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Homepage of Tilo Burghardt


Administrative Roles

PhD (Bristol), MSc (Bristol), Bakk Medien-Inf (Dresden)


Teaching (Current)

COMS30121: Image Processing & Computer Vision (unit director)
COMS30400: Group Project (unit director)
COMS20001: Concurrent Computing (unit director)
COMS10001: Programming & Algorithms II (unit director)
COMSM2202: Research Skills
COMSM3100: MSc Advanced Project
COMSM3201: MSc Project Computer Science

Previously Taught

COMS12800: Introduction to C++ (unit director)
COMS20600: Concurrency (unit director)
COMS22201: Language Engineering
EMATM0009: Complexity in Engineering and Science

Research Interest

Applied Computer Vision, Animal Biometrics, Natural Patterns

Contact

Office 3.45, MVB
Woodland Road
Clifton BS8 1UB

+44 (0) 117 954 5298
tb2935 (at) bristol.ac.uk


SAFE, Forums, Tutorials: Y1, Y2, Linux, TT, Pure, Proactis, fEC

SUMMARY

Dr Tilo Burghardt's research focuses on applied computer vision and animal biometrics. His interests include the robust visual detection and identification in unconstrained environments. He contributed to establishing Visual Animal Biometrics as an emerging cross-discipline routed in computer vision. Burghardt's enthusiasm for computer science and vision is reflected in his dedication to teaching the subject. 

Burghardt graduated with Distinction in Media Computing (Bakk. Medien-Inf.) at Dresden University of Technology (Germany). Subsequently, he received an MSc in Advanced Computing and PhD in Computer Vision from the University of Bristol (UK). After initial post-doctoral research at the School of Physics, he was awarded a Fellowship of the Research Councils UK and then became employed as a Lecturer (2012-present) at the Visual Information Laboratory and the Intelligent Systems Laboratory at the University of Bristol. Burghardt is a member of the British Machine Vision Association (BMVA) and the German Academic Foundation (Studienstiftung des Deutschen Volkes). He is a Fellow of the Higher Education Academy (HEA). Burghardt has been a local organizer for the 23rd European Conference of Machine Learning 2012 (ECML-PKDD) and the 8th International Penguin Conference 2013 (IPC8). He has been a chair of the 24th British Machine Vision Conference (BMVC2013).


Current Research Students:

  • William Andrew (PhD student)
  • Ben Hughes (PhD student)

Alumni:

  • Luke Palmer (MSc by Research 2014)
  • Roz Sandwell (PhD 2015)
RECENT PUBLICATIONS
L Tao, T Burghardt, S Hannuna, M Camplani, A Paiement, D Damen, M Mirmehdi, I Craddock.A Comparative Home Activity Monitoring Study using Visual and Inertial Sensors. To Appear: IEEE 17th International Conference on eHealth Networking, Applications and Services. October 2015.
D Gibson, T Burghardt, N Campbell, N Canagarajah. Towards Automating Visual In-Situ Monitoring of Crops Health. To Appear: IEEE International Conference on Image Processing (ICIP). September 2015.
B Hughes, T Burghardt. Automated Identification of Individual Great White Sharks from Unrestricted Fin Imagery. To Appear: 26th British Machine Vision Conference (BMVC). September 2015.
M Camplani, S Hannuna, D Damen, M Mirmehdi, A Paiement, T Burghardt, L Tao. Robust Real-time RGB-D Tracking with Depth Scaling Kernelised Correlation Filters. To Appear: 26th British Machine Vision Conference (BMVC). September 2015.
B Hughes, T Burghardt. Affinity Matting for Pixel-accurate Fin Shape Recovery from Great White Shark Imagery. To Appear: Machine Vision of Animals and their Behaviour Workshop at BMVC. September 2015.
T Burghardt, D Damen, W Mayol-Cuevas, M Mirmehdi (editors). Correspondence, Matching and Recognition. International Journal of Computer Vision (IJCV), Volume 113, Issue 3:161-162, ISSN 0920-5691, Springer, June 2015. (DOI:10.1007/s11263-015-0827-8)
P Woznowski, F Fafoutis, T Song, S Hannuna, M Camplani, L Tao, A Paiement, E Mellios, M Haghighi, N Zhu, G Hilton, D Damen, T Burghardt, M Mirmehdi, R Piechocki, D Kaleshi, I Craddock. A Multi-modal Sensor Infrastructure for Healthcare in Residential Environment. IEEE ICC Workshop on ICT-enabled Services and Technologies for eHealth and Ambient Assisted Living, June 2015.
L Palmer, T Burghardt. Contextual Saliency for Nonrigid Landmark Registration and Recognition of Natural Patterns. International Conference on Computer Vision Theory and Applications (VISAPP), 403-410, ISBN: 978-989-758-089-5, March 2015. (DOI:10.5220/0005268604030410)
H S Kühl, T Burghardt. Fractal Representation and Recognition for Animal Biometrics: A Reply to Jovani et al. Trends in Ecology and Evolution, Vol 28 No 9, 500-501, September 2013. (DOI:10.1016/j.tree.2013.06.007)
T Burghardt, D Damen, W Mayol-Cuevas, M Mirmehdi (editors). Proceedings of the 24th British Machine Vision Conference, BMVC2013. British Machine Vision Association (BMVA), ISBN 1-901725-49-9, BMVA Press. September 2013.
(BMVC 2013 Book of Abstracts, BMVC 2013 Website)
R C Sandwell, A Loos, T Burghardt. Synthesising Unseen Image Conditions to Enhance Classification Accuracy for Sparse Datasets: Applied to Chimpanzee Face Recognition. British Machine Vision Workshop (BMVW), British Machine Vision Association, September 2013. (BMVW: ISBN 1-901725-50-2)
H S Kühl, T Burghardt. Animal Biometrics: Quantifying and Detecting Phenotypic Appearance. Trends in Ecology and Evolution, Vol 28 No 7, 432–441, July 2013.
(DOI:10.1016/j.tree.2013.02.013)