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——一项为建成环境评估提供工具与数据集的新颖倡议。我们提出了一个用于街景数据采集、加载与分析的整体框架。利用该框架，我们收集了一个创新数据集，该数据集整合了通过胸戴式移动设备采集的同步视频影像与传感器数据（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行进的路径。该数据集包含三小时内容，覆盖九所医院周围12公里范围，包含32.5万帧视频画面及对应的传感器数据。此外，我们提出了一种专门为人行道场景识别创建的包含68个要素的新型分类体系。SideSeeing是构建城市专家可用于深入评估人行道通达性工具套件的重要一步。SideSeeing数据与工具已在https://sites.usp.br/sideseeing/公开提供。