Imagery, privacy and ethics: an overview of partially occluded facial biometric analysis in the era of face masks

The COVID-19 pandemic has drastically changed human lifestyles, with implications on many aspects of human life. With the proliferation of masks to combat the spread of the virus, many computer vision workflows have been inadvertently affected to varying degrees. Consequently, many research articles have been dedicated to evaluating the impact to existing facial imagery recognition problems. Several works have attempted to either extend existing facial models or develop new techniques specific to masked faces. Many new benchmark tasks have also been introduced in this subdomain. However, a detailed review of such advancements is not available for perusal in this critical area for COVID-safe protocol development. In this work, we address this issue as the first review of masked facial recognition tasks and techniques robust to masked facial images. Our motivation is to provide a central reference for automated public health and COVID-safe identification protocols while also exploring the ethical aspects of further development of such techniques.