Keynote Speakers

Scott Acton is Professor of Electrical & Computer Engineering and of Biomedical Engineering at the University of Virginia. He received his M.S. and Ph.D. degrees at the University of Texas at Austin. He received his B.S. degree at Virginia Tech.

Professor Acton’s laboratory at UVA is called VIVA - Virginia Image and Video Analysis. They specialize in image analysis problems. Most work in VIVA is biomedically oriented and funded by the USA’s National Institutes of Health. Professor Acton has over 200 publications in the image analysis area including the recent book Biomedical Image Analysis: Tracking.

Professor Acton has been at the University of Virginia since 2000. Before that time, he worked in the academic world for Oklahoma State University and in the engineering world for AT&T, Motorola and the Mitre Corporation. When Scott is not being an engineer, he plays basketball (poorly) and golf (even worse). This past year, he spent his sabbatical in New Mexico USA.

Roy Davies is Professor of Machine Vision in the Department of Physics at Royal Holloway, University of London. He has been a leading figure in the areas of image processing and computer vision since the mid-1980s and has contributed greatly to both the field and the community. He was awarded the British Machine Vision Association Distinguished Fellowship in 2005.

Roy Davies was educated at Cardiff High School and Jesus College Oxford. He obtained his BA in Physics in 1963 and his DPhil in 1967. The title of his thesis was Electron and Nuclear Resonance Studies in Solids. His early career was based on spin transitions for nuclei and the related electronics, leading to the development of the 'Davies Electron-Nuclear Double Resonance' technique, better known as the 'Davies ENDOR' technique, a method that 35 years later is still regularly referenced in Physics journals. His interest in electronics, noise, and signal extraction or recovery led to the book “Electronics, Noise and Signal Recovery”, published in 1993, which integrated the entire area. The book for which Roy Davies is most well known to computer vision students, researchers, and academics all around the world is “Machine Vision: Theory, Algorithms, Practicalities”, originally published in 1990 and now in its 3rd Edition.

Overall, Roy Davies' career has been involved with making sense of data, and not just images, and in part by negotiation of noise and clutter in a systematic way. His DSc awarded by the University of London in 1996 reflects this major preoccupation. He has published extensively in the leading journals and conference proceedings on many aspects of computer vision, with his work falling under the main headings of image filtering, feature detection, intermediate level analysis, real-time operation, and automated visual inspection. His deep involvement in educational aspects has led to three books and numerous chapters and encyclopaedia articles.

Roy Davies’ combined interest in image analysis and real-time systems has kept him in popular demand by industry for investigating numerous industrial vision problems. He has specialised in algorithm design for automated visual inspection, and also has interests in vision in less constrained environments such as surveillance, crime detection and prevention, vehicle driver assistance, and laparoscopic surgery. Over many years a large proportion of his research funding has come from grants related to food inspection. This led to his third book, “Image Processing for the Food Industry”, published in 2000.

Roy Davies is widely recognised for his authority, popularity, and standing in the computer vision community. He has contributed immensely to the computer vision community through his numerous activities in the BMVA and the IEE; his work on many editorial boards (including Pattern Recognition Letters, Real-Time Imaging, Imaging Science and IET Image Processing); and his involvement in education, including examining over 100 PhD students.

Philip Torr is Professor in Computer Vision and Machine Learning at Oxford Brookes University, where he leads the Computer Vision group in the Department of Computing. He completed his DPhil at the Robotics Research Group of the University of Oxford and worked for a further three years at Oxford as a research fellow before taking up a post as a research scientist with Microsoft Research. He maintains close contact with the University of Oxford as a visiting fellow. He spent six years with Microsoft Research, first in Redmond USA in the Vision Technology Group, then in Cambridge UK founding the vision side of the Machine learning and perception group. He then moved to his current position at Oxford Brookes University, where he has brought in over one million pounds in grants for which he is Principal Investigator.

Philip Torr has won several prestigious awards for his work, including the IEEE Marr prize in 1998 for best paper at the International Conference of Computer Vision. Together with members of his Computer Vision group, he has recently been awarded prizes at IAPR ICVGIP (2005 and 2006) and an honorary mention at the Neural Information Processing Conference (NIPS 2007) for the paper "An Analysis of Convex Relaxations for MAP Estimation" (P. Kumar, V. Kolmorgorov, and P.H.S. Torr). Recent SIGGRAPH work on VideoTrace with the University of Adelaide has been featured extensively on the internet, including slashdot. He was involved in the algorithm design for 2D3’s Boujou camera and object tracking system, which has won a number of industry awards, including Computer Graphics World Innovation Award, IABM Peter Wayne Award, CATS Award for Innovation, and a technical EMMY. He continues to work closely with this Oxford based company as well as other companies such as Sony and Sharp.

Philip Torr is highly active in the organisation and delivery of Computer vision workshops and conferences worldwide. He is co-chair of the 10th European Conference on Computer Vision (ECCV 2008), October 2008, Marseille, France, and presenter of an Invited Tutorial on Optimization Methods for Computer Vision at the British Machine Vision Conference (BMVC 2008), September 2008.