3D Augmented Reality Try-on and Context-aware Emotion Recognition Technologies, Big Data-driven Facial Retouching and Artificial Intelligence-based Beauty Tools, and Deep Learning Sensor Fusion and Visual Perception Algorithms for Social Media
3D Augmented Reality Try-on and Context-aware Emotion Recognition Technologies, Big Data-driven Facial Retouching and Artificial Intelligence-based Beauty Tools, and Deep Learning Sensor Fusion and Visual Perception Algorithms for Social Media
Author(s): Elvira Nica, Asser Khamis, Silviea Crețu, Nurul Lizzan Kamarudin, Muzaffer Aydemir, Emilia Pascu, Cătălina-Oana DumitrescuSubject(s): Media studies, Individual Psychology, Social psychology and group interaction, Behaviorism, ICT Information and Communications Technologies
Published by: Addleton Academic Publishers
Keywords: 3D augmented reality try-on; big data-driven facial retouching; beauty; visual perception; self-presentation; unrealistic physical appearance;
Summary/Abstract: This article advances existing literature concerning 3D augmented reality try-on and context-aware emotion recognition technologies, big data-driven facial retouching and artificial intelligence-based beauty tools, and deep learning sensor fusion and visual perception algorithms for social media-related body dissatisfaction, self-presentation perceptions and behaviors, and unrealistic physical appearance. The screening software tools and evidence synthesis technologies deployed include Abstrackr, CADIMA, DistillerSR, Eppi-Reviewer, JBI SUMARI, Litstream, METAGEAR package for R, Nested Knowledge, PICO Portal, Rayyan, and SRDR+. The case studies cover AirBrush, B612, BeautyPlus, Evoto, Facetune, Filmora, Fotogenic, GlamAR, Meitu, Perfect365, Vivid Glam, and YouCam.
Journal: Journal of Research in Gender Studies
- Issue Year: 15/2025
- Issue No: 2
- Page Range: 53-64
- Page Count: 12
- Language: English
- Content File-PDF
