Copertina

Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment

Salvato in:
Pubblicato in:Applied Sciences vol. 15, no. 11 (2025), p. 5887
Autore principale: Ngo Huu-Huy
Altri autori: Le, Hung Linh, Feng-Cheng, Lin
Pubblicazione:
MDPI AG
Soggetti:
Visual impairment
Embedded systems
Deep learning
Smartphones
Social interaction
Internet access
Age
Computer vision
Gender
Sensors
Classification
Blindness
Algorithms
Facial recognition technology
Surveillance
Emotions
Internet of Things
Accesso online:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
Abstract:For people with vision impairment, various daily tasks, such as independent navigation, information access, and context awareness, may be challenging. Although several smart devices have been developed to assist blind people, most of these devices focus exclusively on navigation assistance and obstacle avoidance. In this study, we developed a portable system for not only obstacle avoidance but also identifying people and their emotions. The core of the developed system is a powerful and portable edge computing device that implements various deep learning algorithms for images captured from a webcam. The user can easily select a function by using a remote control device, and the system vocally reports the results to the user. The developed system has three primary functions: detecting the names and emotions of known people; detecting the age, gender, and emotion of unknown people; and detecting objects. To validate the performance of the developed system, a prototype was constructed and tested. The results reveal that the developed system has high accuracy and responsiveness and is therefore suitable for practical applications as a navigation and social assistive device for people with visual impairment.
ISSN:2076-3417
DOI:10.3390/app15115887
Fonte:Publicly Available Content Database