Masked Face Analysis

Masked Face Analysis

Presenter(s)

Vatsa Sanjay Patel

Comments

Presentation: 12:00 p.m.-12:20 p.m., Kennedy Union 211

Description

Face identification with wearables has been a difficult topic in computer vision since it includes detecting persons who are wearing a face mask. Masked face analysis for the purpose of identifying face masks has the potential to significantly increase performance in a wide variety of face analysis applications. The suggested concept is a single framework for determining the kind of face mask worn by a person. We begin by contributing the mask dataset, which includes a range of face masks. Then, we introduced a deep learning model that takes an input image of a human face wearing a mask and determines the kind of face mask worn by the human face. The presented dataset and methodology will aid in future research on face detection using the mask.

Publication Date

4-20-2022

Project Designation

Independent Research

Primary Advisor

Van Tam Nguyen

Primary Advisor's Department

Computer Science

Keywords

Stander Symposium project, College of Arts and Sciences

United Nations Sustainable Development Goals

Quality Education

Masked Face Analysis

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