Principal Component Analysis

A statistical technique that reduces the dimensionality of data by identifying the principal axes of variation in a dataset. In accessibility and assistive technology contexts, PCA is commonly used in face recognition systems (as the basis of the Eigenfaces method), gesture recognition, and other computer vision applications that help people with disabilities interact with their environment. By reducing complex visual data to a smaller set of meaningful components, PCA enables real-time processing on portable devices.