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Emotion Recognition Technologies in Human-Machine Interaction

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1968

Special Issue Editor


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Guest Editor
Institute of Automation, Chinese Academy of Sciences, Beijing, China
Interests: pattern recognition; affective computing; speech processing; human-machine interaction

Special Issue Information

Dear Colleagues,

Affective computing builds a harmonious human-computer environment by enabling the computer systems and devices to recognize, interpret, and simulate human affects. Emotion recognition is the basic part of affective computing and is effective to improve the naturalness for intelligent interaction. This kind of cooperation needs a special set of sensors or even sensor networks. Within affective science more broadly, there is an explosion of interest in realizing more natural human-computer interaction by taking affective computing into consideration. It is also important to understand of how emotion is represented in the brain and how it shapes the body in biological processes. Research to quantitatively measure emotions through the development of sensor technology and artificial intelligence has urgent requirement.

This Special Issue is addressed to all types of sensors signals analyzed for Emotion Recognition.

Dr. Bin Liu
Guest Editor

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Keywords

  • motion capture for affect recognition
  • multimodal data fusion for affect recognition
  • affective speech analysis and recognition
  • affective text processing and sentiment analysis
  • facial and body gesture recognition
  • affective recognition from alternative modalities
  • remote emotion sensing
  • affective interface
  • affective and social robotics and virtual agents

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Published Papers (1 paper)

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Research

20 pages, 8912 KiB  
Article
Implementation of Engagement Detection for Human–Robot Interaction in Complex Environments
by Sin-Ru Lu, Jia-Hsun Lo, Yi-Tian Hong and Han-Pang Huang
Sensors 2024, 24(11), 3311; https://doi.org/10.3390/s24113311 - 22 May 2024
Cited by 3 | Viewed by 1483
Abstract
This study develops a comprehensive robotic system, termed the robot cognitive system, for complex environments, integrating three models: the engagement model, the intention model, and the human–robot interaction (HRI) model. The system aims to enhance the naturalness and comfort of HRI by enabling [...] Read more.
This study develops a comprehensive robotic system, termed the robot cognitive system, for complex environments, integrating three models: the engagement model, the intention model, and the human–robot interaction (HRI) model. The system aims to enhance the naturalness and comfort of HRI by enabling robots to detect human behaviors, intentions, and emotions accurately. A novel dual-arm-hand mobile robot, Mobi, was designed to demonstrate the system’s efficacy. The engagement model utilizes eye gaze, head pose, and action recognition to determine the suitable moment for interaction initiation, addressing potential eye contact anxiety. The intention model employs sentiment analysis and emotion classification to infer the interactor’s intentions. The HRI model, integrated with Google Dialogflow, facilitates appropriate robot responses based on user feedback. The system’s performance was validated in a retail environment scenario, demonstrating its potential to improve the user experience in HRIs. Full article
(This article belongs to the Special Issue Emotion Recognition Technologies in Human-Machine Interaction)
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