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A Lie group approach to a neural system for three-dimensional interpretation of visual motion

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4 Author(s)
Tsao, T.-R. ; Vitro Corp., Silver Spring, MD, USA ; Shyu, H.J. ; Libert, J.M. ; Chen, V.C.

A novel approach is presented to neural network computation of three-dimensional rigid motion from noisy two-dimensional image flow. It is shown that the process of 3-D interpretation of image flow can be viewed as a linear signal transform. The elementary signals of this linear transform are the 2-D vector fields of the six infinitesimal generators of the 3-D Euclidean group. This transform can be performed by a neural network. Results are also reported of neural network simulations for the 3-D interpretation of image flow and a comparison of the performance of this approach with that using conventional methods. Computer simulation results verify the Lie-group-based neural network approach to three-dimensional motion perception

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Neural Networks, IEEE Transactions on  (Volume:2 ,  Issue: 1 )