= PDF Reprint, = BibTeX entry, = Online Abstract
L. Itti, Quantitative analysis of perceptual salience at the point of gaze in humans and monkeys, Workshop on Natural Environments, Taska, and Intelligence (NETI), Austin, Texas, Mar 2008.
Abstract: Visual processing of complex natural environments requires animals to combine, in a highly dynamic and adaptive manner, sensory signals that originate from the environment (bottom-up) with behavioral goals and priorities dictated by the task at hand (top-down). In the visual domain, bottom-up and top-down guidance of attention towards salient or behaviorally relevant targets have both been studied and modeled extensively. More recently, the interaction between bottom-up and top-down control of attention has also become of topic of interest. A number of neurally-inspired computational models have emerged which integrate components for the computation of bottom- up salience maps, top-down attention biasing, rapid computation of the 'gist' or rough context of a scene, objet recognition, and some higher-level cognitive reasoning functions. I will review a number of such efforts, which aim at building models that can both process real-world inputs in robust and flexible ways, and perform cognitive reasoning on the symbols extracted from these inputs. I will draw from examples in the biological/computer vision fields, including algorithms for complex scene understanding, robot navigation, and animation of virtual humans.
Themes: Model of Bottom-Up Saliency-Based Visual Attention, Model of Top-Down Attentional Modulation, Computational Modeling
Copyright © 2000-2007 by the University of Southern California, iLab and Prof. Laurent Itti.
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