Facial Hair

Facial hair significantly impacts the accuracy of face recognition systems, creating biases particularly noticeable across different demographics and genders. Current research focuses on developing improved facial hair segmentation models and addressing these biases through data balancing techniques and adaptive thresholding methods, often employing deep learning architectures. These efforts aim to enhance the fairness and reliability of face recognition technology by mitigating the influence of facial hair on recognition accuracy, with implications for security, law enforcement, and other applications relying on facial identification.