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A Vision-Based Wayfinding System for Visually Impaired People Using Situation Awareness and Activity-Based Instructions

机译:基于视觉意识和基于活动的指示的视力障碍者的基于视觉的寻路系统

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摘要

A significant challenge faced by visually impaired people is ‘wayfinding’, which is the ability to find one’s way to a destination in an unfamiliar environment. This study develops a novel wayfinding system for smartphones that can automatically recognize the situation and scene objects in real time. Through analyzing streaming images, the proposed system first classifies the current situation of a user in terms of their location. Next, based on the current situation, only the necessary context objects are found and interpreted using computer vision techniques. It estimates the motions of the user with two inertial sensors and records the trajectories of the user toward the destination, which are also used as a guide for the return route after reaching the destination. To efficiently convey the recognized results using an auditory interface, activity-based instructions are generated that guide the user in a series of movements along a route. To assess the effectiveness of the proposed system, experiments were conducted in several indoor environments: the sit in which the situation awareness accuracy was 90% and the object detection false alarm rate was 0.016. In addition, our field test results demonstrate that users can locate their paths with an accuracy of 97%.
机译:视障人士面临的重大挑战是“寻路”,即在陌生环境中找到通往目的地的道路的能力。这项研究为智能手机开发了一种新颖的寻路系统,该系统可以实时自动识别情况和场景对象。通过分析流图像,提出的系统首先根据用户的位置对用户的当前状况进行分类。接下来,根据当前情况,使用计算机视觉技术只能找到并解释必要的上下文对象。它使用两个惯性传感器估算用户的运动,并记录用户朝向目的地的轨迹,这些轨迹也用作到达目的地后返回路线的指南。为了使用听觉界面有效传达识别的结果,将生成基于活动的指令,以指导用户沿路线进行一系列移动。为了评估所提出系统的有效性,在几种室内环境中进行了实验:情况感知准确度为90%,目标检测错误警报率为0.016的场所。此外,我们的现场测试结果表明,用户可以以97%的精度定位其路径。

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