Hannah Dee BSc, MA, PhD University of Leeds

Senior Lecturer

Contact Details

Room Number..........:  E44
Building....................:  Llandinam
Phone.......................:   +44 (0)1970 621577
E-Mail........................:   hmd1
Home Page...............:   Personal

External Publication Websites:
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Hannah has a BSc in Cognitive Science (1996), an MA in Philosophy (1998) and a PhD in Computing (2005) all from the University of Leeds. Her research areas are applied computer vision; the detection of shadows and reasoning about shadows; and student attitudes to the study of computer science. She has held postdoctoral positions in Grenoble (France), Leeds, and Kingston upon Thames. She is also a women in computing activist: she runs the BCSWomen Lovelace Colloquium, a national conference for women undergraduates in computer science, and has been on the committee of BCSWomen since 2007.

Research Groups

Teaching Areas

Modules Taught


Shadow detection for mobile robots: Features, evaluation, and datasetsNewey, C., Jones, O. & Dee, H. 2017 In : Spatial Cognition and Computation.p. 1-2323 p.
Watching plants grow: A position paper on computer vision and Arabidopsis thalianaBell, J. & Dee, H. 2017 In : IET Computer Vision.11, 2, p. 113-1219 p.
Probabilistic self-localisation on a qualitative map based on occlusionsSantos, P. E., Martins, M. F., Fenelon, V., Cozman, F. G. & Dee, H. 2016 In : Journal of Experimental & Theoretical Artificial Intelligence.28, 5, p. 781-79919 p.
Visual digital humanities: using image data to derive approximate metadataDee, H., Hughes, L., Roderick, G. L. & Brown, A. D. 2016 Managing Digital Cultural Objects: Analysis, discovery and retrieval. Foster, A. & Rafferty, P. (eds.). London: Facet Publishing, p. 89-11021 p.
Special issue on computer vision and image analysis in plant phenotypingScharr, H., Dee, H., French, A. & Tsaftaris, S. A. 2016 In : Machine Vision and Applications.27, 5, p. 607-6093 p.
3D Facial Skin Texture Analysis Using Geometric DescriptorsSeck, A., Dee, H. M. & Tiddeman, B. 2014 22nd International Conference on Pattern Recognition. Stockholm: IEEE Press, p. 1126 - 11316 p. (International Conference on Pattern Recognition)
Towards Automated Classification of Seabed Substrates in Underwater VideoPugh, M., Tiddeman, B., Dee, H. M. & Hughes, P. 2014 Computer Vision for Analysis of Underwater lmagery Workshop: International Conference on Pattern Recognition. Stockholm: IEEE Press, p. 9-168 p.
Can we date an artist's work from catalogue photographs?Brown, A., Roderick, G. L., Dee, H. M. & Hughes, L. 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA).IEEE Press, p. 558-5636 p.
An Evaluation of Image-Based Robot Orientation EstimationCao, J., Labrosse, F. & Dee, H. M. 2013 Towards Autonomous Robotic Systems.Springer Nature, p. 135-14723 p. (Lecture Notes in Artificial Intelligence)
Reasoning about shadows in a mobile robot environmentFenelon, V., Santos, P. E., Dee, H. M. & Cozman, F. G. 2013 In : Applied Intelligence.38, 4, p. 553-565
Local Orientation Patterns for 3D Surface Texture Analysis of Normal Maps: Application to Facial Skin Condition ClassificationSeck, A., Dee, H. M. & Tiddeman, B. 2013 Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part I. Bebis, G., Boyle, R., Parvin, B., Koracin, D., Li, B., Porikli, F., Zordan, V., Klosowski, J., Coquillart, S., Luo, X., Chen, M. & Gotz, D. (eds.). Springer Nature, p. 572-5819 p. (Lecture Notes in Computer Science; vol. 8033)
