Mirrors! Gathering, Querying, and Analyzing Fashion and Medical Data

Abstract

Fashion industry and market represents a paramount domain touching people all over the world; however, it lacks transactional and analytical tools allowing ordinary people and fashion actors to get either real time information about their fashion life trajectory and/or analytical ones about the fashion market and industry evolving. Inspired from the Snow-White fairy tale, the objective of this work is to design a fashion pervasive system related to multiple participating persons providing their multimedia data captured through smart mirrors. Captured data, related essentially to fashion images and video augmented by users' annotation, is then organized and stored locally for users' transactional querying and secured and centralized into a data warehouse and/or data mart for enhanced analysis and mining. Transactional querying permits to ordinary users to get information about their clothing habits and history. Analysis and mining allow fashion enterprises to get insights and predictions about the fashion market and industry evolution.