Computer vision is the problem of understanding or extracting useful information from images, for example, reconstructing 3D models or recognising objects and faces. Computer graphics is the problem of creating realistic images or models, for example for use in video games or movie visual effects. Graphics and vision both require a good understanding of how 2D images are formed of the 3D world.

Contact us

Dr Will Smith

Dr Will Smith

Vision, Graphics and Learning Research Group lead

william.smith@york.ac.uk

Related links

VGL Google site

 

Computer vision is the problem of understanding or extracting useful information from images, for example, reconstructing 3D models or recognising objects and faces. Computer graphics is the problem of creating realistic images or models, for example for use in video games or movie visual effects. Graphics and vision both require a good understanding of how 2D images are formed of the 3D world. Some aspects of this process can be modelled using ideas from physics, such as, the way in which light reflects from different materials and how 3D points project to points in a 2D image. However, describing every part of this hugely complex process in enough detail to produce photorealistic images quickly becomes impossible. 

This is where machine learning becomes useful. We have access to almost unlimited amounts of visual data: for example, the images and videos uploaded to the internet captured in real world conditions by casual photographers. We can use this data to learn patterns, rules or useful assumptions that make our task easier. For example, in neural rendering we can train a system to add details to an image that bridges the gap between computer graphics and a real photograph.

We are interested in sensing and the acquisition of images themselves. We are interested in using new sensing modalities (such as polarisation cameras, 3D scanners and MRI scanners) or controlled acquisition setups (such as light stages and multispectral illumination) for interrogating shape, structure and material properties. 

We are also interested in learning from and better understanding how human vision works. If we know humans are able to solve a visual task, it proves that it is possible. By exploring how humans perform the task, we might uncover insights into how a machine can solve the problem. We have investigated questions such as how concepts of memorability and complexity affect human image perception and whether neural representations encode shape information.

Our overarching aim is to advance the state of the art in the principled analysis (vision) and synthesis (graphics) of visual data. We develop new algorithms and techniques that combine explicit modelling of the geometry and photometry of the image formation process with data-driven statistical and machine learning. In terms of the specific problems and applications the group work on, our main objectives are to advance knowledge in:

  1. Capture, synthesis and modelling of human faces and bodies
  2. Physics-based computer vision
  3. Analysis-by-synthesis, differentiable rendering and neural rendering
  4. Statistical shape modelling and computational geometry
  5. Reflectance modelling and physically-based rendering
  6. Connections between human and machine visual perception
  7. Applications of Computer Vision in Security and Healthcare

We collaborate very closely with commercial partners from a range of industries and with other academic disciplines. In 3D face modelling we work with craniofacial surgeons and dentists to develop new tools for surgical planning and evaluation, diagnosis and ergonomic design. In surveying and mapping we work with road and rail industry partners to automate condition and safety inspections, with glaciologists to understand how glaciers have changed their 3D structure, and with ecologists to understand changes in land use and tree cover. In object and face capture we work with retailers and visual effects studios to create photorealistic renderings of products and actors. We work with psychologists to use vision and graphics techniques to label or synthesise images to understand how the human visual system learns from and processes images.

Group members

PhotoContact details
Dr Adrian Bors 

Dr Adrian Bors

Academic staff

adrian.bors@york.ac.uk

Dr Claudio Guarnera 

Dr Claudio Guarnera

Academic staff

claudio.guarnera@york.ac.uk

Dr Patrik Huber 

Dr Patrik Huber

Academic staff

patrik.huber@york.ac.uk

Dr Nick Pears 

Dr Nick Pears

Academic staff

nick.pears@york.ac.uk

Dr Will Smith 

Dr Will Smith

Academic staff - group lead

william.smith@york.ac.uk

Dr Paulina Lewinska 

Dr Paulina LewiƄska

Research associate

paulina.lewinska@york.ac.uk

Dr Mona Ragab 

Dr Mona Ragab

Research associate

 

Enes Algul

Enes Algul

Postgraduate research student

ea918@york.ac.uk 

Meghna Asthana

Meghna Asthana

Postgraduate research student 

ma1828@york.ac.uk

James Gardner

James Gardner

Postgraduate research student

james.gardner@york.ac.uk

Yajie Gu

Yajie Gu

Postgraduate research student

yg1390@york.ac.uk 

Zechao Hu 

Zechao Hu

Postgraduate research student

zh955@york.ac.uk 

Guoxi Huang

Guoxi Huang

Postgraduate research student

gh825@york.ac.uk

Finlay Hudson

Finlay Hudson

Postgraduate research student

fgch500@york.ac.uk 

Tatsuro Koizumi

Tatsuro Koizumi

Postgraduate research student

tk856@york.ac.uk

Cameron Kyle-Davidson

Cameron Kyle-Davidson

Postgraduate research student

cameron.kyle-davidson@york.ac.uk

Mingrui Li

Mingrui Li

Postgraduate research student

ml1652@york.ac.uk

Bruce Muller

Bruce Muller

Postgraduate research student

brm512@york.ac.uk

Tejas Pandey

Tejas Pandey

Postgraduate research student

tejas.pandey@york.ac.uk

Will Rowan 

Will Rowan

Postgraduate research student

wjr508@york.ac.uk

Hao Sun

Hao Sun

Postgraduate research student

hs1145@york.ac.uk

George Vanica

George Vanica

Postgraduate research student

gfv501@york.ac.uk

Rapee Wanaset

Rapee Wanaset

Postgraduate research student

rw1734@york.ac.uk

Zeyu Xing

Zeyu Xing

Postgraduate research student

zx997@york.ac.uk 

Jingbo Yang

Jingbo Yang

Postgraduate research student

jy1655@york.ac.uk 

Fei Ye

Fei Ye

Postgraduate research student

fy689@york.ac.uk

Oguzhan Yigit

Oguzhan Yigit

Postgraduate research student

oguzhan.yigit@york.ac.uk

Other affiliates

  • Dr Owais Mehmood

 

Contact us

Dr Will Smith

Dr Will Smith

Vision, Graphics and Learning Research Group lead

william.smith@york.ac.uk

Related links

VGL Google site