The Use of Neural Networks in Real-time Face Detection
Kevin Curran, Xuelong Li and Neil M. Caughley
DOI : 10.3844/jcssp.2005.47.62
Journal of Computer Science
Volume 1, Issue 1
As continual research is being conducted in the area of computer vision, one of the most practical applications under vigorous development is in the construction of a robust real-time face detection system. Successfully constructing a real-time face detection system not only implies a system capable of analyzing video streams, but also naturally leads onto the solution to the problems of extremely constraint testing environments. Analyzing a video sequence is the current challenge since 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, detection performances of many systems are heavily dependent upon a strictly constrained environment. The problem of detecting faces under gross variations remains largely uncovered. This study presents a real-time face detection system which uses an image based neural network to detect images.
© 2005 Kevin Curran, Xuelong Li and Neil M. Caughley. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.