Professor Fred Stentiford

Electronic and Electrical Engineering Department,
University College London

Information.

 

Address :

Department of Electronic & Electrical Engineering
 

Torrington Place, London WC1E 7JE

Phone :

+44 (0) 1394 411469

Mobile :

+44 (0) 7761 828300

Fax :

+44 (0) 1394 411469

E-mail :

 
 

Issues in Pattern Recognition

Pattern Recognition is in a crisis. Performance in recent years has been attributable only to increasing computer power and knowledge about specific applications. Serious questions lie in the following tricky areas:

  • Systems which rely upon the pre-selection of feature measurements suffer a huge risk of failure on unseen data. The commitment to a fixed set of features constrains performance to a restricted set of solutions for which those features are appropriate.
  • Representative data is often gathered for training purposes and system optimisation. By definition such data cannot represent unseen data and therefore cannot be expected to compensate for a restricted feature set.
  • The labelling of data for real life problems is difficult. There is no guarantee that different people will label data in the same way or what effect different labelling will have on system design and ultimate performance.
  • There is no guarantee that computer search for an optimal recognition performance is ever the best in a real problem. The intuitive heuristic rules of inference used in the search almost always preclude large volumes of the solution space from being entered. The existence of such solutions cannot be proved as this would lead to a contradiction, but equally it cannot be disproved.

Our work in Pattern Recognition recognises these issues and favours new approaches that avoid them as far as possible.

Content-Based Image Retrieval

The volume of digital images has increased dramatically in recent years and as a result a crisis is now taking place within a broad range of disciplines that need and use visual material. Whilst storage and capture technologies are able to cope with the huge numbers of images, poor image retrieval is in danger of rendering many repositories valueless because of the difficulty of access. These problems motivated this research.
Image Compression
Compression mechanisms that are dependent upon the significance of image regions promise to offer considerable improvements in efficiency and computational requirements whilst maintaining perceptual quality.  Advances in this area have particular relevance to mobile communications.
 

Modeling and Measurement of Visual Attention

Much research has been carried out into mechanisms of attention in the human visual system.  Some of these models may provide solutions to problems of the machine interpretation of images and the intuitive access to databases containing visual material.

Detection of Symmetries

Features that characterise visual symmetry are very closely related to those that reveal saliency. Indeed symmetry is salient in its own right. Recent work has shown that the introduction of rotation and reflection transforms into visual attention mechanisms can expose axes of symmetry without making any prior assumptions about the image content.

The research applies to the naturally symmetric images of faces. The first image is taken from the Yale database B.
(http://cvc.yale.edu/projects/yalefacesB/yalefacesB.html)The second image is a road scene with some obvious global symmetry.

Vanishing Points

Perspective is another attribute that drops out of attention mechanisms. By using a simple scaling transform during matching, the location of vanishing points can be identified.

Focusing

Focusing and visual accommodation is very much related to attention. Experiments have shown that when global attention measures are maximised across focal planes, the principal subject becomes in focus.

Zoom and Pan

As with accommodation, measures of attention enable us to decide which image sub-window has most impact and to define an optimal zoom path.

Brief CV

I studied mathematics at St Catharine's College, Cambridge, and obtained a PhD in Pattern Recognition at Southampton University.  I first joined the Plessey Company to work on various applications including the recognition of fingerprints and patterns in time varying magnetic fields.  I then joined BT and carried out research on optical character recognition and speech recognition.  After that I led a team developing systems employing pattern recognition methods for the machine translation of text and speech.  This work led to the world's first demonstration of automatic translation of speech between different languages.  

I then moved into designing dialogues for new telephone services and managed the government funded collaborative Dialogues 2000 project which aimed to research and promote common standards in the spoken user interface in UK industry.  The membership of over 200 companies was a measure of its success.

I returned to vision research to lead a group developing new algorithms for analysing and delivering multimedia content and more recently joined UCL to pursue this research more intensively.

I am a corporate member of the IEE and the BCS.

I look after the Boyton village website.

Research Interests

My current interests are in the field of Pattern Recognition and Machine Vision.  I have an open mind on the usefulness of mathematical theory in this area of research preferring to rely upon experiment to determine the direction that investigation should take.  I have a special interest in evolution and why it works.

