Title :
Volterra series analysis and synthesis of a neural network for velocity estimation
Author :
Gray, W. Steven ; Nabet, Bahram
Author_Institution :
Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA
fDate :
4/1/1999 12:00:00 AM
Abstract :
The motion detection problem occurs frequently in many applications connected with computer vision. Researchers have studied motion detection based on naturally occurring biological circuits for over a century. In this paper, we propose and analyze a motion detection circuit which is based on nerve membrane conduction. It consists of two unidirectional neural networks connected in an opposing fashion. Volterra input-output (I-O) models are then derived for the network so that velocity estimation can be cast as a parameter estimation problem. The technique is demonstrated through simulation
Keywords :
Volterra series; computer vision; image motion analysis; neural net architecture; parameter estimation; Volterra series analysis; biological circuits; computer vision; motion detection problem; nerve membrane conduction; neural network; parameter estimation; simulation; velocity estimation; Application software; Biological system modeling; Biomembranes; Circuit simulation; Circuit synthesis; Computer vision; Motion detection; Network synthesis; Neural networks; Parameter estimation;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.752793