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Uncertainty-Aware Visual Perception System for Outdoor Navigation of the Visually Challenged
George Dimas1, Dimitris E Diamantis1, Panagiotis Kalozoumis1
1Department. of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece.
Sensors (Basel, Switzerland)
|April 26, 2020
Summary
This study introduces a wearable visual perception system (VPS) to aid visually challenged people (VCP) in outdoor navigation. The system uses AI for obstacle detection and linguistic descriptions, enhancing safe mobility.
Area of Science:
- Computer Science
- Artificial Intelligence
- Robotics
Background:
- Visually challenged people (VCP) experience significant mobility and accessibility limitations in daily life.
- Outdoor navigation presents unique challenges for VCP, impacting independence and safety.
Purpose of the Study:
- To propose a novel wearable visual perception system (VPS) for enhancing outdoor navigation for VCP.
- To develop an AI-driven system for robust obstacle detection and risk assessment.
- To provide users with descriptive linguistic feedback for intuitive environmental understanding.
Main Methods:
- Integration of deep learning and object recognition models within a wearable VPS.
- Utilization of Generative Adversarial Networks (GANs) for eye fixation-based obstacle detection.
- Implementation of uncertainty-aware fuzzy logic for obstacle risk assessment and spatial localization.
Main Results:
- The proposed system effectively detects and localizes obstacles in outdoor environments.
- Linguistic expressions are generated to describe obstacle positions and types for user comprehension.
- Performance evaluation demonstrates the system's capability for safe navigation in culturally significant outdoor settings.
Conclusions:
- The developed wearable VPS offers a promising solution for improving the mobility and independence of VCP.
- The AI-powered obstacle detection and linguistic feedback mechanism enhance user safety and environmental awareness.
- Comparative analysis indicates favorable design and user-requirement satisfaction compared to existing systems.
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