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Talk Videos from BMVA Symposium: 3D worlds from 2D

January 29, 2020. United Kingdom, London
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About the Event

When humans view a photograph they perceive the 3D world that constructed the image. They can, for example, describe the depth relationships between objects, plan a route through the scene and imagine the scene from a different viewpoint. This process is automatic and compulsive. For example, even though humans possess size constancy they will readily misinterpret the size of a person in order to make sense of the rest of the scene as a 3D world. State of the art computer vision systems are now also very good at reconstructing 3D layout from 2D images (3D uplift) although, unlike humans, this is often restricted to specific domains or requires multiple views. This workshop will consider recent developments in 3D uplift as well as our current knowledge of scene understanding in human vision.
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Featured Speakers

Paul Linton

Research Fellow in Visual Neuroscience at University of London
My research focuses on 3D visual experience. In my PhD I demonstrated that the visual system does not appear to use vergence (the angular rotation of the eyes) to triangulate the size and distance of objects. This work has significant implications for visual scale, binocular disparity processing, multisensory integration, and object interaction. In my book The Perception and Cognition of Visual Space (Palgrave, 2017), I explore inconsistencies in the 3D vision literature and argue that there are still important gaps between leading theories and our visual experience. I initiated, and I am now co-organising, a Royal Society meeting on “New Approaches to 3D Vision” with representatives from Facebook Reality Labs, Google DeepMind, Google Robotics, and Microsoft Research. As an Intern at Facebook Reality Labs, I collaborated with deep learning and computer graphics researchers to study naturalistic real-time gaze-contingent defocus blur (the DeepFocus project). Before vision science I was a Stipendiary Lecturer in Law at St Hilda’s College Oxford, and a Teaching Fellow at University College London.

Will Smith

Dept. Computer Science at University of York
I am a Reader (Associate Professor++) in the Vision, Graphics and Learning (VGL) research group in the Department of Computer Science, University of York. I was a Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow from 2019-2020. I am an Associate Editor of the journal Pattern Recognition.

My research interests span vision, graphics and ML. Specifically, physics-based and 3D computer vision, shape and appearance modelling and the application of statistics and machine learning to these areas. The application areas in which I most commonly work are face/body analysis and synthesis, surveying and mapping, object capture and inverse rendering. A wide variety of tools and areas of maths are often useful in my research such as: convex optimisation, nonlinear optimisation, manifold learning, learning/optimisation on manifolds, computational geometry and low level computer vision (e.g. features and correspondence). I lead a team of five PhD students and one postdoc. I have published over 100 papers, many in the top conferences and journals in the field.

Johannes Burge

Assistant Professor of Psychology at University of Pennsylvania
Specialties: research, computational models, human vision, human perception, human behavior, Bayesian statistics, computer vision, image processing, neuroscience, 3D displays, information processing, data analysis
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Paul Linton
Research Fellow in Visual Neuroscience at University of London
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BMVA Symposium 3D worlds from 2D Paul Linton, Does Human Vision Triangulate Absolute Distance

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James Elder
Professor & York Research Chair in Human and Computer Vision at York University
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BMVA Symposium 3D worlds from 2D - James Elder

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Robert Black
RealSpace
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BMVA Symposium 3D worlds from 2D Robert Black, RealSpace, ‘Paradoxical’ Bi Ocular Stereoscopy

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