Topographic Product Models Applied to Natural Scene Statistics

Topographic Product Models Applied to Natural Scene Statistics

We present an energy-based model that uses a product of generalized Student-t distributions to capture the statistical structure in data sets. This model is inspired by and particularly applicable to "natural" data sets such as images. We begin by providing the mathematical framework, where we discuss complete and overcomplete models and provide algorithms for training these models from data. U...

Modelling the Statistics of Natural Images with Topographic Product of Student-t Models

We present an energy-based model that uses a product of generalised Student-t distributions to capture the statistical structure in datasets. This model is inspired by and particularly applicable to “natural” datasets such as images. We begin by providing the mathematical framework, where we discuss complete as well as undercomplete

Subjective randomness and natural scene statistics.

Accounts of subjective randomness suggest that people consider a stimulus random when they cannot detect any regularities characterizing the structure of that stimulus. We explored the possibility that the regularities people detect are shaped by the statistics of their natural environment. We did this by testing the hypothesis that people's perception of randomness in two-dimensional binary ar...

From natural scene statistics to models of neural coding and representation ( part 2 )

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics

Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics,...