Face and Eye Detection by CNN Algorithms

Authors:
David Balya;Tamás Roska
Affiliations:
Analogical and Neural Computing Laboratory, Computer and Automation Research Institute, Lágymányosi u. 11, Budapest, H-1111, Hungary;Analogical and Neural Computing Laboratory, Computer and Automation Research Institute, Lágymányosi u. 11, Budapest, H-1111, Hungary
Venue:
Journal of VLSI Signal Processing Systems - Special issue on spatiotemporal signal processing with analog CNN visual microprocessors
Year:
1999

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Abstract

A novel approach to critical parts of face detectionproblems is given, based on analogic cellular neural network (CNN)algorithms. The proposed CNN algorithms find and help to normalizehuman faces effectively while their time requirement is a fraction ofthe previously used methods. The algorithm starts with the detectionof heads on color pictures using deviations in color and structure ofthe human face and that of the background. By normalizing thedistance and position of the reference points, all faces should betransformed into the same size and position. For normalization, eyesserve as points of reference. Other CNN algorithm finds the eyes onany grayscale image by searching characteristic features of the eyesand eye sockets. Tests made on a standard database show that thealgorithm works very fast and it is reliable.