论文标题
人类活动识别在工业过程中的应用 - 人类和技术的协同作用
Applications of human activity recognition in industrial processes -- Synergy of human and technology
论文作者
论文摘要
人类技术合作依赖于口头和非语言交流。机器必须能够检测并了解人类的运动，以促进非语言交流。在本文中，我们介绍了对内部杂志中人类活动识别的持续研究，并展示了如何在工业环境中应用。我们展示了如何使用语义属性来灵活地描述人类的活动，以及上下文信息如何提高分类器的性能以自动识别它们。除此之外，我们提出了一个基于网络物理双胞胎的概念，该概念可以减少为人类活动识别创建培训数据集所需的精力和时间。将来，可以在维持甚至提高分类性能的同时，仅使用逼真的模拟数据培训分类器。
Human-technology collaboration relies on verbal and non-verbal communication. Machines must be able to detect and understand the movements of humans to facilitate non-verbal communication. In this article, we introduce ongoing research on human activity recognition in intralogistics, and show how it can be applied in industrial settings. We show how semantic attributes can be used to describe human activities flexibly and how context informantion increases the performance of classifiers to recognise them automatically. Beyond that, we present a concept based on a cyber-physical twin that can reduce the effort and time necessary to create a training dataset for human activity recognition. In the future, it will be possible to train a classifier solely with realistic simulation data, while maintaining or even increasing the classification performance.
