论文标题
Building Brook：人力车相互作用研究的多模式和面部视频数据库
Building BROOK: A Multi-modal and Facial Video Database for Human-Vehicle Interaction Research
论文作者
论文摘要
随着自动驾驶汽车的日益普及，在人体车相互作用的背景下，更多的机会绽放了。但是，缺乏针对整个设计空间中相关研究的这种特定用例限制的全面和具体的数据库支持。在本文中，我们介绍了我们进行的工作，这是一个带有面部视频记录的公共多模式数据库，可用于表征驾驶员的情感状态和驾驶风格。我们首先解释了我们如何详细研究此类数据库，以及我们通过十个月的研究获得了什么。然后，我们展示了一个基于神经网络的预测指标，利用Brook，该预测通过面部视频支持多模式预测（包括心率和皮肤电导的生理数据以及速度的驾驶状态数据）。最后，我们讨论在Brook背景下构建此类数据库和未来方向时的相关问题。我们认为Brook是未来人车相互作用研究的重要组成部分。
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.
