论文标题
Google Edge TPU上的实时面具检测
Real-time Mask Detection on Google Edge TPU
论文作者
论文摘要
在Covid-19疫情爆发之后，自动检测人们是否戴口罩以降低前线工人的风险已经变得很重要。此外，在本地处理用户数据是解决隐私和网络带宽问题的好方法。在本文中，我们提出了一个轻巧的模型，用于检测特定区域中的人们是否戴口罩（也可以在珊瑚开发委员会（Coral Dev Board）上部署，珊瑚开发委员会（Coral Dev Board）是一个包含Google Edge TPU的市售开发板。我们的方法结合了基于Mobilenetv2 Plus SSD的对象检测网络和仅整数硬件的量化方案。结果，Edge TPU中的较轻模型的延迟明显较低，更适合于实时执行，同时保持与浮点设备相当的精度。
After the COVID-19 outbreak, it has become important to automatically detect whether people are wearing masks in order to reduce risk of front-line workers. In addition, processing user data locally is a great way to address both privacy and network bandwidth issues. In this paper, we present a light-weighted model for detecting whether people in a particular area wear masks, which can also be deployed on Coral Dev Board, a commercially available development board containing Google Edge TPU. Our approach combines the object detecting network based on MobileNetV2 plus SSD and the quantization scheme for integer-only hardware. As a result, the lighter model in the Edge TPU has a significantly lower latency which is more appropriate for real-time execution while maintaining accuracy comparable to a floating point device.
