A Lie group approach to a neural system for three-dimensionalinterpretation of visual motion |
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Authors: | Tsao T-R Shyu H-J Libert JM Chen VC |
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Affiliation: | Vitro Corp., Silver Spring, MD. |
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Abstract: | 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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