摘要
Figure-ground discrimination and pattern discrimination represent one of the most important problems in computer vision. Based on computational neuronal network model proposed by Reichardt et al. for figure-ground discrimination in the visual system of the fly, entire systematic computer simulations were carried out under nonstationary conditions. Results show that the model network and simulations have predictive power for behavioural experimental results. This paper proposes that motion perception and elementary pattern discrimination in human visual system may be mediated by some kind of figure-ground system with movement detectors as input layer.
Figure-ground discrimination and pattern discrimination represent one of the most important problems in computer vision. Based on computational neuronal network model proposed by Reichardt et al. for figure-ground discrimination in the visual system of the fly, entire systematic computer simulations were carried out under nonstationary conditions. Results show that the model network and simulations have predictive power for behavioural experimental results. This paper proposes that motion perception and elementary pattern discrimination in human visual system may be mediated by some kind of figure-ground system with movement detectors as input layer.
