Real-time Mask Detection on Google Edge TPU

• URL: http://arxiv.org/abs/2010.04427v1
• Date: Fri, 9 Oct 2020 08:21:34 GMT
• Title: Real-time Mask Detection on Google Edge TPU
• Authors: Keondo Park, Wonyoung Jang, Woochul Lee, Kisung Nam, Kihong Seong, Kyuwook Chai, Wen-Syan Li
• Abstract summary: After the COVID-19 outbreak, it has become important to automatically detect whether people are wearing masks. 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.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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