Comparative Study of Face Detection and Recognition for Sports Celebrity Videos

This research presents a comparative study on face detection and recognition techniques in organic video, specifically focusing on a sports celebrities database. The efficacy of many machine learning methods, such as DeepFace, Convolutional Neural Networks (CNNs), and Haar Cascade Classifiers, in identifying faces in cluttered and dynamic situations is assessed in this study. The model recognizes and categorizes athletes by examining video frames from live sporting events. Comparative research shows that deep learning models, in particular, CNNs achieve better robustness and accuracy in facial recognition tasks, which makes them perfect for real-time sports analytics and broadcasting applications.