Edge co-occurrence in natural images predicts contour grouping performance.

By Wilson S. Geisler, Jeffrey S. Perry, B. Super, D. P. Gallogly. Vision Research, 2001

712 citations recorded by the source corpus.

Subfields: Biophysics, Cognitive Neuroscience, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/5777e5fb5d0c00aa9e6a8edc8893f174486a235d

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In Biophysics

In Cognitive Neuroscience

In Computer Vision and Pattern Recognition

Citations in the corpus

Cardinal rules: Visual orientation perception reflects knowledge of environmental statistics (2011, methodology): “The Bayesian framework provides a quantitative formulation of the inference problem and has been used to explain aspects of human perceptio”
Natural image statistics and neural representation. (2001, methodology): “Geisler et al (2001) examined empirical distributions of the dominant orientations at nearby locations and used them to predict psychophysical performance on a contour detection task.”
Natural signal statistics and sensory gain control (2001, background): “For example, oriented structures in images (such as edges of objects) tend to extend along smooth contours, yielding strong responses in linear Þlters that are separated from each other spatially, but lying along the same contour (see also [26, 27]).”
Statistical Modeling and Conceptualization of Visual Patterns (2003, background): “Going beyond pixel statistics, some most recent work measured the statistics of object shapes [96], contours [ 32 ], and the size of regions and objects in natural images [4].”
Seven Challenges in Image Quality Assessment: Past, Present, and Future Research (2013, background): “Other studies, focused on modeling the statistics of natural scenes, have revealed properties such as 1/f amplitude spectra [292, 299] (where f denotes spatial frequency) and the importance of phase [300, 301] and edge cooccurrences [109] in perception.”
Visual perception and the statistical properties of natural scenes. (2008, background): “One way to match the dynamic range of responses with that of the input signals is via histogram equalization: Adjust the shape of the neuron’s response function so that all response levels occur equally often under natural stimulus conditions.”
A Century of Gestalt Psychology in Visual Perception I. Perceptual Grouping and Figure-Ground Organization (2012, background): “Geisler et al. (2001) treated contours as unordered sets of oriented elements, measuring the statistics for pairs of contour elements on a common object boundary, regardless of whether these element pairs were close together or far apart on the object contour.”