Abstract :
Face recognition across age progression is remains one of the areas most challenging tasks now a days, as the aging process affects both the shape and texture of a face. One possible solution is to apply a probabilistic model to represent a face simultaneously with its identity variable, which is stable through time, and its aging variable, which changes with time. This paper proposes a deep learning and set based approach to the face recognition subject to aging. The images for each subject taken at various times are treated as a single set, which is then compared to the sets of images belonging to other subjects. Facial features are extracted using a convolutional neural network characteristic of the deep learning. Our experimental results show that set based recognition performs better than the singleton based approach for the both face identification and face verification. We also find that by using set based recognition, it is easier to recognize older subjects from younger ones rather than younger subjects from older ones. Prathama V | Thippeswamy G "Age Invariant Face Recognition" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23572.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23572/age-invariant-face-recognition/prathama-v
Keyword :
CNN- Convolution Neural network, AIFR-Age invariant face recognition, Polling, Flattening, Keras