A Review of Cross-Age Facial Recognition Based on Discriminative Models
摘要
Biometric recognition leveraging facial features faces challenges due to aging-related changes in contours and textures, highlighting the importance of cross-age facial recognition. This review assesses discriminative methods within this domain, including both traditional and deep learning-based techniques, summarizing their strengths and limitations. It also details representative datasets and evaluation metrics used in the field, providing a comparative analysis of existing methods’ performance. Finally, the paper discusses future developments in cross-age facial recognition, outlining current research trends and potential investigative directions.