SMARTPHONE-BASED CROSSWALK DETECTION AND LOCALIZATION FOR VISUALLY IMPAIRED PEDESTRIANS.
SMARTPHONE-BASED CROSSWALK DETECTION AND LOCALIZATION FOR VISUALLY IMPAIRED PEDESTRIANS.
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DOI：
10.1109/icmew.2013.6618432
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发表时间：
2013-07
期刊：
影响因子：
--
通讯作者：
Coughlan JM
中科院分区：
文献类型：
--
作者：
Murali VN;Coughlan JM
本文介绍了“交叉观察”项目的最新工作，该项目是一个基于计算机视觉的智能手机系统，旨在为交通路口的盲人和视障人士提供指导。CrossWatch的一个关键功能是自定位--估计用户相对于当前交通路口人行横道的位置。这些信息对于视力较低或没有视力的用户可能非常重要，以确保他们知道要进入哪个人行横道，并相对于人行横道适当地对齐和定位。然而，虽然基于计算机视觉的方法已被用于寻找人行横道并帮助盲人旅行者将自己与其对齐，但这些方法假设整个人行横道模式可以在一帧视频中成像，这对缺乏足够视觉的用户来说是一个巨大的挑战，用户不知道将相机指向哪里以便正确地拍摄人行横道。在这篇文章中，我们描述了解决人行横道检测和自我定位问题的正在进行的工作，基于最近的工作，描述了使盲人和视障用户能够在人行道上原地转弯时获得360°图像全景图的技术。图像全景图被转换为附近交叉口的空中(俯瞰)视图，以用户所在的位置为中心，以便于与从谷歌地图卫星图像获得的交叉口的模板匹配。匹配过程允许检测人行横道特征，并允许估计用户相对于感兴趣的人行横道的精确位置。通过对盲人用户获取的交叉口图像进行实验，验证了该方法的可行性。
This paper describes recent work on the “Crosswatch” project, which is a computer vision-based smartphone system developed for providing guidance to blind and visually impaired travelers at traffic intersections. A key function of Crosswatch is self-localization – the estimation of the user’s location relative to the crosswalks in the current traffic intersection. Such information may be vital to users with low or no vision to ensure that they know which crosswalk they are about to enter, and are properly aligned and positioned relative to the crosswalk. However, while computer vision-based methods have been used for finding crosswalks and helping blind travelers align themselves to them, these methods assume that the entire crosswalk pattern can be imaged in a single frame of video, which poses a significant challenge for a user who lacks enough vision to know where to point the camera so as to properly frame the crosswalk. In this paper we describe work in progress that tackles the problem of crosswalk detection and self-localization, building on recent work describing techniques enabling blind and visually impaired users to acquire 360° image panoramas while turning in place on a sidewalk. The image panorama is converted to an aerial (overhead) view of the nearby intersection, centered on the location that the user is standing at, so as to facilitate matching with a template of the intersection obtained from Google Maps satellite imagery. The matching process allows crosswalk features to be detected and permits the estimation of the user’s precise location relative to the crosswalk of interest. We demonstrate our approach on intersection imagery acquired by blind users, thereby establishing the feasibility of the approach.