Top-Down Object Biased Attention Using Growing Fuzzy Topology ART

In this paper, we propose a top-down object biased attention model which is based on human visual attention mechanism integrating feature based bottom-up attention and goal based top-down attention. The proposed model can guide attention to focus on a given target object over other objects or feature based salient areas by considering both the object preferable bottom-up attention mechanism and the object biased attention mechanism. We proposed a growing fuzzy topology ART that plays important roles for object biased attention, one of which is to incrementally learn and memorize features of arbitrary objects and the other one is to generate top-down bias signal by competing memorized features of a given target object with features of an arbitrary object. Experimental results show that the proposed model performs well in successfully focusing on given target objects, as well as incrementally perceiving arbitrary objects in natural scenes.