Process mining is one of the most active research streams in business process management. In recent years, numerous methods have been proposed for analyzing structured process data. Yet, in many cases, it is only the digitized parts of processes that are directly captured from process-aware information systems, and manual activities often result in blind spots. While the use of video cameras to observe these activities could help to fill this gap, a standardized approach to extracting event logs from unstructured video data remains lacking. Here, we propose a reference architecture to bridge the gap between computer vision and process mining. Various evaluation activities (i.e., competing artifact analysis, prototyping, and real-world application) ensured that the proposed reference architecture allows flexible, use-case-driven, and context-specific instantiations. Our results also show that an exemplary software prototype instantiation of the proposed reference architecture is capable of automatically extracting most of the process-relevant events from unstructured video data.

翻译：采矿是业务流程管理中最活跃的研究流之一。近年来,提出了许多分析结构化流程数据的方法。然而,在许多情况下,只有流程的数字化部分直接从过程意识信息系统中采集,人工活动往往导致盲点。虽然使用摄像机观察这些活动可有助于填补这一空白,但从非结构化视频数据中提取事件日志的标准化方法仍然缺乏。在这里,我们提议了一个弥合计算机愿景和进程采矿之间差距的参考架构。各种评估活动(即竞争性文物分析、原型和现实世界应用)确保了拟议的参考结构允许灵活、使用个案驱动和因地制宜的即时。我们的结果还表明,拟议的参考结构的示范软件原型即能自动从无结构的视频数据中提取大部分与过程相关的事件。