research-article

Sensing Micro-Motion Human Patterns using Multimodal mmRadar and Video Signal for Affective and Psychological Intelligence

Authors:

Zhenan SunAuthors Info & Claims

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

Pages 5935 - 5946

https://doi.org/10.1145/3581783.3611754

Published: 27 October 2023 Publication History

Abstract

Affective and psychological perception are pivotal in human-machine interaction and essential domains within artificial intelligence. Existing physiological signal-based affective and psychological datasets primarily rely on contact-based sensors, potentially introducing extraneous affectives during the measurement process. Consequently, creating accurate non-contact affective and psychological perception datasets is crucial for overcoming these limitations and advancing affective intelligence. In this paper, we introduce the Remote Multimodal Affective and Psychological (ReMAP) dataset, for the first time, apply head micro-tremor (HMT) signals for affective and psychological perception. ReMAP features 68 participants and comprises two sub-datasets. The stimuli videos utilized for affective perception undergo rigorous screening to ensure the efficacy and universality of affective elicitation. Additionally, we propose a novel remote affective and psychological perception framework, leveraging multimodal complementarity and interrelationships to enhance affective and psychological perception capabilities. Extensive experiments demonstrate HMT as a "small yet powerful" physiological signal in psychological perception. Our method outperforms existing state-of-the-art approaches in remote affective recognition and psychological perception. The ReMAP dataset is publicly accessible at https://remap-dataset.github.io/ReMAP.

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Cited By

Bian SLiu MZhou BLukowicz PMagno M(2024)Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435558:1(1-49)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643555

Index Terms

Sensing Micro-Motion Human Patterns using Multimodal mmRadar and Video Signal for Affective and Psychological Intelligence
1. Computing methodologies
  1. Artificial intelligence
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods

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cover image ACM Conferences

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

October 2023

9913 pages

ISBN:9798400701085

DOI:10.1145/3581783

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada & MBZUAI, UAE
,
Tao Mei
HiDream.ai, China
,
Rita Cucchiara
University of Modena and Reggio Emilia, Italy
,
Program Chairs:
Marco Bertini
University of Florence, Italy
,
Diana Patricia Tobon Vallejo
Unversidad de Medellin, Colombia
,
Pradeep K. Atrey
University at Albany, State University of New York, USA
,
M. Shamim Hossain
M. Shamim Hossain (King Saud University, KSA

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Published: 27 October 2023

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Beijing Nova Program
Natural Science Foundation of China
National Key R&D Program of China
China Postdoctoral Science Foundation

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MM '23: The 31st ACM International Conference on Multimedia

October 29 - November 3, 2023

Ottawa ON, Canada

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Cited By

Bian SLiu MZhou BLukowicz PMagno M(2024)Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435558:1(1-49)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643555

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