One in twenty-five patients admitted to a hospital will suffer from a
hospital acquired infection. If we can intelligently track healthcare staff,
patients, and visitors, we can better understand the sources of such
infections. We envision a smart hospital capable of increasing operational
efficiency and improving patient care with less spending. In this paper, we
propose a non-intrusive vision-based system for tracking people's activity in
hospitals. We evaluate our method for the problem of measuring hand hygiene
compliance. Empirically, our method outperforms existing solutions such as
proximity-based techniques and covert in-person observational studies. We
present intuitive, qualitative results that analyze human movement patterns and
conduct spatial analytics which convey our method's interpretability. This work
is a step towards a computer-vision based smart hospital and demonstrates
promising results for reducing hospital acquired infections.

本研究提出一种基于计算机视觉的智能医院系统，用于跟踪医务人员、患者和访客的行动，并提高医院的运营效率和患者护理质量，特别是在手部卫生合规性的测量方面优于现有解决方案，为建立计算机视觉智能医院的发展迈出了一步，有望降低医院获得性感染的发生率。