An infant emotion recognition system using visual and audio information

Fang, Chiung‐Yao; Ma, Chung-Wen; Chiang, Meng-Lin; Chen, Sei-Wang

doi:10.1109/iea.2017.7939223

Cited by 7 publications

(2 citation statements)

References 4 publications

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“…Numerous potential applications exist for facial recognition software in infant care, including identifying facial nerve abnormalities 49 , recognizing infants at risk for insecure attachment 50 , and detecting emotional distress 51 . This technology could benefit various settings, such as hospitals and childcare centers, where addressing infant emotional distress is crucial for health and wellbeing.…”

Section: Facial Recognition Software For the Evaluation Of Infant Emo...mentioning

confidence: 99%

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Emergence of 3D body model-based infant health evaluation: a review

Tang¹,

Lee²,

Xia³

et al. 2023

Preprint

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The accurate evaluation of infant health is paramount in ensuring optimal growth, development, and overall well-being. Traditional methods of evaluation, such as physical exams and laboratory tests, can be invasive and may not provide a detailed enough assessment of an infant's health or development. In recent years, the use of 3D body models has emerged as a promising approach for the evaluation of infant health. We examine the application of 3D body models in detecting body shape abnormalities, evaluating infant motor function using 3D body tracking technology, and utilizing facial recognition software to assess infant emotions. The benefits of these innovative approaches, including enhanced accuracy, non-invasive assessment, and cost-effectiveness, are highlighted. However, we also acknowledge the limitations of 3D body model-based evaluation, such as limited availability, potential for errors, and challenges in interpreting the data. Despite these challenges, the potential of 3D body models to transform infant health evaluations is significant. As the technology continues to evolve, its adoption in healthcare settings is expected to improve the accuracy and effectiveness of infant health assessments, ultimately contributing to better care and treatment for infants.

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Section: Facial Recognition Software For the Evaluation Of Infant Emo...mentioning

confidence: 99%

“…3). Fang et al 51 Onal Ertugrul et al 52 developed an infant action unit (AU) detector, InfantAFAR, using convolutional neural networks (Fig. 4).…”

Section: Facial Recognition Software For the Evaluation Of Infant Emo...mentioning

confidence: 99%