CVOct 9, 2023

Developing and Refining a Multifunctional Facial Recognition System for Older Adults with Cognitive Impairments: A Journey Towards Enhanced Quality of Life

arXiv:2310.06107v1Has Code
Originality Synthesis-oriented
AI Analysis

This work addresses the need for assistive technologies for older adults with cognitive impairments, but it is incremental as it builds on existing open-source tools without major methodological innovations.

The researchers developed a Multifunctional Facial Recognition System (MFRS) using the face_recognition library to assist older adults with cognitive impairments, integrating facial recognition, image capture, and voice memos to enhance usability and versatility.

In an era where the global population is aging significantly, cognitive impairments among the elderly have become a major health concern. The need for effective assistive technologies is clear, and facial recognition systems are emerging as promising tools to address this issue. This document discusses the development and evaluation of a new Multifunctional Facial Recognition System (MFRS), designed specifically to assist older adults with cognitive impairments. The MFRS leverages face_recognition [1], a powerful open-source library capable of extracting, identifying, and manipulating facial features. Our system integrates the face recognition and retrieval capabilities of face_recognition, along with additional functionalities to capture images and record voice memos. This combination of features notably enhances the system's usability and versatility, making it a more user-friendly and universally applicable tool for end-users. The source code for this project can be accessed at https://github.com/Li-8023/Multi-function-face-recognition.git.

Code Implementations2 repos
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes