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Emotion Recognition in Video Streams Using Intramodal and Intermodal Attention Mechanisms

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Advances in Visual Computing (ISVC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13599))

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Abstract

Automatic emotion recognition from video streams is an essential challenge for various applications including human behavior understanding, mental disease diagnosis, surveillance, or human-machine interaction. In this paper we introduce a novel, completely automatic, multimodal emotion recognition framework based on audio and visual fusion of information designed to leverage the mutually complementary nature of features while maintaining the modality-distinctive information. Specifically, we integrate the spatial, channel and temporal attention into the visual processing pipeline and the temporal self-attention into the audio branch. Then, a multimodal cross-attention fusion strategy is introduced that effectively exploits the relationship between the audio and video features. The experimental evaluation performed on RAVDESS, a publicly available database, validates the proposed approach with average accuracy scores superior to 87.85%. When compared with the state-of the art methods the proposed framework returns accuracy gains of more than 1.85%.

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Acknowledgement

This work has been carried out within the framework of the joint lab AITV (Artificial Intelligence for Television) established between Télécom SudParis and France Télévisions.

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI – UEFISCDI, project number PN-III-P1–1.1-TE-2021–0393, within PNCDI III.

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Authors and Affiliations

  1. ARTEMIS Department, Institut Polytechnique de Paris, Télécom SudParis, 9 Rue Charles Fourier, 91000, Evry, France

    Ruxandra Tapu

  2. Department of Telecommunications, Faculty of ETTI, University “Politehnica” of Bucharest, Bucharest, Romania

    Bogdan Mocanu & Ruxandra Tapu

Authors
  1. Bogdan Mocanu
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  2. Ruxandra Tapu
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Corresponding author

Correspondence to Ruxandra Tapu .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. University of Illinois Urbana-Champaign, Urbana, IL, USA

    Bo Li

  3. National University of Singapore, Singapore, Singapore

    Angela Yao

  4. Microsoft Research Asia, Beijing, China

    Yang Liu

  5. University of Missouri, Columbia, MO, USA

    Ye Duan

  6. City University of Hong Kong, Kowloon, Hong Kong

    Manfred Lau

  7. Idaho National Laboratory, Idaho Falls, ID, USA

    Rajiv Khadka

  8. Salesforce, Seattle, WA, USA

    Ana Crisan

  9. Tufts University, Medford, MA, USA

    Remco Chang

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Mocanu, B., Tapu, R. (2022). Emotion Recognition in Video Streams Using Intramodal and Intermodal Attention Mechanisms. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2022. Lecture Notes in Computer Science, vol 13599. Springer, Cham. https://doi.org/10.1007/978-3-031-20716-7_23

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  • DOI: https://doi.org/10.1007/978-3-031-20716-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20715-0

  • Online ISBN: 978-3-031-20716-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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