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Limits of visual awareness

Published 24 August 2007, 09:00 PM

When we briefly examine a scene visually, we can pay attention only to one color at a time. However, we can see it in multiple locations.

New research by Liqiang Huang et al. proves the unexpected fact that our rich visual experience appears to be a substantial overestimation of what we are actually perceiving. We think we are aware of a complex world of varied colors, shapes, and directions of motions, etc. but in fact in any given instant we can see only one color.

What we see is what we can retrieve from visual memory, which does not contain a single image or frame, but what we have perceived in a number of different instants. For example, if we consider a small number of colored monochrome disks on a neutral surface, then if they disks have all the same color, in an instant we can determine that color and the disk's position. If the disks are in more than a single color, then in an instant we can see the disk's locations, but not their colors.

The two experiments required to prove this are not simple and are reported in Science Magazine of 10 August 2007: Vol. 317. no. 5839, pp. 823 - 825. They require to determine what the informational content of any single momentary act of conscious perception is.

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Posted By GiordanoBeretta | 1 Comments | Trackbacks | Permalink
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Researchers at MIT have developed 2 measures of visual clutter: the Feature Congestion measure, and the Subband Entropy measure. They have also released the associated Matlab code used in their project. See the links below.

Feature Congestion metric: This measure of visual clutter is based on the common experience of going to put a note on a colleague's desk. If the desk is uncluttered, it's easy to find a place to put the note where we are confident our colleague will notice it. However, if the desk is cluttered, we tend not to be confident they will notice the note, and perhaps will leave the note on a chair so they will spot it. This suggests that clutter is related to the difficulty in adding an attention-grabbing item to a display. Visual search models typically attempt to predict the difficulty of searching for a particular target among particular distractors. However, our Statistical Saliency Model can easily make the dual prediction of how difficult it would be to add an attention-grabbing item to a display, and what features that item should have in order to draw attention. Our Feature Congestion measure of visual clutter is based upon this model of visual search.

Subband Entropy metric : This measure of visual clutter is based upon the intuition that a scene or display is less cluttered the more "organized" it is, i.e. the more items "group" together perceptually, whether through use of similar colors, or alignment, or other tricks. A related question to ask is to what extent each part of the display or scene is predictable from the rest of the scene? How redundant is the visual information in the scene?

With more organization, and thus more redundancy, the brain (or a computer) can represent an image with a more efficient encoding, which maintaining image quality. This suggests that the more cluttered an image, the more bits it should take to encode that image with something like JPEG2000. In fact, the Subband Entropy measure developed out of our observation that JPEG compressed file size was highly correlated with the Feature Congestion measure described above.

The Subband Entropy measure of visual clutter is based upon these observations and intuitions. It decomposes an image into wavelet subbands, much like the decomposition early in the visual system. It then computes the entropy in each subband, and combines these to get total clutter for a given image or display.

Here are links to the supporting information:

Press release ... http://web.mit.edu/newsoffice/2007/clutter-0821.html

Matlab code ... http://dspace.mit.edu/handle/1721.1/37593

Associated paper ... http://www.journalofvision.org/7/2/17/Rosenholtz-2007-jov-7-2-17.pdf

# Wednesday, August 29, 2007 04:57 PM by RocketRoo

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