Design of an automotive platform for computer vision research

Dominik Schörkhuber, R. Popp, Oleksandr Chistov, Fabian Windbacher, Michael Hödlmoser, M. Gelautz
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Abstract

The goal of our work is to design an automotive platform for AD/ADAS data acquisition in view of subsequent application to behaviour analysis of vulnerable road users. We present a novel data capture platform mounted on a Mercedes GLC vehicle. The car is equipped with an array of sensors and recording hardware including multiple RGB cameras, Lidar, GPS and IMU. For future research on human behaviour analysis in traffic scenes, we compile two kinds of data recordings. Firstly, we design a range of artificial test cases which we then record on a safety regulated proving ground with stunt persons to capture rare events in traffic scenes in a predictable and structured way. Secondly, we record data on public streets of Vienna, Austria, showing unconstrained pedestrian behaviour in an urban setting, while also considering European General Data Protection Regulation (GDPR) requirements. We describe the overall framework including the planning phase, data acquisition and ground truth annotation.
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汽车计算机视觉研究平台的设计
我们的工作目标是设计一个用于AD/ADAS数据采集的汽车平台,以便随后应用于弱势道路使用者的行为分析。我们提出了一个新的数据捕获平台安装在奔驰GLC车辆。该车配备了一系列传感器和记录硬件,包括多个RGB摄像头、激光雷达、GPS和IMU。为了进一步研究交通场景中的人类行为分析,我们编写了两种数据记录。首先,我们设计了一系列人工测试用例,然后在安全监管的试验场与特技人员一起记录,以可预测和结构化的方式捕捉交通场景中的罕见事件。其次,我们记录了奥地利维也纳公共街道上的数据,显示了城市环境中不受约束的行人行为,同时也考虑了欧洲通用数据保护条例(GDPR)的要求。我们描述了整个框架,包括规划阶段,数据采集和地面真值注释。
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