A Novel Image Similarity Measure for Place Recognition in Visual Robotic NavigationCao, J., Labrosse, F. & Dee, H. M. 2012 Advances in Autonomous Robotics: Lecture Notes in Artificial Intelligence. Herrmann, G., Studley, M., Pearson, M., Conn, A., Melhuish, C., Witkowski, M., Kim, J-H. & Vadakkepat, P. (eds.). Springer Nature, Vol. 7429, p. 414-4152 p. (Lecture Notes in Computer Science; vol. 7429)
Face recognition using the POEM descriptorVu, N-S., Dee, H. M. & Caplier, A. 2012 In : Pattern Recognition.45, 7, p. 2478-2488
Building semantic scene models from unconstrained videoDee, H. M., Cohn, A. G. & Hogg, D. C. 2012 In : Computer Vision and Image Understanding.116, 3, p. 446-45611 p.
Coping with Noise in Ultrasound Images: A reviewZwiggelaar, R., Roscoe, J. F. & Dee, H. 2012
Improving bioenergy crop yield and quality through manipulating senescenceRobson, P., Mos, M., Dee, H., Clifton-Brown, J. C. & Donnison, I. 2011 In : Aspects of Applied Biology.112, p. 323-3286 p.
The Perception and Content of Cast Shadows: An Interdisciplinary ReviewDee, H. & Santos, P. E. 2011 In : Spatial Cognition and Computation.11, 3, p. 226-25328 p.
Crowd behaviour analysis using histograms of motion directionDee, H. & Caplier, A. 2010
Knowledge-based adaptive thresholding from shadowsDee, H., Santos, P. E. & Fenelon, V. 2010
Knowledge-based adaptive thresholding from qualitative robot localisation using cast shadowsSantos, P. E., Fenelon, V. & Dee, H. 2010
Inspiring women undergraduatesDee, H. & Boyle, R. 2010
Navigational strategies in behaviour modellingDee, H. M. & Hogg, D. C. 2009 In : Artificial Intelligence.173, 2, p. 329-34214 p.
Qualitative robot localisation using information from cast shadowsFenelon, V., Dee, H. & Santos, P. E. 2009 p. 220-2256 p.
Scene modelling and classification using learned spatial relationsHogg, D. C., Cohn, A. G. & Dee, H. 2009 p. 295-31117 p.
Why are we still here?: Experiences of successful women in computing.Pau, R., Dee, H., Boyle, R. & Petrie, K. E. 2009 p. 233-2375 p.
How close are we to solving the problem of automated visual surveillance? A review of real-world surveillance, scientific progress and evaluative mechanismsDee, H. M. & Velastin, S. A. 2008 In : Machine Vision and Applications.19, 5-6, p. 329-34315 p.
Notes on a qualitative theory of shadowsSantos, P. E., Fenelon, V. & Dee, H. 2008 p. 47-548 p.
Modelling scenes using the activity within themDee, H., Fraile, R., Hogg, D. C. & Cohn, A. G. 2008 p. 394-40815 p.
Using Computer based Systems to Address the Gender Imbalance in ComputingKomisarczuk, J., Petrie, K. E., Ross, M., Paterson, F., Dee, H., Boldyreff, C. & Massey, E. 2008
Navigational strategies and surveillanceHogg, D. C. & Dee, H. 2006 p. 73-819 p.
Supporting undergraduate teaching in histopathology with virtual microscopyQuirke, P., Griffin, N. R., Dee, H., Dixon, M. F. & Waterhouse, M. 2006
On the feasibility of using a cognitive model to filter surveillance dataDee, H. & Hogg, D. C. 2005 p. 34-396 p.
An e-learning system using virtual slidesGriffin, N. R., Quirke, P., Dixon, M. F., Treanor, D., Waterhouse, M. & Dee, H. 2005
A searchable online database of virtual slides.Quirke, P., Lewis, F., Casali, G., Treanor, D., Dee, H., Dixon, M. F. & Edward, S. 2005
Is it Interesting?: Comparing human and machine judgements on the PETS datasetHogg, D. C. & Dee, H. 2004 p. 49-557 p.
Detecting inexplicable behaviourHogg, D. C. & Dee, H. 2004 p. 477-48610 p.
The bigger the better? A new look at virtual learningDee, H. & Tebb, C. 2003 p. 462-4665 p.
ACOM ('Computing for all') : an integrated approach to the teaching and learning of information technologyReffell, P. & Dee, H. 1999 p. 195-1951 p.