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I am a NOMIS Foundation Fellow of the Italian Academy for Advanced Studies at Columbia University leading the "New Approach to 3D Vision" Project with the generous support of the NOMIS Foundation. I am also a Presidential Scholar in Society and Neuroscience at Columbia University, and an Affiliate of Niko Kriegeskorte's Visual Inference Lab at the Zuckerman Mind Brain Behavior Institute. I am the author of the book The Perception and Cognition of Visual Space (Palgrave, 2017), the organiser of the Royal Society meeting New Approaches to 3D Vision, and the lead editor of the accompanying Philosophical Transactions of the Royal Society B volume. Previously, I have been a Research Fellow at the Centre for Applied Vision Research, City, University of London, a Law Tutor at St Hilda's College, Oxford University, a Teaching Fellow in Philosophy at University College London, and Research Intern at Meta Reality Labs. Email / CV / Google Scholar / LinkedIn / Twitter |
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Single author book arguing that 3D vision is a two stage process that involves the extraction of depth from stereo vision (at the level of perception) before the integration of stereo vision with other depth cues (at the level of cognition).
Reviewed in Perception by Casper Erkelens (former Head of Physics at Utrecht) as "a valuable contribution to the scientific literature on visual perception." Featured on the Brains Blog, the leading online forum for cognitive science.
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Royal Society meeting bringing together researchers in Computer Vision, Animal Navigation, and Human Vision, to better understand what is the most appropriate representation for 3D vision? Over 800 people participated, with speakers from DeepMind, Google Robotics, Meta (Facebook) Reality Labs, and Microsoft Research. Talks and abstracts available on the Royal Society meeting website. |
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Traditionally, it's thought that 3D vision relies on recreating an accurate 3D model of the world. The new approaches to 3D vision explored in this volume challenge this assumption. Instead, they investigate the possibility that computer vision, animal navigation, and human vision can rely on partial or distorted models, or no model at all. This theme issue also highlights the implications for artificial intelligence, autonomous vehicles, human perception in virtual and augmented reality, and the treatment of visual disorders, all of which are explored by individual articles. |
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Competitively selected response to Bowers et al. (2022), ‘Deep Problems with Neural Network Models of Human Vision’ in Behavioral and Brain Sciences, explaining how AI can contribute to our understanding of human vision |
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Introduction to our Royal Society volume arguing that Computer Vision, Animal Navigation, and Human Vision, are currently grappling with the same qustion, namely what is the most appropriate representation for 3D vision? Draws parallels between the solutions the different disciplines adopt, and questions for future research. |
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If my experimental work argues the visual system doesn’t know the rotation of the eyes (the ‘vergence’ signal), then my theoretical work argues that the visual system doesn’t even know the two eyes are in different locations. This leads me to develop a new theory of visual scale and visual shape, which is focused on resolving this tension, rather than trying to estimate the distance and shape of objects in the world. |
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The closer an object is, the more the eyes have to rotate to fixate on it. This mechanism (known as 'vergence') is thought to provide critically important distance information. However, in this paper I test vergence as a distance cue divorced from other sources of distance information, and find it provides no useful distance information. Featured on the Psychonomic Society's "All Things Cognition" podcast. |
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Vergence eye movements are also thought to play an essential role in size perception, in a process known as “size constancy”, which enables us to differentiate a small object up close from a large object far away, even though both cast the same retinal image. I develop a new paradigm to demonstrate that this effect does not exist once cognitive influences (subjective knowledge about changes in distance) have been controlled for. Invited for a special issue on Size Constancy in Perception and Action edited by Mel Goodale FRS and Robert Whitwell. |
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In Linton (2020) and Linton (2021) I find that vergence has either a negligible or no effect on size and distance perception. The question is how to reconcile this finding with the processing of the vergence signal in the primary visual cortex (V1). I argue that we need to distinguish between perceptual and cognitive processing in V1, and draw an analogy with findings on non-visual processing in the mouse V1. Special issue on Consciousness Science and Its Theories. Contributors include Stanislas Dehaene, Catherine Tallon-Baudry, Biyu Jade He, and Axel Cleeremans. |
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Debate in PNAS with Jorge Morales, Axel Bax, and Chaz Firestone on 3D shape processing in response to Morales et al. (2020). ‘Sustained representation of perspectival shape’, PNAS, 117(26), 14873-82. Provided inspiration for new experiments in Morales et al. (2021). ‘Reply to Linton: Perspectival interference up close’, PNAS, 118 (28) e2025440118. |
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Collaborated closely with researchers in deep learning, computer graphics, and optics, as part of a small interdisciplinary team, using artificial intelligence for real-time gaze-contingent defocus blur rendering. Used principles of vision science to inform the development of neural network. Ran user studies to evaluate neural network and make actionable recommendations. |
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In contemporary virtual reality displays, the scene is static despite eye movements by the observer. This can cause a problem because the centre of projection of the eye (the nodal point) and the centre of rotation of the eye are off-set relative to one another. I was the first to propose updating the camera frustum in virtual reality with eye movements to control for these distortions. |
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Thanks to Jon Barron for the html template |