This paper introduces SideSeeing, a novel initiative that provides tools and datasets for assessing the built environment. We present a framework for street-level data acquisition, loading, and analysis. Using the framework, we collected a novel dataset that integrates synchronized video footaged captured from chest-mounted mobile devices with sensor data (accelerometer, gyroscope, magnetometer, and GPS). Each data sample represents a path traversed by a user filming sidewalks near hospitals in Brazil and the USA. The dataset encompasses three hours of content covering 12 kilometers around nine hospitals, and includes 325,000 video frames with corresponding sensor data. Additionally, we present a novel 68-element taxonomy specifically created for sidewalk scene identification. SideSeeing is a step towards a suite of tools that urban experts can use to perform in-depth sidewalk accessibility evaluations. SideSeeing data and tools are publicly available at https://sites.usp.br/sideseeing/.

翻译：本文介绍SideSeeing，这是一项旨在为建成环境评估提供工具与数据集的新举措。我们提出了一个用于街道级数据采集、加载与分析的整体框架。利用该框架，我们收集了一个新颖的数据集，该数据集整合了通过胸戴式移动设备捕获的同步视频片段与传感器数据（加速度计、陀螺仪、磁力计和GPS）。每个数据样本代表用户在巴西和美国医院附近拍摄人行道时所经过的路径。该数据集包含三小时的内容，覆盖九家医院周围12公里的范围，并包含325,000个视频帧及其对应的传感器数据。此外，我们提出了一个专门为人行道场景识别创建的、包含68个类别的新颖分类体系。SideSeeing是迈向为城市专家提供用于深入评估人行道可达性工具套件的一步。SideSeeing的数据与工具已在 https://sites.usp.br/sideseeing/ 公开提供。