High-fidelity pedestrian tracking in real-life conditions has been an important tool in fundamental crowd dynamics research allowing to quantify statistics of relevant observables including walking velocities, mutual distances and body orientations. As this technology advances, it is becoming increasingly useful also in society. In fact, continued urbanization is overwhelming existing pedestrian infrastructures such as transportation hubs and stations, generating an urgent need for real-time highly-accurate usage data, aiming both at flow monitoring and dynamics understanding. To successfully employ pedestrian tracking techniques in research and technology, it is crucial to validate and benchmark them for accuracy. This is not only necessary to guarantee data quality, but also to identify systematic errors. In this contribution, we present and discuss a benchmark suite, towards an open standard in the community, for privacy-respectful pedestrian tracking techniques. The suite is technology-independent and is applicable to academic and commercial pedestrian tracking systems, operating both in lab environments and real-life conditions. The benchmark suite consists of 5 tests addressing specific aspects of pedestrian tracking quality, including accurate crowd flux estimation, density estimation, position detection and trajectory accuracy. The output of the tests are quality factors expressed as single numbers. We provide the benchmark results for two tracking systems, both operating in real-life, one commercial, and the other based on overhead depth-maps developed at TU Eindhoven. We discuss the results on the basis of the quality factors and report on the typical sensor and algorithmic performance. This enables us to highlight the current state-of-the-art, its limitations and provide installation recommendations, with specific attention to multi-sensor setups and data stitching.
翻译:在现实条件下,高度忠诚行人跟踪现实生活条件下的高度忠诚行人是基本人群动态研究的一个重要工具,可以量化相关观察点的统计数据,包括行走速度、相互距离和身体定向。随着这一技术的进步,它也在社会上越来越有用。事实上,持续的城市化使现有的行人基础设施,如交通枢纽和车站,变得压倒一切,造成迫切需要实时高度精确的使用数据,既着眼于流动监测和动态理解。为了成功地在研究和技术中采用行人跟踪技术,验证和衡量这些技术的准确性至关重要。这不仅是为了保证数据质量,而且也是为了查明系统性错误。在这个贡献中,我们提出并讨论一个基准套,在社区中建立开放的标准,用于尊重隐私的行人跟踪技术。这套建筑以技术为主,适用于学术和商业行人跟踪系统,在实验室环境和真实生活条件条件下运作。基准套包括5个测试,涉及行人行跟踪质量的具体方面,包括准确的人群流量估计、密度估计、定位和轨迹精确性。测试的产出是作为单一数字表示的质量因素。我们用一个标准来评估其具体运行结果。我们用两个系统根据实际运行的服务器结果。我们用一个数据库,根据一个数据库,用两个系统,根据一个数据库,根据一个数据库,根据一个数据库,根据一个数据库,根据一个数据库,提供计算。我们使用结果,用两个系统,根据一个数据库,根据一个数据库,根据一个数据库的进度和运行结果,提供两个系统进行基准,根据一个数据库,根据一个数据库,根据一个数据库,根据一个数据库进行。