Human-like Tactile Sensing and Perception Technologies, Beauty Filter-based Appealing Self-Presentation and Realistic Makeup Simulation Tools, and Deep Learningbased Facial Expression Recognition and Artificial Intelligence
Human-like Tactile Sensing and Perception Technologies, Beauty Filter-based Appealing Self-Presentation and Realistic Makeup Simulation Tools, and Deep Learningbased Facial Expression Recognition and Artificial Intelligence
Author(s): Ioana Alexandra Pârvu, Zoran Simonović, Vloreen Nity Anak Mathew, Alexandra Teodora Ababii, Firdaus Abdullah, Cristian Florin CiurlăuSubject(s): Media studies, Individual Psychology, Social psychology and group interaction, Experimental Psychology, Clinical psychology, Behaviorism, Human Resources in Economy, ICT Information and Communications Technologies
Published by: Addleton Academic Publishers
Keywords: beauty filter-based appealing self-presentation; realistic makeup simulation; tactile sensing and perception; facial expression recognition; mediated virtual selfexpression and representation; artificial intelligence-enabled emotion communication;
Summary/Abstract: The purpose of the paper is to explore human-like tactile sensing and perception technologies, beauty filter-based appealing self-presentation and realistic makeup simulation tools, and deep learning-based facial expression recognition and artificial intelligence-enabled emotion communication systems for mediated virtual self-expression and representation. Study screening tools, machine learning classifiers, and reference management software employed include AMSTAR, BIBOT, Catchii, DistillerSR, Eppi-Reviewer, JBI SUMARI, Litstream, METAGEAR package for R, Nested Knowledge, PICO Portal, ROBIS, and SluRp. The case studies cover AirBrush, BeautyPlus, Evoto, FaceApp, FaceTune, Fotor, Maybelline, Media.io, Meitu, Picsart, PhotoDirector, PrettyUp, VanceAI, Vivid Glam, Wondershare UniConverter, and YouCam.
Journal: Journal of Research in Gender Studies
- Issue Year: 15/2025
- Issue No: 2
- Page Range: 76-87
- Page Count: 12
- Language: English
- Content File-PDF
