Mobile-Based Navigation Assistant for Visually Impaired Person with Real-time Obstacle Detection Using YOLO-based Deep Learning Algorithm

G. Catedrilla
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Abstract

This project mainly aims to develop a mobile-based application for navigation with real-time obstacle detection to provide fair access to people with visual impairment to some activities, specifically navigating outdoors. It is a navigation mobile application equipped with speech and gesture recognition, to allow the people with visual impairment to access and use the application, and obstacle detection to provide audio prompts to the user, so they will know whenever an object or obstacle is within the frame of the phone camera. The research was structured and accomplished through different scientific and technological process and approach. With the use of Dialog flow, it was possible to create a speech recognition feature for the application, while YOLO algorithm allowed the process of object detection using mobile phone camera, possible. In this research, it was found out that the application was applicable to improving the navigation of the visually impaired, it is ideal that it serves as supplement to the white stick in order to improve their navigation experience. Also, this project would like to emphasize that researches that seeks to help person with disability be considered and conducted by other researchers.
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基于深度学习算法的视障人士实时障碍物检测移动导航助手
本项目主要目的是开发一款具有实时障碍物检测功能的移动导航应用程序,为视力障碍人士提供公平的活动机会,特别是在户外导航。它是一款配备语音和手势识别功能的导航移动应用程序,允许视障人士访问和使用该应用程序,障碍物检测功能为用户提供音频提示,以便他们知道何时有物体或障碍物在手机摄像头的框架内。本研究是通过不同的科技流程和方法来组织和完成的。通过使用Dialog流,可以为应用程序创建语音识别功能,而YOLO算法允许使用手机摄像头检测物体的过程。在本研究中,我们发现该应用程序适用于改善视障人士的导航,它可以作为白棒的补充,以改善视障人士的导航体验。此外,这个项目想强调的是,寻求帮助残疾人的研究应该由其他研究人员考虑和进行。
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