Research Director, Professor Andrew Blake

Professor Andrew Blake is Research Director at The Alan Turing Institute. Prior to joining the Institute in 2015, Professor Blake held the position of Microsoft Distinguished Scientist and Laboratory Director of Microsoft Research Cambridge, England. He joined Microsoft in 1999 as a Senior Researcher to found the Computer Vision group. In 2008 he became a Deputy Managing Director at the lab, before assuming the directorship in 2010. Before joining Microsoft Andrew trained in mathematics and electrical engineering in Cambridge England, and studied for a doctorate in Artificial Intelligence in Edinburgh. He was an academic for 18 years, latterly on the faculty at Oxford University, where he was a pioneer in the development of the theory and algorithms that can make it possible for computers to behave as seeing machines.

Professor Blake has published several books including “Visual Reconstruction” with A.Zisserman (MIT press), “Active Vision” with A. Yuille (MIT Press) and “Active Contours” with M. Isard(Springer-Verlag). He has twice won the prize of the European Conference on Computer Vision, with R. Cipolla in 1992 and with M. Isard in 1996, and was awarded the IEEE David Marr Prize (jointly with K. Toyama) in 2001.

In 2006 the Royal Academy of Engineering awarded him its Silver Medal and in 2007 the Institution of Engineering and Technology presented him with the Mountbatten Medal(previously awarded to computer pioneers Maurice Wilkes and Tim Berners-Lee, amongst others.) He was elected Fellow of the Royal Academy of Engineering in 1998, Fellow of the IEEE in 2008, and Fellow of the Royal Society in 2005. In 2010, Andrew was elected to the council of the Royal Society. In 2011, he and colleagues at Microsoft Research received the Royal Academy of EngineeringMacRobert Award for their machine learning contribution to Microsoft Kinect human motion-capture. In 2012 Andrew was elected to the board of the EPSRC and also received an honorary degree of Doctor of Science from the University of Edinburgh. In 2013 Andrew was awarded an honorary degree of Doctor of Engineering from the University of Sheffield. In 2014, Andrew gave the prestigious Gibbs lecture at the Joint Mathematics Meetings (transcript available here). Professor Andrew Blake has been named as the recipient of the 2016 BCS Lovelace Medal, the top award in computing in the UK, awarded by BCS, The Chartered Institute for IT. The award is presented annually to individuals who, in the opinion of BCS, have made a significant contribution to the advancement of Information Systems.

