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

Professor Will Smith

Professor Will Smith

Vision, Graphics and Learning Research Group lead

william.smith@york.ac.uk

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.

Stories

Focus on Impact -

Focus on PhD student - Jamie Sykes

Group members

Photo Contact details
Academic staff
Dr Kofi Appiah

Dr Kofi Appiah

Academic Staff

kofi.appiah@york.ac.uk

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

Professor Nick Pears 

Professor Nick Pears

Academic staff

nick.pears@york.ac.uk

 

Professor Will Smith

Professor - group lead

william.smith@york.ac.uk

Research staff

Tao Chen

Research Associate

t.chen@york.ac.uk

Postgraduate research students

Luke Farrar

Postgraduate research student 

lbf514@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 

Finlay Hudson

Finlay Hudson

Postgraduate research student

fgch500@york.ac.uk 

Evgenii Kashin

Evgenii Kashin

Postgraduate research student

ek1234@york.ac.uk

Tatsuro Koizumi

Tatsuro Koizumi

Postgraduate research student

tk856@york.ac.uk

Nattapong Kurpukdee

Nattapong Kurpukdee

Postgraduate research student

nk1186@york.ac.uk

Qiran Lai

Qiran Lai

Postgraduate research student

xwj504@york.ac.uk

Mingrui Li

Mingrui Li

Postgraduate research student

ml1652@york.ac.uk

Will Rowan 

Will Rowan

Postgraduate research student

wjr508@york.ac.uk

Patipol Saengduean

Postgraduate research student

ps1510@york.ac.uk

Jamie Sykes

Jamie Sykes

Postgraduate research student

jamie.sykes@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

Tom Wells

Postgraduate research student

tw1700@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 

Oguzhan Yigit

Oguzhan Yigit

Postgraduate research student

oguzhan.yigit@york.ac.uk

Jiaqi Yu

Postgraduate research student

jiaqi.yu@york.ac.uk

Cheng Zhang

Cheng Zhang

Postgraduate research student

rrg517@york.ac.uk

Other affiliates

Dr Patrik Huber

Dr Patrik Huber

Associate

patrik.huber@york.ac.uk

 

Luke Isham

KTP Associate

luke.isham@york.ac.uk

 Dr Paulina Lewinska

Dr Paulina Lewińska

Research Associate

paulina.lewinska@york.ac.uk

 

 

Dr Owais Mehmood

Affiliate

owais.mehmood@york.ac.uk 

Tejas Pandey

Tejas Pandey

Affiliate

tejas.pandey@york.ac.uk

Contact us

Professor Will Smith

Professor Will Smith

Vision, Graphics and Learning Research Group lead

william.smith@york.ac.uk