ArticleJournal of imaging2021
A Cortical-Inspired Sub-Riemannian Model for Poggendorff-Type Visual Illusions.
Article in Journal of imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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Who cites it
3 citing papers in PubMed.
- Diffusion-Shock PDEs for Deep Learning on Position-Orientation Space.Journal of mathematical imaging and vision · 2026Article
- A Cortical-Inspired Contour Completion Model Based on Contour Orientation and Thickness.Journal of imaging · 2024Article
- Multi-Frequency Image Completion via a Biologically-Inspired Sub-Riemannian Model with Frequency and Phase.Journal of imaging · 2021Article
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Authors and funding
4 authors.
Funding
Abstract
We consider Wilson-Cowan-type models for the mathematical description of orientation-dependent Poggendorff-like illusions. Our modelling improves two previously proposed cortical-inspired approaches, embedding the sub-Riemannian heat kernel into the neuronal interaction term, in agreement with the intrinsically anisotropic functional architecture of V1 based on both local and lateral connections. For the numerical realisation of both models, we consider standard gradient descent algorithms combined with Fourier-based approaches for the efficient computation of the sub-Laplacian evolution. Our numerical results show that the use of the sub-Riemannian kernel allows us to reproduce numerically visual misperceptions and inpainting-type biases in a stronger way in comparison with the previous approaches.
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Registered trials
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