How Visual Attention and Suppression Facilitate Object Recognition?

Abstract. Visual attention can support object recognition by selecting the relevant target information in the huge amount of sensory data, especially important in scenes composed of multiple objects. Here we demonstrate how attention in a biologically plausible and neuro-computational model of visual perception facilitates object recognition in a robotic real world scenario. We will point out that it is not only important to select the target information, but rather to explicitly suppress the distracting sensory data. We found that suppressing the features of each distractor is not sufficient to achieve robust recognition. Instead, we also have to suppress the location of each distractor. To demonstrate the effect of this spatial suppression, we disable this property and show that the recognition accuracy drops. By this, we show the interplay between attention and suppression in a real world object recognition task