Application of a Neural Architecture to Extract Motion from Image Sequences

摘要

Investigation of two neural architectures is performed in two dimensions using both synthetic and real imagery. Our model follows the work performed by H. Ogmen and S GagnC in 1990 on the fly's visual system. We extended their model to a two-dimensional architecture and also developed a new model by adding long-term memory at the input -adaptive model. Our investigation compares the response of the adaptive model against the original Ogmen and GagnC's cell-activity model. The output of both models were further processed using causal and noncausal moving average filters to help remove tonic image elements and identify direction of motion Our simulations show that the adaptive model can be used to segment motion from sequences of imagery.