  • Publications

    • J. Shotton, R. Girshick, A. Fitzgibbon, T. Sharp, M. Cook, M. Finocchio, R. Moore, P. Kohli, A. Criminisi, A. Kipman, A. Blake (2013). Efficient Human Pose Estimation from Single Depth Images. Decision Forests for Computer Vision and Medical Image Analysis. PDF
    • D.J. Holland, J. Mitchell, A. Blake, and L. F. Gladden (2013). Grain Sizing in Porous Media using Bayesian Magnetic Resonance. Physical Review Letters. PDF
    • A.A. Muryy, A.E. Welchman, A. Blake, R.W. Fleming (2013). Specular Reflections and the Estimation of Shape from Binocular Disparity. Proceedings of the National Academy of Sciences of the United States. PNAS
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden (2012). Bubble Size Measurement Using Bayesian Magnetic Resonance. Chemical Engineering Science. PDF
    • J.G. Rossa, D.J. Holland, A. Blake, A.J. Sederman, L.F. Gladden (2012). Extending the use of Earth’s Field NMR using Bayesian methodology: Application to Particle Sizing. Journal of Magnetic Resonance. PDF
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden (2011). A Bayesian Approach to Characterising Multi-phase Flows Using Magnetic Resonance: Application to Bubble Flows. Journal of Magnetic Resonance. PDF Science Direct
    • J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake (2011), Real-Time Human Pose Recognition in Parts from a Single Depth Image, in CVPR (Best Paper), IEEE. PDF
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden. (2011). A Bayesian Approach to Characterising Multi-phase Flows Using Magnetic Resonance: Application to Bubble Flows. Journal of Magnetic Resonance. 209(1), 83-7.Download
    • V. Gulshan, C. Rother, A. Criminisi, A. Blake, and A. Zisserman (2010). Geodesic Star Convexity for Interactive Image Segmentation, Proc. IEEE Conf. Computer Vision and Pattern Recognition. PDF
    • D.J. Holland, D.M. Malioutov, A. Blake, A.J. Sederman and L.F. Gladden (2010). Reducing Data Acquisition Times in Phase-encoded Velocity Imaging Using Compressed Sensing. Journal of Magnetic Resonance. 203, 2, 236-246. In press.
    • D. Cremers, Y. Boykov, A. Blake, F. R. Schmidt:, eds (2009). Energy Minimization Methods in Computer Vision and Pattern Recognition, in EMMCVPR. PDF
    • P. Parasoglou, D. Malioutov, A.J. Sederman, J. Rasburn, H. Powell, L.F. Gladden, A. Blake and M.L. Johns (2009). Quantitative Single Point Imaging with Compressed Sensing. Journal of Magnetic Resonance. 201, 1, 72-80. PDF
    • B. Amberg, A. Blake, T. Vetter (2009). On Compositional Image Alignment with an Application to Active Appearance Models. IEEE Conf. Computer Vision and Pattern Recognition. PDF
    • V. S. Lempitsky, M.Verhoek, J. A. Noble, A. Blake (2009). Random Forest Classification for Automatic Delineation of Myocardium in Real-Time 3D Echocardiography. Functional Imaging and Modeling of the Heart. 447-456. PDF
    • Z. Yi, A. Criminisi, J. Shotton, and A. Blake (2009). Discriminative, Semantic Segmentation of Brain Tissue in MR Images. Medical Image Computing and Computer Assisted Intervention. PDF
    • V. Lempitsky, C. Rother, S. Roth, and A. Blake (2009). Fusion Moves for Markov Random Field Optimization. Microsoft Research Technical Report no. MSR-TR-2009-60, May 2009. Also IEEE Trans. PAMI, in press. PDF
    • P. V. Gehler, C. Rother, A. Blake, T. P. Minka, T. Sharp (2008). Bayesian Color Constancy Revisited. Proc. IEEE Conf. Computer Vision and Pattern Recognition. PDF
    • A. Criminisi, T. Sharp, A. Blake (2008). GeoS: Geodesic Image Segmentation. Proc. Eur. Conf. on Computer Vision, 99-112. PDF
    • V. S. Lempitsky, A. Blake, C. Rother(2008). Image Segmentation by Branch-and-Mincut. Proc. Eur. Conf. on Computer Vision, 15-29. PDF
    • J. Shotton, A. Blake, R. Cipolla (2008). Multiscale Categorical Object Recognition Using Contour Fragments. IEEE Trans. Pattern Anal. Mach. Intell. 30(7), 1270-1281. PDF
    • J. Shotton, A. Blake, R. Cipolla (2008). Efficiently Combining Contour and Texture Cues for Object Recognition.Proc. British Machine Vision Conf. PDF
    • A. W. Fitzgibbon, D.P. Robertson, A. Criminisi, S. Ramalingam, A. Blake (2007). Learning priors for calibrating families of stereo cameras. Proc. Int. Conf. Computer Vision, 1-8. PDF
    • V. S. Lempitsky, C. Rother, A. Blake (2007). LogCut – Efficient Graph Cut Optimization for Markov Random Fields. Proc. Int. Conf. Computer Vision, 1-8. PDF
    • B. Amberg, A. Blake, A.W. Fitzgibbon, S. Romdhani, T. Vetter (2007). Reconstructing High Quality Face-Surfaces using Model Based Stereo. Proc. Int. Conf. Computer Vision, 1-8. PDF
