Abstract


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Click to download PDF version Click to download BibTeX data Clik to view abstract D. Walther, L. Itti, M. Riesenhuber, T. Poggio, C. Koch, Attentional Selection for Object Recognition - a Gentle Way, In: Lecture Notes in Computer Science, Vol. 2525, pp. 472-479, Nov 2002. (Cited by 260)

Abstract: Attentional selection of an object for recognition is often modeled using all-or-nothing switching of neuronal connection pathways from the attended region of the retinal input to the recognition units. However, there is little physiological evidence for such all-or-none modulation in early areas. We present a combined model for spatial attention and object recognition in which the recognition system monitors the entire visual field, but attentional modulation by as little as 20 percent at a high level is sufficient to recognize multiple objects. To determine the size and shape of the region to be modulated, a rough segmentation is performed, based on preattentive features already computed to guide attention. Testing with synthetic and natural stimuli demonstrates that our new approach to attentional selection for recognition yields encouraging results in addition to being biologically plausible.

Themes: Computational Modeling, Model of Bottom-Up Saliency-Based Visual Attention, Computer Vision

 

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