Abstract
Analysing a video sequence is a challenge, because faces are constantly in dynamic motion, presenting many different possible rotational and illumination conditions. While solutions to the task of face detection have been presented, the detection performances of many systems are heavily dependent upon a strictly constrained environment. This paper presents the results of an image-based neural network face detection system which seeks to address the problem of detecting faces under gross variations.