Open AccessThe Use of Neural Networks in Real-time Face Detection
Author(s) -
Kevin Curran,
X Li,
S mccaughley
Publication year - 2005
Publication title -
journal of computer sciences/journal of computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.161
H-Index - 28
eISSN - 1552-6607
pISSN - 1549-3636
DOI - 10.3844/jcssp.2005.47.62
Subject(s) - computer science , artificial intelligence , face detection , computer vision , face (sociological concept) , object class detection , task (project management) , artificial neural network , constraint (computer aided design) , motion detection , facial recognition system , real time computing , pattern recognition (psychology) , motion (physics) , social science , sociology , mechanical engineering , management , economics , engineering
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