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Smart environment architecture for robust people detection by infrared and visible video fusion

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Abstract

Smart people detection systems are nowadays using heterogeneous cameras. This paper proposes an architecture which is focused on robustly detecting people by infrared and visible video fusion in smart environment. The architecture covers all levels provided by the INT\(^3\)-Horus framework, initially designed to perform monitoring and activity interpretation tasks. Indeed, INT\(^3\)-Horus is used as the development environment where the approach starts with image segmentation in both infrared and visible spectra. Then, the results are fused to enhance the overall detection performance. The paper describes in detail the INT\(^3\)-Horus levels selected to implement the new architecture. These are the acquisition, segmentation, fusion, identification and Tracking levels.

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Acknowledgements

This work was partially supported by Spanish Ministerio de Economía y Competitividad / FEDER under TIN2013-47074-C2-1-R and DPI2016-80894-R grants.

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Authors and Affiliations

  1. Universidad Carlos III de Madrid, RoboticsLab, 28911, Leganés, Madrid, Spain

    José Carlos Castillo

  2. Universidad de Castilla-La Mancha, Escuela de Ingenieros Industriales, 02071, Albacete, Spain

    Antonio Fernández-Caballero

  3. Tecon Soluciones Informáticas, Calle Arcángel San Gabriel, 7, 02002, Albacete, Spain

    Juan Serrano-Cuerda

  4. Universidad de Castilla-La Mancha, Escuela Superior de Ingeniería Informática, 02071, Albacete, Spain

    María T. López

  5. Universidad de Castilla-La Mancha, Instituto de Tecnologías Audiovisuales, 13071, Albacete, Cuenca, Spain

    Arturo Martínez-Rodrigo

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  1. José Carlos Castillo
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Correspondence to Antonio Fernández-Caballero.

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Castillo, J.C., Fernández-Caballero, A., Serrano-Cuerda, J. et al. Smart environment architecture for robust people detection by infrared and visible video fusion. J Ambient Intell Human Comput 8, 223–237 (2017). https://doi.org/10.1007/s12652-016-0429-5

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