Desarrollo de un algoritmo de re-identificación multi-modal de personas para mejorar la asistencia personalizada en una casa familiar

Abstract

This document presents the development of a multimodal re-identification algorithm to improve Human-Robot interaction in the home care setting. In this way, different people recognition strategies were integrated, such as facial recognition, voice recognition and soft-biometric characteristics (hair, eye and skin color). For this, in the first place a bibliographic consultation was carried out where possible algorithms to be used were chosen; Later, different tests were implemented and carried out in order to choose the algorithms that presented the best results for each re-identification strategy, then they were integrated into a single development based on multiple linear regression, which had a 97.4% success rate. Similarly, the entire system was implemented in ROS (robotic operating system) and tests were carried out where it was evaluated if the algorithm recognized personalized basic orders.