A complex associative memory model based on a neural network architect
ure is proposed for tracking three-dimensional objects in a dynamic en
vironment. The storage representation of the complex associative memor
y model is based on an efficient amplitude-modulated phase-only matche
d filter. The input to the memory is derived from the discrete Fourier
transform of the edge coordinates of the to-be-recognized moving obje
ct, where the edges are obtained through motion-based segmentation of
the image scene. An adaptive threshold is used during the decision-mak
ing process to indicate a match or identify a mismatch. Computer simul
ation on real-world data proves the effectiveness of the proposed mode
l. The proposed scheme is readily amenable to optoelectronic implement
ation.