Eigenfaces Method

Eigenfaces, a technique using Principal Component Analysis (PCA) to represent faces as a linear combination of "eigenfaces," aims to achieve efficient and robust face recognition. Current research explores improvements to the method, including integrating it with neural networks for enhanced accuracy and handling variations in lighting and expression, and comparing its performance against alternative approaches like Discrete Cosine Transform. While initially focused on full-face images, recent work addresses challenges like partial faces through image stitching and explores applications beyond simple identification, such as estimating mask-wearing ratios in crowds using both detection and regression-based methods. These advancements contribute to improved biometric systems and broader applications in image analysis and surveillance.