4,059 research outputs found
IPE895028 MagicWandMovie3 - Supplemental material for Dynamic Amodal Completion Through the Magic Wand Illusion
No full textSupplemental material, IPE895028 MagicWandMovie3 for Dynamic Amodal Completion Through the Magic Wand Illusion by Christopher W. Tyler in i-Perception</p
IPE895028 Supplemental Material - Supplemental material for Dynamic Amodal Completion Through the Magic Wand Illusion
No full textSupplemental material, IPE895028 Supplemental Material for Dynamic Amodal Completion Through the Magic Wand Illusion by Christopher W. Tyler in i-Perception</p
Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience
No full textSymmetry detection is an interesting probe of pattern processing because it requires the matching of novel patterns without the benefit of prior recognition. However, there is evidence that prior knowledge of the axis location plays an important role in symmetry detection. We investigated how the prior information about the symmetry axis affects symmetry detection under noise-masking conditions. The target stimuli were random-dot displays structured to be symmetric about vertical, horizontal, or diagonal axes and viewed through eight apertures (1.2u diameter) evenly distributed around a 6u diameter circle. The information about axis orientation was manipulated by (1) cueing of axis orientation before the trial and (2) varying axis salience by including or excluding the axis region within the noise apertures. The percentage of correct detection of the symmetry was measured at for a range of both target and masking noise densities. The threshold vs. noise density function was flat at low noise density and increased with a slope of 0.75–0.8 beyond a critical density. Axis cueing reduced the target threshold 2–4fold at all noise densities while axis salience had an effect only at high noise density. Our results are inconsistent with an ideal observer or signal-to-noise account of symmetry detection but can be explained by a multiple-channel model is which the response in each channel is the ratio between the nonlinear transform of the responses of sets of early symmetry detectors and the sum of external and intrinsic sources of noise
Computer vision : from surfaces to 3D objects / edited by Christopher W. Tyler.
No full textIncludes bibliographical references (p. 219-240) and index.Book fair 2013.xxvi, 250 p. :"The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine object shape; the structural edges have to be encoded in terms of their full 3D spatial configuration. Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of veridical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world.An Unprecedented Framework for Complex Object RepresentationPresenting the material from both computational and neural implementation perspectives, the book covers novel analytic techniques for all levels of the surface representation problem. The cutting-edge contributions in this work run the gamut from the basic issue of the ground plane for surface estimation through mid-level analyses of surface segmentation processes to complex Riemannian space methods for representing and evaluating surfaces.State-of-the-Art 3D Surface and Object RepresentationThis well-illustrated book takes a fresh look at the issue of 3D object representation. It provides a comprehensive survey of current approaches to the computational reconstruction of surface structure in the visual scene"--Provided by publisher."Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of vertical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world. Leading theorists cover full 3D scene reconstruction, instead of the simplistic 2D planar algorithms employed in the past. They explore cutting-edge research on computational algorithms for scene analysis and present an integrated, complementary treatment of neural, behavioral, mathematical, and computational approaches. The text includes numerous graphics of complex processes, with many in color"--Provided by publisher
Excitatory and inhibitory interaction fields of flankers revealed by contrast-masking functions
No full textTo study spatial interactions corresponding to the non-classical receptive field organization for human vision, we used a dual-masking paradigm to measure how target contrast discrimination can be affected by the relative location of the flankers. The observers’ task was to detect a 4 cycle/deg vertical Gabor superimposed on a matching Gabor pedestal in the presence of vertical Gabor flankers. The flankers were either (i) collinear with the target and varying in distance or (ii) at a fixed distance from the target but with varying in location relative to the vertical axis. Compared with the no-flanker condition, the collinear flankers decreased target threshold at low pedestal contrasts (facilitation) and increased threshold at high contrasts (suppression). The low contrast facilitation increased with distance up to 4 wavelengths and decreased beyond that. Both facilitative and suppressive flanker effects were greatest at the collinear location and decreased monotonically as flanker location deviated from the collinear axis. These flanker effects are modeled with our sensitivity modulation model, which suggests that the flanker effects are multiplicative terms applied to both the excitatory and inhibitory terms of a divisive inhibition response function. The model parameters show that the facilitative flanker effect is narrowly tuned in space. The data are not compatible with a model of additive normalization by the pedestal contrast or with
the uncertainty model
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