School of Computer Science, Technological University Dublin, D07EWV4 Dublin, Ireland.
Faculty of Computers and Artificial Intelligence, Cairo University, Cairo 12613, Egypt.
Sensors (Basel). 2021 Apr 29;21(9):3103. doi: 10.3390/s21093103.
Blind and Visually impaired people (BVIP) face a range of practical difficulties when undertaking outdoor journeys as pedestrians. Over the past decade, a variety of assistive devices have been researched and developed to help BVIP navigate more safely and independently. In addition, research in overlapping domains are addressing the problem of automatic environment interpretation using computer vision and machine learning, particularly deep learning, approaches. Our aim in this article is to present a comprehensive review of research directly in, or relevant to, assistive outdoor navigation for BVIP. We breakdown the navigation area into a series of navigation phases and tasks. We then use this structure for our systematic review of research, analysing articles, methods, datasets and current limitations by task. We also provide an overview of commercial and non-commercial navigation applications targeted at BVIP. Our review contributes to the body of knowledge by providing a comprehensive, structured analysis of work in the domain, including the state of the art, and guidance on future directions. It will support both researchers and other stakeholders in the domain to establish an informed view of research progress.
视障人士在进行户外步行时会遇到一系列实际困难。在过去的十年中,已经研究和开发了各种辅助设备来帮助视障人士更安全、更独立地导航。此外,在相关领域的研究也在使用计算机视觉和机器学习,特别是深度学习方法,来解决自动环境解释的问题。本文的目的是对视障人士辅助户外导航的直接相关或相关研究进行全面综述。我们将导航区域细分为一系列导航阶段和任务。然后,我们使用这种结构对研究进行系统的回顾,按任务分析文章、方法、数据集和当前的局限性。我们还概述了针对视障人士的商业和非商业导航应用。我们的综述通过对视障人士辅助户外导航领域工作的全面、结构化分析做出了贡献,包括最新技术,并为未来的发展方向提供了指导。它将支持该领域的研究人员和其他利益相关者对研究进展有一个明智的看法。