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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 2 (unit director)
COMS10004: Programming & Algorithms 2A (unit director)
2nd Year Tutorial: Object Recognition
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, BB, Forums, Tutorials: Y1, Y2, Linux, TT, Pure, Proactis, fEC, Google, Cal, GM


CALL FOR PAPERS: IET Computer Vision Special Issue on 'Computer Vision for Animal Biometrics', deadline 31/01/2017
The development of computer vision approaches that detect and describe animal life in image or video data is an emerging subject in machine vision. First real-world applications are now becoming available to assist work in a variety of areas; including ecology, agriculture, conservation, and the behavioral sciences. This special issue seeks to bring together and organize a collection of recently developed approaches in this domain. It is intended to provide an international forum for researchers to report recent developments in the field in an original research paper style.

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)

Research Student Alumni:

  • Luke Palmer (MSc by Research 2014)
  • Roz Sandwell (PhD 2015)
  • Ben Hughes (PhD 2016)

Current Final Year Student Projects:


    Ecological Prediction using Deconvolutional and Convolutional Neural Nets
    Iris Recognition using a Portable USB Microscope
    Elephant Skin Biometrics using Neural Networks
    Analysis of Body and Eye Movements in Video Testimonies
    Classifying Marine Calcareous Microfossils
    CatIdentifier: Which cat is in the Photo?
    Detecting a Species in Natural Images using CNNs
    Great Ape Detection by Motion Signature using CNNs
    LoD for Elephant-part Recognition using Hierarchical DPBMs
    AR for Contextual Awareness in a Zoo Environment

Some Former Final Year Student Projects:


    Music Score Interpretation from Sketches using a Native Mobile Platform
    Mammography Interpretation Tool using Computer Vision
    Insect Species Recognition via Combined Local and Global Features
    Enhancing AR Museum Guides Using Markerless Tracking and 3D Model Generation in a Web-Browser
    Visual Identification and Comparison of Bristol graffiti
    Object Specific Haar-like Features for Fast and Accurate Shark Fin Detection
    Salient Object Detection for Navigation of Mars-like Environments
RECENT PUBLICATIONS
L Tao, T Burghardt, M Mirmehdi, D Damen, A Cooper, M Camplani, S Hannuna, A Paiment, I Craddock. Calorie Counter: RGB-Depth Visual Estimation of Energy Expenditure at Home. To Appear: Workshop on Assistive Vision at Asian Conference of Computer Vision (ACCV). November 2016.
S Hannuna, M Camplani, J Hall, M Mirmehdi, D Damen, T Burghardt, A Paiment, L Tao. DS-KCF: A real-time tracker for RGB-D data. Journal of Real-Time Image Processing. November 2016. (DOI 10.1007/s11554-016-0654-3)
AS Crunchant, M Egerer, K Zuberbuehler, K Corogenes, V Leinert, L Kulik, A Loos, T Burghardt, H Kuehl. Automated face detection for estimating baseline occurrence in chimpanzees. To Appear: American Journal of Primatology. 2016.
B Hughes, T Burghardt. Automated Visual Fin Identification of Individual Great White Sharks. International Journal of Computer Vision (IJCV), pp. 1-16, ISSN:1573-1405, October 2016. (DOI:10.1007/s11263-016-0961-y), (Dataset FinsScholl2456)
J Hall, M Camplani, S Hannuna, M Mirmehdi, L Tao, D Damen, T Burghardt, A Paiment. Designing a Video Monitoring System for AAL applications: The SPHERE Case Study. To Appear: IET International Conference on Technologies for Active and Assisted Living (TechAAL). October 2016.
L Tao, T Burghardt, M Mirmehdi, D Damen, A Cooper, M Camplani, S Hannuna, A Paiment, I Craddock. Real-time Estimation of Physical Activity Intensity for Daily Living. To Appear: IET International Conference on Technologies for Active and Assisted Living (TechAAL). October 2016.
W Andrew, S Hannuna, N Campbell, T Burghardt. Automatic Individual Holstein Friesian Cattle Identification via Selective Local Coat Pattern Matching in RGB-D Imagery. IEEE International Conference on Image Processing (ICIP), pp. 484-488, ISBN: 978-1-4673-9961-6, September 2016. (DOI:10.1109/ICIP.2016.7532404), (Dataset FriesianCattle2015)
L Tao, A Paiment, D Damen, M Mirmehdi, S Hannuna, M Camplani, T Burghardt, I Craddock. A Comparative Study of Pose Representation and Dynamics Modelling for Online Motion Quality Assessment. Computer Vision and Image Understanding, 148:136-152, Elsevier, May 2016. (DOI:10.1016/j.cviu.2015.11.016)
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. IEEE 17th International Conference on eHealth Networking, Applications and Services. pp.644-647, October 2015. (DOI:10.1109/HealthCom.2015.7454583), (Dataset SPHERE_H130)
D Gibson, T Burghardt, N Campbell, N Canagarajah. Towards Automating Visual In-Situ Monitoring of Crops Health. IEEE International Conference on Image Processing (ICIP), pp. 3906 - 3910, September 2015. (DOI:10.1109/ICIP.2015.7351537)
B Hughes, T Burghardt. Automated Identification of Individual Great White Sharks from Unrestricted Fin Imagery. 26th British Machine Vision Conference (BMVC), pp. 92.1-92.14, ISBN 1-901725-53-7, BMVA Press, September 2015. (DOI:10.5244/C.29.92), (Dataset FinsScholl2456)
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. 26th British Machine Vision Conference (BMVC), pp. 145.1-145.11, ISBN 1-901725-53-7, BMVA Press, September 2015. (DOI:10.5244/C.29.145), (Code Download)
B Hughes, T Burghardt. Affinity Matting for Pixel-accurate Fin Shape Recovery from Great White Shark Imagery. Machine Vision of Animals and their Behaviour (MVAB), Workshop at BMVC, pages 8.1-8.8. BMVA Press, September 2015. (DOI:10.5244/CW.29.MVAB.8), (Dataset FinsScholl2456)
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, 271-277, (DOI:10.1109/ICCW.2015.7247190), 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 Kuehl, 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), BMVA Press, September 2013. (BMVW: ISBN 1-901725-50-2)
H S Kuehl, 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)