Automatic Children Detection in Digital Images
Hans Weda, Mauro Barbieri · 2007
Distinguishing children from adults in digital images is beneficial for enabling ambient intelligent applications. For example, when an ambient intelligent shop window detects a child, it could adapt its content to the particular limitations and needs of children. This article presents a method to automatically detect children in digital images. The method is based on the fact that the size of a person's iris is practically constant after birth while the head grows as the person grows adult. Therefore adults can be distinguished from children based on the face/iris size ratio. The faces are detected using a standard Viola-Jones face detection technique. The irises are found and measured by using iterative Canny edge detection and a modified circular Hough transform. Our results show an accuracy of over 80% when tested on a set of 289 real life photographs of frontal faces.