Specific topics of interest include:

Visual attention

Similarity measures

Content-Based Image Retrieval

HCI

Recent Publications

  1. L Chen and F W M Stentiford, “Video sequence matching based on temporal ordinal measurement,” Pattern Recognition Letters, vol. 29, no 13, pp 1824-1831, 2008.
  2. S Zhang and F W M Stentiford, "A saliency based object tracking method," Sixth International Workshop on Content-Based Multimedia Indexing, 18-20 June, London, 2008.
  3. S Zhang and F W M Stentiford, “Motion segmentation using region growing and an attention based algorithm,” 4th European Conference on Visual Media Production, 27-28 Nov, London, 2007.
  4. O. Oyekoya and F. W. M. Stentiford, "Perceptual image retrieval using eye movements," International Journal of Computer Mathematics, vol. 84, no. 9 pp 1379-1391, September, 2007. http://dx.doi.org/10.1080/00207160701242268
  5. R T Shilston and F W M Stentiford, “Preliminary Subjective Focus Assessment Results,” London Communications Symposium, UCL, 19th September, 2007.
  6. S Zhang and F W M Stentiford, “Region Growing for Motion Segmentation using an Attention Based Algorithm,” London Communications Symposium, 19th September, London, 2007.
  7. S Zhang and F W M Stentiford, “Motion detection using a model of visual attention,” ICIP, San Antonio, September 16th – 19th, 2007.
  8. J Law-To, O. Buisson, L. Chen, V. Gouet-Brunet, A. Joly, N. Boujemaa, I. Laptev and F.Stentiford, “Video Copy Detection: A Comparative Study", ACM Int. Conf. on Image and Video Retrieval, Amsterdam, July 9th - 11th, 2007.
  9. F. W. M. Stentiford and A. Bamidele, "Attention based colour correction," Annals of the BMVA, vol. 2007, no 5, pp 1-11, 2007.
  10. F. W. M. Stentiford, “Attention based Auto Image Cropping,” Workshop on Computational Attention and Applications, ICVS, Bielefeld, March 21-24, 2007.
  11. S. Zhang and F. W. M. Stentiford, “An Attention Based Method for Motion Detection and Estimation,” Workshop on Computational Attention and Applications, ICVS, Bielefeld, March 21-24, 2007.
  12. F. W. M. Stentiford, "Attention based similarity," Pattern Recognition, DOI, 40(3), pp 771-783, 2007.
  13. L. Chen and F. W. M. Stentiford, “Comparison of near-duplicate image matching,” 3rd European Conference on Visual Media Production, 29-30 November 2006.
  14. F. W. M. Stentiford, "Attention-based vanishing point detection," Int. Conf. on Image Processing, Oct. 8-11, Atlanta, 2006.
  15. R. Shilston and F. W. M. Stentiford, "An attention-based focus control system," Int. Conf. on Image Processing, Oct. 8th - 11th, Atlanta, 2006.
  16. L. Chen and F. W. M. Stentiford, "An attention based similarity measure for colour images," Int. Conf. on Artificial Neural Networks - special session on Visual Attention Algorithms and Architectures for Perceptual Understanding and Video Coding, 10-14 September, Athens, 2006.
  17. S Zhang and F W M Stentiford, “An attention based method for motion detection and estimation,” London Communications Symposium, 14-15th September, 2006.
  18. O Oyekoya and F W M Stentiford, “Perceptual Image Retrieval Using Eye Movements,” International Workshop on Intelligent Computing in Pattern Analysis/Synthesis, 26 August, Xi’an, China, 2006.
  19. O K Oyekoya and F W M Stentiford, “Eye Tracking: A New Interface for Visual Exploration,” BT Technology Journal, vol 24, no. 3, July 2006.
  20. O K Oyekoya and F W M Stentiford, “Eye tracking as a new interface for image retrieval,” Intelligent Spaces: the Application of Pervasive ICT, Springer-Verlag, London, pp 273-284, 2006.
  21. O Oyekoya and F W M Stentiford, “Perceptual Image Retrieval Using Eye Movements,” in Advances in Machine Vision, Image Processing and Pattern Analysis, Vol 4153, pp 281-289, Springer Berlin / Heidelberg, 2006.  doi: 10.1007/11821045.
  22. A Bamidele, F W M Stentiford and J Morphett, “An attention based approach to content based image retrieval,” Intelligent Spaces: the Application of Pervasive ICT , Springer-Verlag, London, pp 257-269, 2006.
  23. O. Oyekoya and F. W. M. Stentiford, "An eye tracking interface for image search," Eye Tracking Research & Applications Symposium, March 27-29, San Diego, 2006.
  24. F. W. M. Stentiford and M Walker, "Attention based colour correction," in Human Vision and Electronic Imaging XI, SPIE Conf., San Jose, 15-19 Jan., 2006. Demo at http://colourcorrection.bat.bt.co.uk/ColourCorrection/
  25. M. Davis, M. Smith, F. Stentiford, A. Bamidele, J. Canny, N. Good, S. King, R. Janakiraman, “Using context and similarity for face and location identification,” SPIE Internet Imaging VII, San Jose, Jan. 2006.
