Parallel visual computation
Abstract
The functional abilities and parallel architecture of the human visual system are a rich source of ideas about visual processing. Any visual task that we can perform quickly and effortlessly is likely to have a computational solution using a parallel algorithm. Recently, several such parallel algorithms have been found that exploit information implicit in an image to compute intrinsic properties of surfaces, such as surface orientation, reflectance and depth. These algorithms require a computational architecture that has similarities to that of visual cortex in primates.
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Minimizing free energy maximizes the Bayesian evidence for the generative model.
“minimizing free energy maximizes the Bayesian evidence for the generative model (Ballard et al., 1983; Hinton and van Camp, 1993; Dayan et al., 1995)”
From The Computational Anatomy of Psychosis (2013) · cites this paper as Ballard et al., 1983
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“This means that minimizing free energy maximizes the Bayesian evidence for the generative model (Ballard et al., 1983; Hinton and van Camp, 1993; Dayan et al., 1995).”
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- Authors
- Ballard, D. H., Hinton, G. E., & Sejnowski, T. J.
- Affiliations
- University of Rochester (US)
- Carnegie Mellon University (US)
- Venue
- Nature
- Published
- 1983-11
- Volume
- 306
- Issue
- 5938
- Pages
- 21-26
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1981025738
- Cited by
- 356
- References
- 2
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 1 · 2022: 1 · 2021: 5 · 2020: 2 · 2019: 3 · 2018: 2 · 2017: 4 · 2016: 7 · 2015: 2 · 2014: 8 · 2013: 4 · 2012: 9
- FWCI
- 36.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- human visual system, parallel algorithms, surface orientation, reflectance estimation, depth perception, visual cortex, computational architecture
- MeSH terms
- Computers, Depth Perception, Humans, Models, Theoretical, Surface Properties, Visual Cortex, Visual Pathways, Visual Perception
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