Face and Upper-Body Emotion Recognition Using Service Robot’s Eyes in a Domestic Environment

Vithanawasam, T.M.W.; Madhusanka, B.G.D.A.

doi:10.23919/scse.2019.8842658

Cited by 8 publications

(2 citation statements)

References 2 publications

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“…The facial emotion recognition system has a wide range of applications in the fields of smart home and medical care. Functionally, it needs to be able to accurately recognize the face or emotion to reflect the correct judgment output [8,[23][24][25][26][27][28][29][30][31][32][33][34], but in the above articles, there are no systems built by integrating LabVIEW and Python. In [35][36][37][38][39][40][41][42], different recognition applications and computing methods are mentioned, such as [42] proposes CNN architecture to segregate different plant images from the sequences collected.…”

Section: Introductionmentioning

confidence: 99%

Establishing an Intelligent Emotion Analysis System for Long-Term Care Application Based on LabVIEW

et al. 2022

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In this study, the authors implemented an intelligent long-term care system based on deep learning techniques, using an AI model that can be integrated with the Lab’s Virtual Instrumentation Engineering Workbench (LabVIEW) application for sentiment analysis. The input data collected is a database of numerous facial features and environmental variables that have been processed and analyzed; the output decisions are the corresponding controls for sentiment analysis and prediction. Convolutional neural network (CNN) is used to deal with the complex process of deep learning. After the convolutional layer simplifies the processing of the image matrix, the results are computed by the fully connected layer. Furthermore, the Multilayer Perceptron (MLP) model embedded in LabVIEW is constructed for numerical transformation, analysis, and predictive control; it predicts the corresponding control of emotional and environmental variables. Moreover, LabVIEW is used to design sensor components, data displays, and control interfaces. Remote sensing and control is achieved by using LabVIEW’s built-in web publishing tools.

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Section: Introductionmentioning

confidence: 99%

Establishing an Intelligent Emotion Analysis System for Long-Term Care Application Based on LabVIEW

et al. 2022

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“…Kim et al [140], Le et al[155], Lee and Kang[156], Li et al[166], Liu et al[169], Lopez-Rincon[171], Maeda and Geshi[173], Nunes[194], Panya and Patel[199], Shi et al[225], Vithanawasam and Madhusanka[273], Wu et al[280], Zhang and Xiao[296], Zhang et al[169,297,298] BodyInthiam, Mowshowitz, and Hayashi[122], Nunes[194], Vithanawasam and Madhusanka [273], Wang et al [275] Speech Alonso-Martin et al [4], Anjum [8], Breazeal [29], Breazeal and Aryananda [30], Chastagnol [45], Chen et al [48], Devillers et al [62], Erol et al [78], Huang et al [118], Hyun et al [120], Kim et al [135], Kwon et al [151], Le and Lee [154], Li et al [166], Park et al [200], Park et al [203], Park and Sim [201], Rázuri et al [212], Song et al [228], Tahon et al [245], Zhu and Ahmad [302] Brain feedback Schaaff and Schultz [220], Su et al [240], Tsuchiya et al [266], Val-Calvo et al [268] Thermal imaging e.g., based on facial cutaneous temperature Abd et al [1] Biofeedback Kurono et al [149], Rani and Sarkar [210], Sugaya [241], Yang et al [288] Multimodal information Bien et al [26], Castillo et al [41], Cid et al [52], Keshari and Palaniswamy [134], Wu and Zheng [281], Yu and Tapus [292]Online audio-visual emotion recognition Kansizoglou et al[132] …”

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confidence: 99%

Survey of Emotions in Human–Robot Interactions: Perspectives from Robotic Psychology on 20 Years of Research

Stock‐Homburg

2021

Int J of Soc Robotics

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Knowledge production within the interdisciplinary field of human–robot interaction (HRI) with social robots has accelerated, despite the continued fragmentation of the research domain. Together, these features make it hard to remain at the forefront of research or assess the collective evidence pertaining to specific areas, such as the role of emotions in HRI. This systematic review of state-of-the-art research into humans’ recognition and responses to artificial emotions of social robots during HRI encompasses the years 2000–2020. In accordance with a stimulus–organism–response framework, the review advances robotic psychology by revealing current knowledge about (1) the generation of artificial robotic emotions (stimulus), (2) human recognition of robotic artificial emotions (organism), and (3) human responses to robotic emotions (response), as well as (4) other contingencies that affect emotions as moderators.

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A Software Package for Monitoring Human Emotional Reactions and Cognitive Activity by Analyzing Biomedical Signals

Sidorov

Bodrina

2020

Software Engineering Perspectives in Intelligent Systems

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Face and Upper-Body Emotion Recognition Using Service Robot’s Eyes in a Domestic Environment

Cited by 8 publications

References 2 publications

Establishing an Intelligent Emotion Analysis System for Long-Term Care Application Based on LabVIEW

Establishing an Intelligent Emotion Analysis System for Long-Term Care Application Based on LabVIEW

Survey of Emotions in Human–Robot Interactions: Perspectives from Robotic Psychology on 20 Years of Research

A Software Package for Monitoring Human Emotional Reactions and Cognitive Activity by Analyzing Biomedical Signals

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