  26. A. Bamidele and F. W. M. Stentiford, "An attention based similarity measure used to identify image clusters," , 2nd European Workshop on the Integration of Knowledge, Semantics & Digital Media Technology, London, 30th Nov. - 1st Dec., 2005.
  27. O. Oyekoya and F. W. M. Stentiford, "A performance comparison of eye tracking and mouse interfaces in a target image identification task," 2nd European Workshop on the Integration of Knowledge, Semantics & Digital Media Technology, London, 30th Nov. - 1st Dec., 2005.
  28. F. W. M. Stentiford, "Attention based symmetry in colour images," IEEE International Workshop on Multimedia Signal Processing, Shanghai, China, Oct 30 - Nov 2, 2005.
  29. F. W. M. Stentiford, "Attention based facial symmetry detection," International Conference on Advances in Pattern Recognition, Bath, UK, 22-25 August, 2005.
  30. M Fitch, K Briggs, I Boyd, and F W M Stentiford, “Gaussian multi-level FM for high-bandwidth satellite communications,” 29th World Telecommunications Congress, Seoul, 12-15 September, 2004.
  31. F. W. M. Stentiford, "A visual attention estimator applied to image subject enhancement and colour and grey level compression," International Conference on Pattern Recognition 2004, Cambridge, 23-26 August, 2004.
  32. O. Oyekoya and F. W. M. Stentiford, "Exploring human eye behaviour using a model of visual attention," International Conference on Pattern Recognition 2004, Cambridge, 23-26 August, 2004.
  33. F. W. M. Stentiford, “The measurement of the salience of targets and distractors through competitive novelty,” 26th European Conference on Visual Perception, Paris, September 1-5, 2003. (Poster)
  34. A. P. Bradley and F. W. M. Stentiford, “Visual attention for region of interest coding in JPEG 2000,” Journal of Visual Communication and Image Representation, vol 14, pp 232 - 250, 2003.
  35. F. W. M. Stentiford, “An attention based similarity measure for fingerprint retrieval,”  Proc. 4th European Workshop on Image Analysis for Multimedia Interactive Services, pp 27-30, London, April 9-11, 2003.
  36. F. W. M. Stentiford, “An attention based similarity measure with application to content based information retrieval,” in Storage and Retrieval for Media Databases 2003, M. M. Yeung, R. W. Lienhart, C-S Li, Editors, Proc SPIE Vol. 5021, 20-24 Jan, Santa Clara, 2003.
  37. M. Roach, J. Mason, L-Q. Xu, and F. W. M. Stentiford, “Recent trends in video analysis: a taxonomy of video classification problems,” 6th IASTED Int. Conf. on Internet and Multimedia Systems and Applications, Hawaii, Aug 12-14, 2002.
  38. F. W. M. Stentiford, N. Morley, and A. Curnow, “Automatic identification of regions of interest with application to the quantification of DNA damage in cells,” in Human Vision and Electronic Imaging VII, B. E. Rogowitz, T. N. Pappas, Editors, Proc SPIE Vol. 4662, pp 244-253, San Jose, 20-26 Jan, 2002.
  39. A. P. Bradley and F. W. M. Stentiford, “JPEG 2000 and region of interest coding,” Digital Imaging Computing – Techniques and Applications, Melbourne, Australia, Jan 21-22, 2002.
  40. M. Russ, I. Kegel, and F. W. M. Stentiford, “Smart Realisation: delivering content smartly,” J. Inst. BT Engineers, Vol. 2, Part 4, pp 12-17, Oct-Dec 2001.
  41. F. W. M. Stentiford, “An evolutionary programming approach to the simulation of visual attention,” Congress on Evolutionary Computation, Seoul, May 27-30, 2001.
  42. F. W. M. Stentiford, “An estimator for visual attention through competitive novelty with application to image compression,” Proc. Picture Coding Symposium, pp 101-104, Seoul, 24-27 April, 2001.
  43. L-Q. Xu, J. Zhu, and F. W. M. Stentiford, “Video summarisation and semantic editing tools,” in Storage and Retrieval for Media Databases, Proc SPIE Vol. 4315, San Jose, 21 - 26 Jan, 2001.
  44. F. W. M. Stentiford, “Evolution: the best possible search algorithm?,” BT Technology Journal, Vol. 18, No 1, January 2000. (Movie version)
  45. K. Curtis, P. W. Foster, and F. W. M. Stentiford, “Metadata – the key to content management services,” 3rd IEEE Metadata Conference, April 6 – 7, 1999.

Related Publications

  1. F. W. M. Stentiford, “Automatic feature design for OCR using an evolutionary search procedure,” IEEE Trans PAMI, Vol. 7, No 3, May 1985.
  2. F. W. M. Stentiford, “Some new heuristics for thinning binary handprinted characters for OCR,” IEEE Trans on Systems, Man, and Cybernetics, Vol. SMC-13, No. 1, Jan.Feb 1983.
  3. F. W. M. Stentiford, “An evolutionary approach to the concept of randomness,” British Computer Journal, Vol. 16, No 2, May 1973.

 

 

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