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Review of Trends in Automatic Human Activity Recognition Using Synthetic Audio-Visual Data

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Intelligent Data Engineering and Automated Learning – IDEAL 2020 (IDEAL 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12490))

Abstract

An in-depth study of knowledge and technologies was made related to the various scientific, technical, and industrial domains necessary for the acquisition of skills and capabilities for the design and development of a multisensory fusion system for vehicle cockpits. After an extensive literature review, it was possible to determine the baselines of the solution to be developed and obtain a pipeline prototype.

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Acknowledgments

This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. Human and material resources have also been supported by the European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project number 039334; Funding Reference: POCI-01-0247-FEDER-039334].

Author information

Authors and Affiliations

  1. Centre Algoritmi, University of Minho, 4710-057, Braga, Portugal

    Tiago Jesus, Júlio Duarte, Diana Ferreira, Dalila Durães, Francisco Marcondes, Flávio Santos, Marco Gomes, Paulo Novais, Nicolas Lori, António Abelha & José Machado

  2. Bosch Car Multimedia, 4705-820, Braga, Portugal

    Tiago Jesus, Júlio Duarte, Diana Ferreira, Dalila Durães, Francisco Marcondes, Flávio Santos, Marco Gomes, Paulo Novais, Filipe Gonçalves, Joaquim Fonseca, Nicolas Lori, António Abelha & José Machado

Authors
  1. Tiago Jesus
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  2. Júlio Duarte
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  3. Diana Ferreira
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  4. Dalila Durães
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  5. Francisco Marcondes
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  6. Flávio Santos
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  7. Marco Gomes
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  8. Paulo Novais
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  9. Filipe Gonçalves
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  10. Joaquim Fonseca
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  11. Nicolas Lori
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  12. António Abelha
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  13. José Machado
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Corresponding author

Correspondence to Nicolas Lori .

Editor information

Editors and Affiliations

  1. University of Minho, Braga, Portugal

    Cesar Analide

  2. University of Minho, Braga, Portugal

    Paulo Novais

  3. Technical University of Madrid, Madrid, Spain

    David Camacho

  4. University of Manchester, Manchester, UK

    Hujun Yin

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Jesus, T. et al. (2020). Review of Trends in Automatic Human Activity Recognition Using Synthetic Audio-Visual Data. In: Analide, C., Novais, P., Camacho, D., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2020. IDEAL 2020. Lecture Notes in Computer Science(), vol 12490. Springer, Cham. https://doi.org/10.1007/978-3-030-62365-4_53

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  • DOI: https://doi.org/10.1007/978-3-030-62365-4_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62364-7

  • Online ISBN: 978-3-030-62365-4

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