Lacking the ability to sense ambient environments effectively, blind and visually impaired people (BVIP) face difficulty in walking outdoors, especially in urban areas. Therefore, tools for assisting BVIP are of great importance. In this paper, we propose a novel "flying guide dog" prototype for BVIP assistance using drone and street view semantic segmentation. Based on the walkable areas extracted from the segmentation prediction, the drone can adjust its movement automatically and thus lead the user to walk along the walkable path. By recognizing the color of pedestrian traffic lights, our prototype can help the user to cross a street safely. Furthermore, we introduce a new dataset named Pedestrian and Vehicle Traffic Lights (PVTL), which is dedicated to traffic light recognition. The result of our user study in real-world scenarios shows that our prototype is effective and easy to use, providing new insight into BVIP assistance.

翻译：由于缺乏有效感知环境的能力,盲人和视障人士(BVIP)在户外行走时面临困难,特别是在城市地区。 因此, 帮助BVIP的工具非常重要。 在本文中, 我们提议使用无人驾驶飞机和街道视觉语义分割法为BVIP提供援助的新型“ 飞行导盲犬” 原型。 根据从分割预测中提取的可行走区域, 无人驾驶飞机可以自动调整其运动, 从而引导用户沿着行走路径行走。 通过识别行人交通灯的颜色, 我们的原型可以帮助用户安全过街。 此外, 我们引入了一套名为“ 飞车和车辆交通灯” ( PVTL) 的新数据集, 专门用于识别交通灯光。 我们用户在现实世界情景中的研究结果显示, 我们的原型是有效和容易使用的, 提供了对 BVIP 协助的新的洞察。