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Human vision and its applications

We study human vision, including such topics as visual search, peripheral vision, perceptual organization, set perception, and the impact of visual clutter on task performance.   We take a three-pronged approach: 1) Computational modeling (computer vision-based, ideal observers, Monte Carlo simulations, and neurobiologically-inspired); 2) Behavioral experiments; and 3) Applying our models and understanding of human vision to applications such as image compression, design of user interfaces, and design of information visualizations.

How do we decide where to look next in an image?  How do we interpret the visual input as composed of meaningful parts and objects?  A repeated theme in the work of the lab is that of the visual system as statistician: The visual system represents the visual input via noisy and uncertain feature estimates, and in many cases computes summary statistics such as the mean and variance of those features.  Based upon these "descriptive statistics," the visual system makes intelligent inferences about the world, and participates in intelligently planning what actions to take.  

Models of this form have proven quite powerful in predicting behavior at visual tasks, such as visual search and image segmentation.  Our more recent work suggests that the visual system may represent peripheral stimuli not through the exact configuration of their parts, but rather through the joint statistics of responses of V1-like receptive fields.  This model of the information available in peripheral vision shows promise at being able to predict a wide variety of visual phenomena, from time to find a target in a complex display through the perception of optical illusions.

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R. Rosenholtz, N. R. Twarog, N. Schinkel-Bielefeld, & M. Wattenberg, " An intuitive model of perceptual grouping for HCI design. " SIGCHI 2009, 1331-1340, 2009.

R. Rosenholtz, " Search asymmetries? What search asymmetries? " Perception & Psychophysics, 63 (3), 476-489, 2001.

R. Rosenholtz, A.L. Nagy, N. R. Bell, " The effect of background color on asymmetries in color search. " Journal of Vision, 4 (3), Article 9, 224-240, 2004.

R. Rosenholtz, Y. Li, and L. Nakano" Measuring visual clutter ". Journal of Vision, 7(2):17, 1-22, 2007.

R. Rosenholtz, Y. Li, J. Mansfield, Z. Jin, " Feature Congestion: a measure of display clutter ." SIGCHI 2005 , 761-770, 2005.

C. H. Attar, K. Hamburger, R. Rosenholtz, H. Gotzl, and L. Spillman, "Uniform versus random orientation in fading and filling-in" Vision research, 47(24), 3041-3051, 2007.

R. Rosenholtz, " Significantly different textures: A computational model of pre-attentive texture segmentation. "  Proc. European Conference on Computer Vision, D. Vernon (Ed.), Springer Verlag, LNCS 1843, Dublin, Ireland, pp. 197-211, June 2000.

A. Woodruff, R. Rosenholtz, J. Morrison, A. Faulring, & P. Pirolli, " A comparison on the use of text summaries, plain thumbnails, and enhanced thumbnails for web search tasks ." Journal of the American Society for Information Science and Technology, 53 (2), 172-185, 2002.

B. Suh, A. Woodruff, R. Rosenholtz, A. Glass, " Popout Prism: Adding perceptual principles to overview+detail document interfaces ." SIGCHI 2002 , 251-258, 2002.