面向人车交互研究的多模态人脸视频数据库BROOK的构建
Building BROOK: A Multi-modal and Facial Video Database for Human-Vehicle Interaction Research
摘要：
随着自动驾驶汽车的日益普及，在人车交互的背景下，出现了更多的机会。然而，缺乏全面和具体的数据库支持这样的特定用例限制了整个设计空间的相关研究。在本文中，我们提出了我们正在进行的工作布鲁克，一个公共的多模态数据库与面部视频记录，它可以用来表征驾驶员的情感状态和驾驶风格。我们首先详细解释我们如何过度设计这样的数据库，以及我们通过十个月的研究所获得的成果。然后，我们展示了一个基于神经网络的预测器，利用BROOK，它支持通过面部视频进行多模态预测（包括心率和皮肤电导的生理数据和速度的驾驶状态数据）。最后，我们讨论了相关的问题时，建立这样一个数据库和我们未来的方向在布鲁克的上下文中。我们相信BROOK是未来人车交互研究的重要组成部分。
英文摘要：
With the growing popularity of Autonomous Vehicles, more opportunities have bloomed in the context of Human-Vehicle Interactions. However, the lack of comprehensive and concrete database support for such specific use case limits relevant studies in the whole design spaces. In this paper, we present our work-in-progress BROOK, a public multi-modal database with facial video records, which could be used to characterize drivers' affective states and driving styles. We first explain how we over-engineer such database in details, and what we have gained through a ten-month study. Then we showcase a Neural Network-based predictor, leveraging BROOK, which supports multi-modal prediction (including physiological data of heart rate and skin conductance and driving status data of speed)through facial videos. Finally, we discuss related issues when building such a database and our future directions in the context of BROOK. We believe BROOK is an essential building block for future Human-Vehicle Interaction Research.
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