Face tracking for people with or without wearing face masks - Teh, Boon Jie (Nanyang Technological University, 2021)
Face Tracking (FT) algorithm serves as the backbone of modern public security tool. FT is a two-step process where faces are detected each frame, followed by associations of detections across frames in a video sequence. The core that influences accuracy of the algorithm in tracking human is the accuracy of face detection process and is therefore the focus of this Final Year Project. Many state-of-the-art deep neural network algorithms are much less accurate in detecting human that wear masks as only limited number of images, in the range of hundreds, with human wearing masks are available. Thus, the performances of these algorithms are questioned during the COVID-19 pandemic as wearing face masks has been prevalent.