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Department of Computer Science and Technology

  • Affiliated Lecturer
  • Research Fellow
  • Director of Studies


I'm an Affiliated Lecturer in the Department of Computer Science and Technology and a Fellow of Wolfson College, where I am a Tutor, Director of Studies in Computer Science (see "why Wolfson?"), and run the PhD Mentoring Scheme. I am also Director of Studies in Computer Science for Part II and Part III at Jesus College.


I completed my PhD here at the University of Cambridge Computer Laboratory (Computer Science Department) under the supervision of John Daugman. My PhD thesis was awarded a prize in the BCS Distinguished Dissertation Awards in 2005. Apart from carrying our research (see below), I also continue to supervise undergraduate and Masters students in Computer Science (see here for a list of suggested final year projects). I co-lecture the Part III/ACS Computer Vision module (previously known as LE48, EF12) and I lectured and examined the Part II Computer Vision course (I regularly give guest lectures and supervisions for this course).

My PhD was sponsored by AT&T Labs Research through an Industrial Fellowship from the Royal Commission for the Exhibition of 1851 and various scholarships from Trinity College. Before starting my PhD I completed a pre-doc year at AT&T Laboratories Cambridge and summer internships at AT&T in the USA and Cambridge. Prior to that I received my undergraduate degree with first class honours in Computer Science from the University of Cambridge (Trinity College).


Despite the dramatic growth of digital image and video data in recent years, many challenges remain in enabling computers to interpret visual content. Visual information is inherently ambiguous and semantically impoverished. There consequently exists a wide semantic gap between human interpretations of image and video data and those currently derivable by a computer. My research demonstrates how this gap can be narrowed through the use of ontologies which represent task-specific attributes, objects, and relations, and relate these to the processing modules available for their detection and recognition. Terms in the ontology therefore carry meaning directly related to the appearance of real world objects. Tasks such as image retrieval, automated visual surveillance, and visually mediated human computer interaction can then be carried out by processing sentences in a visual language defined over the ontology. The efficacy of the proposed approach is demonstrated through the development and analysis of solutions to a range of challenging visual analysis problems. Content-based image analysis and ontology-based information modeling are starting to revolutionise professional image search and can also be used to greatly speed up time consuming tasks such as image annotation and optical character recognition.

I am also actively working on pattern matching algorithms for the biological sciences. A generic image processing and identification tool has been developed by me and is available for free use by the academic community. It has already been deployed for research in various fields of ecology and zoology, for example Manta Matcher and NPM.


I co-lecture the Part III/ACS Computer Vision module (previously known as LE48, EF12) and I lectured and examined the Part II Computer Vision course (I regularly give guest lectures and supervisions for this course).


