A Probabilistic Model of Visual Attention and Perceptual Organization for Constructive Object Recognition

Abstract

AbstractThis paper proposes a new probabilistic model of visual attention, figure-ground segmentation and perceptual organization. In this model, spatially parallel preattentive points on a saliency map are organized into sequential selective attended segments through figure-ground segmentation on dynamically-formed Markov random fields and perceptual organization among attended segments are performed in visual working memory for constructive object recognition. Selective attention to segments is controlled based on their saliency, closedness and attention bias. Attended segments in visual working memory are perceptually organized according to a law of proximity. Experiments were conducted by using images of plural categories in an image database and it was shown that selective attention was frequently turned to objects of those categories and that part segments of objects or salient context of objects were perceptually organized.KeywordsVisual AttentionSelective AttentionAttention BiasPerceptual OrganizationMultivariate Gaussian DistributionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.