A Smart Mirror for Emotion Monitoring in Home Environments

Bianco, Simone; Celona, Luigi; Ciocca, Gianluigi; Marelli, Davide; Napoletano, Paolo; Yu, Stefano; Schettini, Raimondo

doi:10.3390/s21227453

Cited by 12 publications

(4 citation statements)

References 55 publications

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“…On the one hand, currently available technologies have expanded the repertoire of ES techniques [ 113 , 114 , 115 ] offering novel possibilities; mobile devices are one such example [ 113 , 116 , 117 ]. Among others, devices that are likely to play a key role in the near future are smart mirrors [ 118 , 119 ]. Unfortunately, in most cases, researchers conducting experiments with novel devices adapted paper-and-pencil methods from classic ES sampling studies [ 114 , 117 ].…”

Section: Discussionmentioning

confidence: 99%

“…In most advanced studies, the ES procedure is extended to exploit physiologically-triggered probing and recording of participants’ self-reports and peripheral physiological activity [ 121 ]. The adoption of devices such as smart mirrors [ 118 , 119 ], beyond the privacy concerns that we shall not address here, might offer the availability of multimodal data for subsequent analysis; in addition, these more complex interaction devices seem to have potential for longitudinal studies in the field under quasi-experimentation design [ 117 ] based on interval contingent triggering (e.g., interacting with the mirror twice a day) [ 116 ]. In the case of current ES studies, ratings to be evaluated are by and large self-reported; however, as long as we have time-series, the presented methods can be suitably adapted for gauging recurrent patterns and their variability together with indicators of affective/social states, namely that crystallise the bare essentials of ES [ 121 ].…”

Section: Discussionmentioning

confidence: 99%

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Inferring Causal Factors of Core Affect Dynamics on Social Participation through the Lens of the Observer

D’Amelio

Patania

Buršić

et al. 2023

Sensors

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A core endeavour in current affective computing and social signal processing research is the construction of datasets embedding suitable ground truths to foster machine learning methods. This practice brings up hitherto overlooked intricacies. In this paper, we consider causal factors potentially arising when human raters evaluate the affect fluctuations of subjects involved in dyadic interactions and subsequently categorise them in terms of social participation traits. To gauge such factors, we propose an emulator as a statistical approximation of the human rater, and we first discuss the motivations and the rationale behind the approach.The emulator is laid down in the next section as a phenomenological model where the core affect stochastic dynamics as perceived by the rater are captured through an Ornstein–Uhlenbeck process; its parameters are then exploited to infer potential causal effects in the attribution of social traits. Following that, by resorting to a publicly available dataset, the adequacy of the model is evaluated in terms of both human raters’ emulation and machine learning predictive capabilities. We then present the results, which are followed by a general discussion concerning findings and their implications, together with advantages and potential applications of the approach.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Inferring Causal Factors of Core Affect Dynamics on Social Participation through the Lens of the Observer

D’Amelio

Patania

Buršić

et al. 2023

Sensors

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“…In [10], the author proposed a model for a smart mirror called the Smart eHealth Mirror. The mirror is designed to detect health issues by analysing the posture and body changes of the individual using a new algorithm called the Posture Analyse Algorithm (PAA).…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Approach to Smart Mirror Technology for Enhanced Elderly Health Monitoring

2023

IJSREM

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Abstract—The integration of smart mirror technology for health monitoring in elderly populations discusses the benefits and challenges of using smart mirrors as a proactive healthcare solution. The study emphasizes features such as facial recognition, posture analysis, and skin condition detection, enabling real-time data collection and personalized recommendations for preventive care. Usability, privacy concerns, and integration issues are considered. Through a review of relevant research, the paper highlights the potential of smart mirrors for proactive health monitoring in the elderly. It offers insights to researchers and healthcare professionals seeking innovative solutions for personalized care. Keywords—Smart mirror, smart assistant, health issues, elderly care, human healthcare, IoT, emotion recognition, mental monitoring

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“…Smart mirrors are devices designed to interact with users in a different way. They are often based on the Internet of Things (IoT) concept and allow users to interact with applications using touch or voice controls and to display feedback and various information [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Designing an AI-Based Virtual Try-On Web Application

Marelli

Bianco

Ciocca

2022

Sensors

Self Cite

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In the last few years, Augmented Reality, Virtual Reality, and Artificial Intelligence (AI) have been increasingly employed in different application domains. Among them, the retail market presents the opportunity to allow people to check the appearance of accessories, makeup, hairstyle, hair color, and clothes on themselves, exploiting virtual try-on applications. In this paper, we propose an eyewear virtual try-on experience based on a framework that leverages advanced deep learning-based computer vision techniques. The virtual try-on is performed on a 3D face reconstructed from a single input image. In designing our system, we started by studying the underlying architecture, components, and their interactions. Then, we assessed and compared existing face reconstruction approaches. To this end, we performed an extensive analysis and experiments for evaluating their design, complexity, geometry reconstruction errors, and reconstructed texture quality. The experiments allowed us to select the most suitable approach for our proposed try-on framework. Our system considers actual glasses and face sizes to provide a realistic fit estimation using a markerless approach. The user interacts with the system by using a web application optimized for desktop and mobile devices. Finally, we performed a usability study that showed an above-average score of our eyewear virtual try-on application.

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A Smart Mirror for Emotion Monitoring in Home Environments

Cited by 12 publications

References 55 publications

Inferring Causal Factors of Core Affect Dynamics on Social Participation through the Lens of the Observer

Inferring Causal Factors of Core Affect Dynamics on Social Participation through the Lens of the Observer

A Novel Approach to Smart Mirror Technology for Enhanced Elderly Health Monitoring

Designing an AI-Based Virtual Try-On Web Application

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