An established researcher in the area of early vision proposes to use psychophysical and computational methods to study grouping, segregation, and contour integration in multi-element patterns.
Specific aims i nclude: 1) the measurement of pairwise trading relationships in grouping strength for symmetry (e.g. how does spatial proximity interact with symmetry in grouping tasks?) 2) comparison of filter vs. structure-based models of grouping and segregation 3) testing of different models of contour integration, 4) measurements of eccentricity effects in texture segregation, 5) modeling of the mechanisms of perceptual organization in perception of complex images. The bulk of the data will be collected with a three element display. The subject's task will be to determine if the center item groups more strongly with the left or right flanking item. In other tasks (e.g. section 4.2) Ss will identify the orientation of a texture patch. A model of grouping is proposed starting with filtering by simple cells as previously modeled by Albrecht and Geisler. A second, """"""""transformational"""""""" matching stage allows for similar items to be grouped together. In a complex image, the plan is to have receptive field matching generate a first set of primitives that can be grouped. These groups are then subject to transformational mapping and higher-order groupings can be based on the results of that operation. Grouping is based on a variety of grouping rules (e.g. figure-ground grouping, associative grouping - a principle that holds that if A and B group and B and C group than A and C will group). The model asserts that grouping can be """"""""multi-level"""""""" though it is admitted that """"""""our current understanding of multiple-level grouping"""""""" is in a rather primitive state.
|Wang, Jiaxing; Struebing, Felix L; Ferdous, Salma et al. (2018) Differential Exon Expression in a Large Family of Retinal Genes Is Regulated by a Single Trans Locus. Adv Exp Med Biol 1074:413-420|
|Geisler, Wilson S (2018) Psychometric functions of uncertain template matching observers. J Vis 18:1|
|Sebastian, Stephen; Geisler, Wilson S (2018) Decision-variable correlation. J Vis 18:3|
|Kim, Seha; Burge, Johannes (2018) The lawful imprecision of human surface tilt estimation in natural scenes. Elife 7:|
|Michel, Melchi M; Chen, Yuzhi; Seidemann, Eyal et al. (2018) Nonlinear Lateral Interactions in V1 Population Responses Explained by a Contrast Gain Control Model. J Neurosci 38:10069-10079|
|McCann, Brian C; Hayhoe, Mary M; Geisler, Wilson S (2018) Contributions of monocular and binocular cues to distance discrimination in natural scenes. J Vis 18:12|
|Sebastian, Stephen; Abrams, Jared; Geisler, Wilson S (2017) Constrained sampling experiments reveal principles of detection in natural scenes. Proc Natl Acad Sci U S A 114:E5731-E5740|
|Jaini, Priyank; Burge, Johannes (2017) Linking normative models of natural tasks to descriptive models of neural response. J Vis 17:16|
|Burge, Johannes; McCann, Brian C; Geisler, Wilson S (2016) Estimating 3D tilt from local image cues in natural scenes. J Vis 16:2|
|Burge, Johannes; Geisler, Wilson S (2015) Optimal speed estimation in natural image movies predicts human performance. Nat Commun 6:7900|
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