Combining bottom-up and top-down attentional influences

Visual attention to salient and relevant scene regions is crucial for an animal's survival in the natural world. It is guided by a complex interplay of at least two factors: image-driven, bottom-up salience [1] and knowledge-driven, top-down guidance [2, 3]. For instance, a ripe red fruit among green leaves captures visual attention due to its bottom-up salience, while a non-salient camou aged predator is detected through top-down guidance to known predator locations and features. Although both bottom-up and top-down factors are important for guiding visual attention, most existing models and theories are either purely top-down [4] or bottom-up [5, 6]. Here, we present a combined model of bottom-up and top-down visual attention.

[1]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[2]  Walter Schneider,et al.  Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. , 1977 .

[3]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[4]  H. Pashler Target-distractor discriminability in visual search , 1987, Perception & psychophysics.

[5]  J. Duncan,et al.  Visual search and stimulus similarity. , 1989, Psychological review.

[6]  A. Nagy,et al.  Critical color differences determined with a visual search task. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[7]  A. Treisman Search, similarity, and integration of features between and within dimensions. , 1991, Journal of experimental psychology. Human perception and performance.

[8]  Michael D'Zmura,et al.  Color in visual search , 1991, Vision Research.

[9]  K. Nakayama,et al.  Priming of pop-out: I. Role of features , 1994, Memory & cognition.

[10]  John K. Tsotsos,et al.  Modeling Visual Attention via Selective Tuning , 1995, Artif. Intell..

[11]  W. Cowan,et al.  Visual search for colour targets that are or are not linearly separable from distractors , 1996, Vision Research.

[12]  C. Koch,et al.  A saliency-based search mechanism for overt and covert shifts of visual attention , 2000, Vision Research.

[13]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[14]  G W Humphreys,et al.  Driving attention with the top down: The relative contribution of target templates to the linear separability effect in the size dimension , 2001, Perception & psychophysics.

[15]  Rajesh P. N. Rao,et al.  Eye movements in iconic visual search , 2002, Vision Research.

[16]  N. P. Bichot,et al.  Priming in Macaque Frontal Cortex during Popout Visual Search: Feature-Based Facilitation and Location-Based Inhibition of Return , 2002, The Journal of Neuroscience.

[17]  J. Wolfe,et al.  Changing your mind: on the contributions of top-down and bottom-up guidance in visual search for feature singletons. , 2003, Journal of experimental psychology. Human perception and performance.

[18]  G. Humphreys,et al.  Inhibition and anticipation in visual search: Evidence from effects of color foreknowledge on preview search , 2003, Perception & psychophysics.

[19]  Naomi M. Kenner,et al.  How fast can you change your mind? The speed of top-down guidance in visual search , 2004, Vision Research.

[20]  Yuhong Jiang,et al.  Setting up the target template in visual search. , 2005, Journal of vision.

[21]  Laurent Itti,et al.  Optimal cue selection strategy , 2005, NIPS.