Real time Mask Detection on Google Edge TPU
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.
ArXiv