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research:texture [2010/06/09 23:05]
kimo
research:texture [2010/06/10 15:14] (current)
rosenholtz
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-====== Texture Perception ======+====== Ruth Rosenholtz ====== 
 +=== Texture Perception ===
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-===== It's not just for segmentation and shape from texture ===== +===== It's Not Just for Segmentation and Shape from Texture =====
In the past, texture perception has largely been studied because changes in texture can signal either a boundary between objects (texture segmentation) or a change in orientation of a surface (shape from texture).  While we have studied these problems, we also believe that texture perception gives us insight into a broader class of visual phenomena, including visual crowding, visual search, object recognition, and set perception. In the past, texture perception has largely been studied because changes in texture can signal either a boundary between objects (texture segmentation) or a change in orientation of a surface (shape from texture).  While we have studied these problems, we also believe that texture perception gives us insight into a broader class of visual phenomena, including visual crowding, visual search, object recognition, and set perception.
===== Understanding Texture Perception is Critical for Understanding Visual Crowding, Visual Search, and Perhaps Perception in General ===== ===== Understanding Texture Perception is Critical for Understanding Visual Crowding, Visual Search, and Perhaps Perception in General =====
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(More detail, and pictures, to follow shortly.  Work done in conjunction with [[:people:benjamin_balas|Benjamin Balas]], [[:people:alvin_raj|Alvin Raj]], Lisa Nakano, [[:people:livia_ilie|Livia Ilie]], Ronald van den Berg, and Stephanie Chan.) (More detail, and pictures, to follow shortly.  Work done in conjunction with [[:people:benjamin_balas|Benjamin Balas]], [[:people:alvin_raj|Alvin Raj]], Lisa Nakano, [[:people:livia_ilie|Livia Ilie]], Ronald van den Berg, and Stephanie Chan.)
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===== Set Perception ===== ===== Set Perception =====
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(Work done in conjunction with George Alvarez.) (Work done in conjunction with George Alvarez.)
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Is the human visual system designed to compute statistical tests like t-tests?  Experiments and modeling in our lab show that this is a good model of a range of “pre-attentive” texture segmentation results.  In this model, the visual system first extracts the equivalent of mean and variance of various features like orientation on each side of a candidate texture boundary.  The variance includes internal noise in the feature estimates, which may depend upon the viewing time as well as the expertise of the observer.  The size of the area over which these statistics are computed seems more inherent to the system, as we have found it varies little between observers.  The observer then detects a texture boundary if the equivalent of a t-test reveals a “significant” difference between the samples on the two sides of the boundary. Is the human visual system designed to compute statistical tests like t-tests?  Experiments and modeling in our lab show that this is a good model of a range of “pre-attentive” texture segmentation results.  In this model, the visual system first extracts the equivalent of mean and variance of various features like orientation on each side of a candidate texture boundary.  The variance includes internal noise in the feature estimates, which may depend upon the viewing time as well as the expertise of the observer.  The size of the area over which these statistics are computed seems more inherent to the system, as we have found it varies little between observers.  The observer then detects a texture boundary if the equivalent of a t-test reveals a “significant” difference between the samples on the two sides of the boundary.
-==== Bibliography ====+== Bibliography ==
    *  C. H. Attar, K. Hamburger, R. Rosenholtz, H. Gotzl, & L. Spillman, "Uniform versus random orientation in fading and filling-in" Vision research, 47(24), 3041-3051, 2007.     *  C. H. Attar, K. Hamburger, R. Rosenholtz, H. Gotzl, & L. Spillman, "Uniform versus random orientation in fading and filling-in" Vision research, 47(24), 3041-3051, 2007.
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Shape from texture, then, is not so different from structure from motion or from binocular stereopsis.  In motion two frames give slightly different views of the same surface, allowing estimation of shape.  In stereopsis, it is the two eyes that give the two different views.  In shape from texture, the statistical homogeneity of the texture allows us to get two views of the same texture with a single image, thus estimating the shape.  With this view, techniques for dealing with multiple motions in a single image can also deal with multiple textures, e.g. a view of grass through the slats of a fence. Shape from texture, then, is not so different from structure from motion or from binocular stereopsis.  In motion two frames give slightly different views of the same surface, allowing estimation of shape.  In stereopsis, it is the two eyes that give the two different views.  In shape from texture, the statistical homogeneity of the texture allows us to get two views of the same texture with a single image, thus estimating the shape.  With this view, techniques for dealing with multiple motions in a single image can also deal with multiple textures, e.g. a view of grass through the slats of a fence.
-==== Bibliography ====+== Bibliography ==
    *  J. Malik & R. Rosenholtz, "Computing local surface orientation and shape from texture for curved surfaces." International Journal of Computer Vision 23(2):149-168, 1997.     *  J. Malik & R. Rosenholtz, "Computing local surface orientation and shape from texture for curved surfaces." International Journal of Computer Vision 23(2):149-168, 1997.
 
research/texture.1276139111.txt.gz · Last modified: 2010/06/09 23:05 by kimo