Peer-reviewed Academic Publications


  • Kwot Sin Lee, Christopher Town. "Mimicry: Towards the Reproducibility of GAN Research", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) AI for Content Creation Workshop, 2020
  • Elham Yousef Kalafi, Nurul Aqilah Mohd Nor, Nur Aishah Taib, Mogana Darshini Ganggayah, Chris Town, Sarinder Kaur Dhillon "Machine Learning and Deep Learning Approaches In Breast Cancer Survival Prediction Using Clinical Data", Folia Biologica (vol 65), 2019
  • Elham Yousef Kalafi, Chris Town and Sarinder Kaur Dhillon "How can automated image analysis techniques help scientists in species identification and classification?", Folia Morphologica 77(2): 179-193, 2018
  • Elham Yousef Kalafi, Boon Tan Wooi, Chris Town and Sarinder Kaur Dhillon "Identification of Selected Monogeneans using Image Processing, Artificial Neural Networks and K- Nearest Neighbour", Journal of Fisheries Sciences, 17(4): 805-820. DOI: 10.5603/FM.a2017.0079, 2018
  • Fiona Hamey, Yoli Shavit, Valdone Maciulyte, Christopher Town, Pietro Lio', and Sabrina Tosi "Automated Detection of Fluorescent Probes in Molecular Imaging", Springer Lecture Notes in Bioinformatics, LNCS 8623, 2017
  • Elham Yousef Kalafi, Boon Tan Wooi, Chris Town and Sarinder Kaur Dhillon "Automated identification of Monogenean using digital image processing and K-nearest neighbour approaches", BMC Bioinformatics (InCoB2016), 17(19): 511. DOI:10.1186/s12859-016-1376-z
  • Sarinder Dhillon, Haris Ali Khan, Mohd Ali, Amandeep Sidhu, Christopher Town and Ving Ching Chong "Ontology Design and Development: A case scenario for a Fish Ontology from conception to implementation", Proceedings of ICCESEN, 2015
  • Mary Stoddard, Rebecca Kilner, and Christopher Town "Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures", Nature Communications, 2014, DOI: 10.1038/ncomms5117 (press release: "Birds evolve signature patterns to distinguish cuckoo eggs from their own", press releases here and here, short video hosted by American Museum of Natural History)
  • Fiona Hamey, Yoli Shavit, Christopher Town and Pietro Lio' "A Method For Automated Detection Of Fluorescent Probes In FISH Images", presented at Eleventh International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB), 2014
  • Christos Makris and Christopher Town "Character segmentation for automatic CAPTCHA solving", Open Computer Science Journal, 2014; DOI: 10.2174/2352627001401010001
  • Alexander Barley and Christopher Town "Combinations of Feature Descriptors for Texture Image Classification", Journal of Data Analysis and Information Processing (JDAIP), 2014, DOI:10.4236/jdaip.2014.23009
  • Mary Stoddard, Rebecca Kilner, and Christopher Town "Host Birds Combat Cuckoo Mimicry By Evolving Recognizable Egg Pattern Signatures", to be presented at Evolution 2014
  • Town, C.P. and Marshall, A.D. and Sethasathien, N. "Manta-Matcher: Automated Photographic Identification of Manta Rays using Keypoint Features", Journal of Ecology and Evolution, 2013; 3(7)
  • Town, C.P. "Content-Based and Similarity-Based Querying for Broad-Usage Medical Image Retrieval", International Symposium on Advances in Biomedical Infrastructure, Springer, 2013
  • Town, C.P. "Ontology based Image and Video Analysis", chapter in the book Advances in Computer Vision, published by Nova, 2011
  • Town, C.P. and Harrison, K. "Large-scale Grid Computing for Content-based Image Retrieval", ISKO (International Society for Knowledge Organization) conference on "Content Architecture: Exploiting and Managing Diverse Resources", 2009, and also published in Aslib Proceedings, Vol 62(4/5), 2010
  • Town, C.P. "Giving Meaning to Content through Ontology-based Image Retrieval", ISKO (International Society for Knowledge Organization) conference on "Content Architecture: Exploiting and Managing Diverse Resources", 2009
  • Town, C.P. "Distributed Grid Computing for Multi-million Image Retrieval", MMKM Workshop on Future Directions in Multimedia Knowledge Management, Knowledge Media Institute of The Open University, 2008
  • F. Brochu, M. Calleja, J. Coles, S. Das, K. Harrison, M.A. Hayes, S.G. Heo, M.A. Parker, D.A. Sinclair, E. Schofield, C.P. Town "Using the Grid to enable Internet-scale Content-based Image Retrieval", Crossing Boundaries: Computational Science, E-Science and Global E-Infrastructures, UK e-Science 2008 All Hands Meeting, 2008
