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Optimization of lateral interaction in accumulative computation on GPU-based platform

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Abstract

The lateral interaction in accumulative computation (LIAC) algorithm is a biologically inspired method that allows us to detect moving objects from image sequences acquired from fixed surveillance cameras. This method achieves excellent precision but requires a high processing time. Sequential implementation is too slow and cannot achieve real-time processing. In this paper, we present several improvements to the LIAC algorithm that increase its efficiency in terms of execution time and energy consumption. In particular, a GPU-based implementation delivers the same precision and is notably faster and more energy efficient than the sequential implementation.

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Acknowledgements

This work was partially supported by Spanish Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación (AEI) / European Regional Development Fund (FEDER, UE) under DPI2016-80894-R and TIN2015-66972-C5-2-R grants.

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Authors and Affiliations

  1. Departamento de Sistemas Informáticos, Universidad de Castilla-La Mancha, Campus Universitario s/n, 02071, Albacete, Spain

    Aurelio Bermúdez, Francisco Montero, María T. López, Antonio Fernández-Caballero & José L. Sánchez

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  1. Aurelio Bermúdez
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  2. Francisco Montero
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  3. María T. López
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  4. Antonio Fernández-Caballero
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  5. José L. Sánchez
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Correspondence to José L. Sánchez.

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Bermúdez, A., Montero, F., López, M.T. et al. Optimization of lateral interaction in accumulative computation on GPU-based platform. J Supercomput 75, 1670–1685 (2019). https://doi.org/10.1007/s11227-018-02736-y

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  • DOI: https://doi.org/10.1007/s11227-018-02736-y

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