Infrared Video

Infrared video analysis is a growing field leveraging the unique thermal information captured by infrared cameras to address diverse applications. Current research focuses on developing advanced deep learning models, including neural networks for image fusion and classification, to improve image quality (e.g., achieving high dynamic range) and extract meaningful information from infrared video data for tasks such as sleep apnea detection and meibomian gland analysis. These techniques offer non-invasive, potentially more accurate, and cost-effective alternatives to existing methods in healthcare and other fields, impacting both clinical practice and diagnostic capabilities. The development of large, annotated datasets is also crucial for advancing the field and enabling more robust model training.