Face Recognition on the Connection Machine CM-5

A biologically motivated compute intensive approach to computer vision is developed and applied to the problem of face recognition. The approach is based on the use of twodimensional Gabor functions that fit the receptive fields of simple cells in the primary visual cortex of mammals. A descriptor set that is robust against translations is extracted and used for a search in an image database. The method was applied on a database of 205 face images of 30 persons and a recognition rate of 94% was achieved. The final version of the paper will report on the results obtained by applying a set of 1024 Gabor functions on a database of 1000 face images of 150 persons and on the implementation on a Connection Machine CM-5 parallel supercomputer to be installed at our university until the end of 1992. 1 Introduction The advent of parallel supercomputers promoted high-speed computing in the many Giga floatingpoint operations per second (Gflops/s, G=10 9 ) domain and the first Tflops/s (T=10 1..