for high-dimensional feature recognition

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Abstract

Over the past few decades, biometric recognition firmly established itself as one of the areas of tremendous potential to make scientific discovery and to advance state-of-the- art research in security domain. Hardly, there is a single area of IT left untouched by increased vulnerabilities, on-line scams, e-fraud, illegal activities, and event pranks in virtual worlds. In parallel with biometric development, which went from focus on single biometric recognition methods to multi-modal information fusion, another rising area of research is virtual world’s security and avatar recognition. This article explores links between multi-biometric system architecture and virtual worlds face recognition, and proposes methodology which can be of benefit for both applications.

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Acknowledgements

Authors of the paper would like to acknowledge support of NSERC and GEOIDE for partially sponsoring this research, as well as Biometric Technologies Laboratory at the University of Calgary. We also would like to acknowledge Prof. Roman Yampolskiy for his collaboration on avatar recognition methodology and for sharing avatar images.

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Authors and Affiliations

  1. Department of Computer Science, University of Calgary, Calgary, Canada

    Kushan Ahmadian & Marina Gavrilova

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  1. Kushan Ahmadian
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  2. Marina Gavrilova
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Correspondence to Marina Gavrilova.

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Ahmadian, K., Gavrilova, M. A multi-modal approach for high-dimensional feature recognition. Vis Comput 29, 123–130 (2013). https://doi.org/10.1007/s00371-012-0741-9

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