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Proxemics-Net: Automatic Proxemics Recognition in Images

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Pattern Recognition and Image Analysis (IbPRIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14062))

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Abstract

Proxemics is a branch of anthropology that studies how humans use personal space as a means of nonverbal communication; that is, it studies how people interact. Due to the presence of physical contact between people, in the problem of proxemics recognition in images, we have to deal with occlusions and ambiguities, which complicates the process of recognition. Several papers have proposed different methods and models to solve this problem in recent years. Over the last few years, the rapid advancement of powerful Deep Learning techniques has resulted in novel methods and approaches. So, we propose Proxemics-Net, a new model that allows us to study the performance of two state-of-the-art deep learning architectures, ConvNeXt and Visual Transformers (as backbones) on the problem of classifying different types of proxemics on still images. Experiments on the existing Proxemics dataset show that these deep learning models do help favorably in the problem of proxemics recognition since we considerably outperformed the existing state of the art, with the ConvNeXt architecture being the best-performing backbone.

Supported by the MCIN Project TED2021-129151B-I00/AEI/10.13039/ 501100011033/European Union NextGenerationEU/PRTR, and project PID2019-103871GB-I00 of the Spanish Ministry of Economy, Industry and Competitiveness, FEDER.

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Authors and Affiliations

  1. Department Computing and Numerical Analysis, University of Córdoba, Córdoba, Spain

    Isabel Jiménez-Velasco, Rafael Muñoz-Salinas & Manuel J. Marín-Jiménez

  2. Maimonides Institute for Biomedical Research of Córdoba (IMIBIC), Córdoba, Spain

    Rafael Muñoz-Salinas & Manuel J. Marín-Jiménez

Authors
  1. Isabel Jiménez-Velasco
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  2. Rafael Muñoz-Salinas
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  3. Manuel J. Marín-Jiménez
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Corresponding author

Correspondence to Isabel Jiménez-Velasco .

Editor information

Editors and Affiliations

  1. University of Alicante, Alicante, Spain

    Antonio Pertusa

  2. University of Alicante, Alicante, Spain

    Antonio Javier Gallego

  3. Universitat Politècnica de València, Valencia, Spain

    Joan Andreu Sánchez

  4. IPO Porto, Coimbra, Portugal

    Inês Domingues

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Jiménez-Velasco, I., Muñoz-Salinas, R., Marín-Jiménez, M.J. (2023). Proxemics-Net: Automatic Proxemics Recognition in Images. In: Pertusa, A., Gallego, A.J., Sánchez, J.A., Domingues, I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2023. Lecture Notes in Computer Science, vol 14062. Springer, Cham. https://doi.org/10.1007/978-3-031-36616-1_32

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  • DOI: https://doi.org/10.1007/978-3-031-36616-1_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36615-4

  • Online ISBN: 978-3-031-36616-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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