Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model

Autor:	Qawaqneh, Zakariya, Mallouh, Arafat Abu, Barkana, Buket D.
Rok vydání:	2017
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	Automatic age estimation from real-world and unconstrained face images is rapidly gaining importance. In our proposed work, a deep CNN model that was trained on a database for face recognition task is used to estimate the age information on the Adience database. This paper has three significant contributions in this field. (1) This work proves that a CNN model, which was trained for face recognition task, can be utilized for age estimation to improve performance; (2) Over fitting problem can be overcome by employing a pretrained CNN on a large database for face recognition task; (3) Not only the number of training images and the number subjects in a training database effect the performance of the age estimation model, but also the pre-training task of the employed CNN determines the performance of the model. Comment: 8 pages, 2 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1709.01664 Zobrazit plný text záznamu View this record from Arxiv