Facial Video

Facial video analysis is a rapidly evolving field focused on extracting meaningful information from video recordings of faces, primarily aiming to measure physiological signals (like heart rate and blood pressure), assess pain or mental health states, and improve video editing and generation techniques. Current research heavily utilizes deep learning, employing architectures such as convolutional neural networks (CNNs), vision transformers (ViTs), and generative adversarial networks (GANs) to analyze spatiotemporal patterns in facial videos. These advancements have significant implications for healthcare monitoring (remote patient diagnostics), mental health assessment, and multimedia applications (realistic video generation and editing), offering non-contact, efficient, and potentially more accessible solutions.