The application of cortex visual cognitive model on road environment perception

Rieseshuber and Poggio from MIT proposed a standard quantitative model of cortex visual cognitive. This feedforward hierarchical model perfect follows the visual perception mechanisms of the cortex from simple cells to the complex cells. This paper first adopts this cortex visual cognitive model (CVCM) into the street environment perception algorithm which is the hot issue in the intelligent transportation field. The algorithm works well in typical street objects detecting and localization in cluster street scene by combining the cortex perception model with the scaled windowing technique. The results show excellent detection rate and low false alarm rate.