Visual attention model based on Bayesian inference using multiple cues

For most of the visual attention models use linear combination to obtain saliency map,a visual attention model based on Bayesian inference using multiple cues is proposed,which is more consistent with biological mechanism.Bayesian inference is used to combine both top-down and bottom-up information,and the processes of visual attention is simulated in ventral stream and dorsal stream.Multiple visual cues are integrated,such as shape,color,and context.The experimental results on object detection and localization in remote sensing images show this model can detect and locate objects effectively.