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A face recognition system using holistic regional feature extraction

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2 Author(s)
Cychosz, L.W. ; Dept. of Electr. Eng., Wisconsin Univ., Milwaukee, WI, USA ; Jun Zhang

Two new face recognition systems are proposed using auto-associative backpropagation neural network feature extractors on facial regions in conjunction with key facial structure measurements. A third proposed system combines the first two systems using confidence measurements to select a best match. A Cottrell/Fleming face recognition network and a structural face data network are also implemented and evaluated. A training set of 60 images and a test set of 12 images, acquired under uncontrolled conditions, were used to evaluate system performances. The first two proposed systems correctly selected 67 percent of the training images when presented with the test image set. The third proposed system achieved a recognition rate of 75 percent. By comparison, the Cottrell/Fleming network and the structural data network achieved recognition rates of 25 percent and 8 percent, respectively

Published in:

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on  (Volume:5 )

Date of Conference:

9-12 May 1995