Scalvini Florian, Bordeau Camille, Ambard Maxime, Migniot Cyrille, Vergnaud Mathilde, Dubois Julien
ImViA EA 7535 - Université de Bourgogne, Dijon, France.
LEAD CNRS UMR 5022, Université de Bourgogne, Dijon, France.
Data Brief. 2024 Feb 1;53:110088. doi: 10.1016/j.dib.2024.110088. eCollection 2024 Apr.
The dataset proposed is a collection of pedestrian navigation data sequences combining visual and spatial information. The pedestrian navigation sequences are situations encountered by a pedestrian walking in an urban outdoor environment, such as moving on the sidewalk, navigating through a crowd, or crossing a street when the pedestrian light traffic is green. The acquired data are timestamped provided RGB-D images and are associated with GPS, and inertial data (acceleration, rotation). These recordings were acquired by separate processes, avoiding delays during their capture to guarantee a synchronisation between the moment of acquisition by the sensor and the moment of recording on the system. The acquisition was made in the city of Dijon, France, including narrow streets, wide avenues, and parks. Annotations of the RGB-D are also provided by bounding boxes indicating the position of relevant static or dynamic objects present in a pedestrian area, such as a tree, bench, or person. This pedestrian navigation dataset aims to support the development of smart mobile systems to assist visually impaired people in their daily movements in an outdoor environment. In this context, the visual data and localisation sequences we provide can be used to elaborate the appropriate visual processing methods to extract relevant information about the obstacles and their current positions on the path. Alongside the dataset, a visual-to-auditory substitution method has been employed to convert each image sequence into corresponding stereophonic sound files, allowing for comparison and evaluation. Synthetic sequences associated with the same information set are also provided based on the recordings of a displacement within the 3D model of a real place in Dijon.
所提出的数据集是一个结合视觉和空间信息的行人导航数据序列集合。行人导航序列是行人在城市户外环境中行走时遇到的情况,例如在人行道上行走、在人群中穿行或在人行横道绿灯亮起时过马路。采集到的数据带有时间戳,提供RGB-D图像,并与GPS和惯性数据(加速度、旋转)相关联。这些记录是通过单独的过程获取的,在采集过程中避免了延迟,以确保传感器采集时刻与系统记录时刻之间的同步。采集工作在法国第戎市进行,包括狭窄的街道、宽阔的大道和公园。还通过边界框提供了RGB-D的注释,指示行人区域中存在的相关静态或动态物体的位置,例如树木、长椅或行人。这个行人导航数据集旨在支持智能移动系统的开发,以帮助视障人士在户外环境中的日常移动。在这种情况下,我们提供的视觉数据和定位序列可用于精心设计适当的视觉处理方法,以提取有关障碍物及其在路径上当前位置的相关信息。除了数据集之外,还采用了一种视觉到听觉的替代方法,将每个图像序列转换为相应的立体声声音文件,以便进行比较和评估。还基于在第戎市一个真实地点的3D模型内的位移记录,提供了与相同信息集相关联的合成序列。