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Overview

Professor Toby Breckon

Professor

BSc PhD CEng CSci ASIS FRPS FIET FBCS FHEA


Affiliations
AffiliationRoom numberTelephone
Professor in the Department of Computer ScienceMCS 2108+44 (0) 191 33 42396
Professor in the Department of EngineeringE234 (Christopherson)+44 (0) 191 33 42396
Member of the Centre for Vision and Visual Cognition  
Fellow of Wolfson Research Institute for Health and Wellbeing +44 (0) 191 33 42396

Biography

Toby Breckon is a Professor in the Department of Engineering and Department of Computer Science at Durham University and an academic tutor at St. Chads College.

Within the department(s), he leads research in computer vision, image processing and robotic sensing, with a strong emphasis on generalized machine learning and pattern recognition techniques, in addition to research-led teaching within the undergraduate Engineering and Computer Science programmes.

Experience

Prof. Breckon's current research spans a breath of computer vision, image processing and robotic sensing application domains including automotive sensing, X-ray security image understanding, automated visual surveillance and robotic sensing.

Within the automotive sector, his team work with a number of major vehicle manufacturers on future automotive sensing solutions having originally commenced work in this area in the early days of intelligent driver assistance systems (2007-2020+). As of 2019, he is a scientific advisor to Machines With Vision on autonomous vehicle sensing.

Within aviation security, his research work on X-ray image understanding pioneered the use of automated prohibited item detection algorithms within the sector and his team are credited with designing the first complete solution for threat image insertion (TIP) within 3D CT security scan imagery. Their 3D TIP approach is now used globally by several major security scanner manufacturers, in numerous major international airports, and helps to secure over 500+ million passenger journeys per annum across five continents (as of 2019/20).

The work of his team on anomaly detection is used by COSMONiO in their NOUS product. COSMONiO, founded by former members of his research team in 2012, was acquired by Intel in 2020.

As of 2014, his team were selected as a research partner in the UK SAPIENT programme, supplying a fully operational research demonstrator, to demonstrate 'the art of the possible' in automated visual surveillance across passive infrared (thermal) imagery resulting in substantial impact into the defence and security sensing sector (2016-2020+).

In 2008 he led the development of image-based automatic threat detection for the the Stellar Team's SATURN multi-platform robot system in the MoD Grand Challenge, going on to win the R.J. Mitchell Trophy (UK MoD Grand Challenge winners, 2008), the Finmeccanica Group Innovation Award (2009) and an IET Award for Innovation (Team Category, 2009).

His research work is recognised by the Royal Photographic Society Selwyn Award (2011) for a significant early career contribution to imaging science.

Background

Before joining Durham in 2013, he held faculty positions at the School of Engineering, Cranfield University, the UK's only postgraduate-only university, and the School of Informatics, University of Edinburgh. Prior to this he was a mobile robotics research engineer with the UK MoD (DERA) and QinetiQ as well as holding prior positions with the schools inspectorate OFSTED, the Scottish Language Dictionaries organisation and (1990s, dot-com) software house Orbital Software.

He has held a visiting faculty positions at ESTIA ( Ecole Supérieure des Technologies Industrielles Avancées), South-West France, Northwestern Polytechnical University (Xi'an, China), Waseda University (Kitakyushu, Japan) and Shanghai Jiao Tong University (Shanghai, China).

He holds a PhD in Informatics (Artificial Intelligence - Computer Vision) from the University of Edinburgh and studied Artificial Intelligence and Computer Science as an undergraduate (B.Sc. (Hons.) (Edin.)).

Service and Outreach

Prof. Breckon is a scientific advisor to H.M. Cabinet Office (Cyber Security Expert Group, 2015-present) and previously to H.M. Government Office for Science (2016/17) in areas pertaining to his research specialism.

At Durham, Prof. Breckon led applied Computer Science research, as Head of Innovative Computing research, between 2014-2018. From 2020, he serves as a member of the Ethics Advisory Committee bringing broad experience in the application of ethics approval and practice within Artificial Intelligence and related areas.

From 2010 he has been a member of the executive committee of the BMVA (British Machine Vision Association) acting as Treasurer for financial oversight of the association's annual computer vision conferences (BMVC, MIUA), summer school and other activities.

Outside of the university, he acts as a STEMNET Science & Engineering Ambassador promoting awareness of intelligent sensing, its underpinning technology and related societal impact.

Research interests

  • image processing
  • computer vision
  • robotic sensing
  • machine learning
  • autonomous sensing

Research groups

  • Innovative Computing
  • Sustainable Infrastructure

Awarded Grants

  • 2019: KTP Cievert- Innovate UK(£152457.20 from Innovate UK)

Media Contacts

Available for media contact about:

  • Computer Science: image processing
  • Computer Science: object recognition
  • Computer Science: computer vision
  • Computer Science: robotic sensing
  • Computer Science: machine learning

Publications

Authored book

  • Fisher, R.B., Breckon, T.P., Dawson-Howe, K., Fitzgibbon, A., Robertson, C., Trucco, E. & Williams, C.K.I. (2014). Dictionary of Computer Vision and Image Processing. Wiley.
  • Solomon, C.J. & Breckon, T.P. (2013). Fundamentos de Processamento Digital de Imagens - Uma Abordagem Pratica com Exemplos em Matlab. Brazil: LTC.
  • Solomon, C.J. & Breckon, T.P. (2010). Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab. Wiley-Blackwell.

Chapter in book

Conference Paper

Doctoral Thesis

  • T.P. Breckon (2006). Completing Unknown Portions of 3D Scenes via 3D Visual Propogation. School of Informatics, University of Edinburgh. PhD.

Journal Article

Supervision students