An Image-Based Method of Distinguishing Children from Adults
Distinguishing children from adults via facial image analysis has lots of potential real-world applications such as security access control and human computer interaction. However,it is still a challenging problem for the computer vision systems to automatically and effectively distinguish children from adults. In this paper, we introduce a novel children recognition method, which improves both the accuracy and reliability of the latest work on this subject simultaneously. Results on the FG-NET aging database show that using the minimum distance classifier on the one dimensional feature space created by using Active Appearance Model (AAM) followed by Linear Discriminant Analysis (LDA), we can recognize the children and adults with accuracies up to 89% and 90%, respectively.