Deep Learning-based Multimodal Emotion Recognition Technologies, 3D Motion and Multisensory Object Representation Tools, and Visual Matching and Image Processing Algorithms for Idealized Beauty Standards and Social Media-related Body Dissatisfaction
Deep Learning-based Multimodal Emotion Recognition Technologies, 3D Motion and Multisensory Object Representation Tools, and Visual Matching and Image Processing Algorithms for Idealized Beauty Standards and Social Media-related Body Dissatisfaction

Summary/Abstract: Despite the relevance of augmented reality-based virtual try-on experiences with regard to idealized beauty standards, social media-related body dissatisfaction, and visual and haptic imagery, only limited research has been conducted on this topic. Throughout May 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “idealized beauty standards” and “social media-related body dissatisfaction” + “deep learning-based multimodal emotion recognition technologies,” “3D motion and multisensory object representation tools,” and “visual matching and image processing algorithms.” As research published between 2017 and 2022 was inspected, only 177 articles satisfied the eligibility criteria, and 25 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT.

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