ICBR - FIS Booth and Usability Project

The last decade has seen an increase in the application of biometrics to security systems such as those implemented for protecting our border. Suppliers and researchers continue to improve the feasibility of these systems through analyzing biometric algorithms and potential vulnerabilities. The Human-Biometric Sensor Interaction (HBSI) evaluation method uses ergonomics, usability and sample quality criteria as explanatory variables for the overall biometric performance of a system. Recent work with the HBSI model has investigated the applicability of the Kinect Sensor for the automation of detecting errors from a user interaction when made to a biometric system. In this research, we discuss the use of critical and associated tracking points for evaluation within a scenario testing environment. The Kinect sensor is tested for its robustness and ability to provide reliable and stable range of skeletal tracking points across a number of transactions where travelers interact with a US-VISIT inspection booth whilst carrying different luggage combinations.近十年来，生物识别技术在边境安保等安防系统中的应用日益增多。供应商与研究人员通过分析生物识别算法与潜在漏洞，持续提升此类系统的落地可行性。人-生物识别传感器交互（Human-Biometric Sensor Interaction, HBSI）评估方法将人体工程学、可用性与样本质量标准作为系统整体生物识别性能的解释变量。基于HBSI模型的近期研究已探索了Kinect传感器在自动化检测生物识别系统用户交互错误方面的适用性。本研究探讨了在场景化测试环境中使用关键关联跟踪点开展评估的方法。本研究针对Kinect传感器展开测试，验证其在多组旅客携带不同组合行李、与US-VISIT查验台交互的场景下的鲁棒性，以及能否提供可靠且稳定的骨骼跟踪点范围。