StreetAware: A High-Resolution Synchronized Multimodal Urban Scene Dataset

Access to high-quality data is an important barrier in the digital analysis of urban settings, including applications within computer vision and urban design. Diverse forms of data collected from sensors at areas of high activity in the urban environment, such as street intersections, are thus a valuable resource for researchers interpreting the dynamics between vehicles, pedestrians, and the built environment. We present a high-resolution audio, video, and LiDAR dataset of three urban intersections in Brooklyn, New York, totaling approximately 8 unique hours. The data is collected with custom Reconfigurable Environmental Intelligence Platform (REIP) sensors that are designed with the ability to accurately synchronize multiple video and audio inputs. Access the data files Due to the size (~550 GB) and complexity of the data, you must access it via Globus: https://app.globus.org/file-manager?origin_id=c43d41ac-d286-4ac4-9318-3d65f3d9b855&origin_path=%2Fq1byv-qc065-streetaware%2F. The README file explains the contents further.在城市环境的数字化分析工作中，获取高质量数据是一项核心瓶颈，其应用范畴涵盖计算机视觉与城市设计等领域。从城市高流量区域（如道路交叉口）的传感器采集的多模态数据，是研究人员解析车辆、行人与建成环境间动态交互关系的宝贵资源。本研究发布一组高分辨率数据集，包含美国纽约布鲁克林区三处城市交叉口的音频、视频与激光雷达（LiDAR）数据，总时长约8小时。该数据集通过定制化可重构环境智能平台（Reconfigurable Environmental Intelligence Platform, REIP）传感器采集，该平台支持对多路视频与音频输入进行精准同步校准。 数据获取说明 鉴于数据集体量约550GB且结构复杂，您需通过Globus平台获取数据：https://app.globus.org/file-manager?origin_id=c43d41ac-d286-4ac4-9318-3d65f3d9b855&origin_path=%2Fq1byv-qc065-streetaware%2F。数据集附带的README文件将进一步详述数据内容。

搜集汇总

背景与挑战

背景概述

StreetAware是一个高分辨率、多模态同步的城市场景数据集，包含音频、视频和LiDAR数据，采集自纽约布鲁克林的三个交叉口，总时长约8小时。该数据集旨在支持计算机视觉和城市设计研究，通过自定义REIP传感器实现精确数据同步，数据量约550 GB，需通过Globus平台访问。