  • Town, C.P. "Managing Image Overload: Making Sense of Multimedia", Interdisciplinary Graduate Conference 2008: Challenges of the 21st Century, Cambridge University, 2008
  • Town, C.P. "Using Grid Technology for Commercial Scale Content-based Image Retrieval", EGEE (Enabling Grids for E-sciencE) User Forum, Clermont-Ferrand, France, 2008
  • Town, C.P. "Sensor Fusion and Environmental Modelling for Multimodal Sentient Computing", chapter in the book Multimodal Surveillance: Sensors, Algorithms and Systems, published by Artech, 2007
  • Town, C.P. "Multi-sensory and Multi-modal Fusion for Sentient Computing", International Journal of Computer Vision, Volume 71, Issue 2, 2007 PDF
  • Town, C.P. "Ontological Inference for Image and Video Analysis", International Journal of Machine Vision and Applications, Volume 17, Number 2, pp 94-115, 2006 pre-print PDF
  • Saatci, Y. and Town, C.P. "Cascaded Classification of Gender and Facial Expression using Active Appearance Models", Proc. International Conference on Automatic Face and Gesture Recognition, 2006 PDF
  • Song, Y.Z. and Town, C.P. "Visual Recognition of Man-made Materials and Structures in an Office Environment", Proc. International Conference on Vision, Video and Graphics, 2005
  • Town, C.P. "Vision-based Augmentation of a Sentient Computing World Model", Proc. International Conference on Pattern Recognition, 2004
  • Town, C.P. and Pugh, D.J. "Combining Contour, Edge and Blob Tracking", Proc. International Conference on Visualisation, Imaging, and Image Processing, 2004
  • Town, C.P. and Moran, S.J. "Robust Fusion of Colour Appearance Models for Object Tracking", Proc. British Machine Vision Conference, 2004
  • Town, C.P. "Ontology-driven Bayesian Networks for Dynamic Scene Understanding", Proc. International Workshop on Detection and Recognition of Events in Video (at CVPR04), 2004
  • Town, C.P. "Fusion of Visual and Ultrasonic Information for Environmental Modelling", Proc. International Workshop on Object Tracking Beyond the Visual Spectrum (at CVPR04), 2004
  • Town, C.P. "Ontology-guided Training of Bayesian Networks for High-level Analysis in Visual Surveillance", Proc. IEEE International Workshop on Performance Evaluation in Tracking and Surveillance (at ECCV04), 2004
  • Town, C.P. and Sinclair, D.A. "Language-based Querying of Image Collections on the basis of an Extensible Ontology", International Journal of Image and Vision Computing, Vol. 22/3, pp 251-267, 2004 DjVu PDF
  • Town, C.P. "Adaptive Integration of Visual Tracking Modalities for Sentient Computing", IEEE International Workshop on Visual Surveillance and Performance Evaluation in Tracking and Surveillance (at ICCV03), 2003
  • Town, C.P. "Computer Architecture for Self-referential Perceiving Systems", Perception journal special supplement (Proceedings of the European Conference on Visual Perception), 2003
  • Town, C.P. "Goal-directed Visual Inference for Multi-modal Analysis and Fusion", Proceedings of the IEE Conference on Visual Information Engineering, 2003
  • Town, C.P. and Sinclair, D.A. "A Self-referential Perceptual Inference Framework for Video Interpretation", Lecture Notes in Computer Science, Springer, Volume 2626, pp. 54-67 (Proceedings of the International Conference on Vision Systems), 2003 (winner of the runner-up prize for best cognitive vision paper) DjVu PDF
  • Town, C.P. and Sinclair, D.A. "Ontological Query Language for Content Based Image Retrieval", Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (at CVPR'01), 2001 DjVu PDF
  • Town, C.P. and Sinclair, D.A. "Content Based Image Retrieval using Semantic Visual Categories", Society for Manufacturing Engineers, Technical Report MV01-211, 2001 (previously published as AT&T Laboratories Cambridge Technical Report TR2000-14) DjVu PDF



  • Town, C.P. "Ontology based Visual Information Processing", PhD Thesis, University of Cambridge Computer Laboratory, 2004 (finalist for the Distinguished Dissertation Award by the Conference of Professors and Heads of Computing and the British Computer Society) PDF (also published by the BCS, see 2005 Distinguished Dissertations website)
  • Town, C.P. "Neural Network based Region Classification for Image Retrieval", Final year Undergraduate Dissertation, University of Cambridge Computer Laboratory, 2000 (winner of the Part II Distinguished Dissertation award)

Contact Details

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(01223) 7-63686