DeepAI AI Chat
Log In Sign Up

CoverTheFace: face covering monitoring and demonstrating using deep learning and statistical shape analysis

by   Yixin Hu, et al.

Wearing a mask is a strong protection against the COVID-19 pandemic, even though the vaccine has been successfully developed and is widely available. However, many people wear them incorrectly. This observation prompts us to devise an automated approach to monitor the condition of people wearing masks. Unlike previous studies, our work goes beyond mask detection; it focuses on generating a personalized demonstration on proper mask-wearing, which helps people use masks better through visual demonstration rather than text explanation. The pipeline starts from the detection of face covering. For images where faces are improperly covered, our mask overlay module incorporates statistical shape analysis (SSA) and dense landmark alignment to approximate the geometry of a face and generates corresponding face-covering examples. Our results show that the proposed system successfully identifies images with faces covered properly. Our ablation study on mask overlay suggests that the SSA model helps to address variations in face shapes, orientations, and scales. The final face-covering examples, especially half profile face images, surpass previous arts by a noticeable margin.


page 1

page 3

page 4

page 6


The Effect of Wearing a Face Mask on Face Image Quality

Due to the COVID-19 situation, face masks have become a main part of our...

Bias-Aware Face Mask Detection Dataset

In December 2019, a novel coronavirus (COVID-19) spread so quickly aroun...

A Masked Face Classification Benchmark

We propose a novel image dataset focused on tiny faces wearing face mask...

Multi-Stage CNN Architecture for Face Mask Detection

The end of 2019 witnessed the outbreak of Coronavirus Disease 2019 (COVI...

Creative NFT-Copyrighted AR Face Mask Authoring Using Unity3D Editor

In this paper, we extend well-designed 3D face masks into AR face masks ...