    • A. Agarwal, S. Izadi, M. Chandraker, A. Blake (2007). High Precision Multi-touch Sensing on Surfaces using Overhead Cameras. Tabletop, 197-200.
    • S. Izadi, A. Agarwal, A. Criminisi, J.M. Winn, A. Blake, A.W. Fitzgibbon (2007). C-Slate: A Multi-Touch and Object Recognition System for Remote Collaboration using Horizontal Surfaces. Tabletop, 3-10. PDF
    • A. Criminisi, A. Blake, C. Rother, J. Shotton, P.H.S. Torr (2007). Efficient Dense Stereo with Occlusions for New View-Synthesis by Four-State Dynamic Programming. International Journal of Computer Vision 71(1), 89-110. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross, C. Rother (2006). Probabilistic Fusion of Stereo with Color and Contrast for Bi-Layer Segmentation. Int. Journal of Computer Vision 76(2), 107. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross and C. Rother (2006). Probabilistic Fusion of Stereo with Colour and Contrast for Bi-layer Segmentation. IEEE Trans. Pattern Analysis and Machine Intelligence, 480-1492. PDF
    • C. Rother, L. Bordeaux, Y. Hamadi and A. Blake (2006). AutoCollage. ACM Trans. Graphics (SIGGRAPH), 847-852. PDF
    • A. Criminisi, J. Shotton, A. Blake, C Rother and PHS Torr (2006). Efficient Dense Stereo with Occlusions for New View-synthesis by Four-state Dynamic Programming. Int. J. Computer Vision, 0920-5691. PDF
    • A. Agarwal and A. Blake (2006). The Panum Proxy Algorithm for Dense Stereo Matching Over a Volume of Interest. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2339-2346. PDF
    • A. Criminisi, G. Cross and A. Blake (2006). Bilayer Segmentation of Live Video. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 53-60. PDF
    • O. Williams, A. Blake and R Cipolla (2006). Sparse and Semi-supervised Visual Mapping with S3GP. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 230-237. PDF
    • C. Rother, V. Kolmogorov, T. Minka and A. Blake (2006). Cosegmentation of Image Pairs by Histogram Matching Incorporating a Global Constraint into MRFs. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 993-1000. PDF
    • O. Williams, A. Blake, and R. Cipolla (2005). Sparse Bayesian regression for efficient visual tracking. IEEE Trans Pattern Analysis and Machine Intelligence, 27, 8, 12921304. PDF
    • A. Blake (2005). Visual tracking: a short research roadmap. In Mathematical Models of Computer Vision: The Handbook, eds. O. Faugeras, Y. Chen and N. Paragios, Springer, in press. PDF
    • J. Shotton, A. Blake and R. Cipolla (2005). Contour-based learning for object recognition. Proc. Int. Conf. Computer Vision, 1, 503510. PDF
    • C. Rother, S. Kumar, V. Kolmogorov and A. Blake (2005). Digital Tapestry. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2, 589596. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross and C. Rother (2005). Bi-layer segmentation of binocular stereo. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2,407414. PDF
    • O. Williams, A. Blake, and R. Cipolla (2004). The Variational Ising Classifier (VIC) algorithm for coherently contaminated data. Proc Neural Information Processing Systems, 17. PDF
    • J. Winn and A. Blake (2004). Generative affine localisation and tracking. Proc Neural Information Processing Systems, 17. PDF
    • S.Romdhani, P. Torr, B. Schoelkopf and A. Blake (2004). Efficient face detection by a cascaded support-vector machine expansion. Proc. Roy. Soc. A, 460, 2501, 32833297. PDF
    • C. Rother, V. Kolmogorov and A. Blake (2004). GrabCut interactive foreground extraction using iterated graph cuts. ACM Trans. Graphics (SIGGRAPH), 309314. PDF
    • A. Blake, C. Rother, M. Brown, P. Perez, and P. Torr (2004). Interactive image segmentation using an adaptive GMMRF model. Proc. Eur. Conf. on Computer Vision (ECCV), Springer-Verlag, 428441. PDF
    • P. Perez, J. Vermaak and A. Blake (2004). Data fusion for visual tracking with particles. Proc. IEEE, 92, 3, 495513. PDF
    • P. Perez, M. Gangnet and A. Blake (2003). Poisson image editing. ACM Trans. Graphics (SIGGRAPH), 2(3):313-318. PDF
    • A. Criminisi, J. Shotton, A. Blake and P.H.S. Torr (2003). Gaze manipulation for one to one teleconferencing. Proc. Int. Conf. on Computer Vision (ICCV), 191198. PDF
    • O. Williams, A. Blake and R. Cipolla (2003). A sparse probabilistic learning algorithm for realtime tracking. Proc. Int. Conf. on Computer Vision (ICCV), 353360. PDF
    • K. Toyama and A. Blake (2002). Probabilistic tracking with exemplars in a metric space. Int. J. Computer Vision, 48, 919. PDF
    • J. Rittscher, T. Watanabe, J. Kato, S. Joga and A. Blake (2002). An HMM-based segmentation method for traffic monitoring. IEEE Trans. Pattern Analysis and Machine Intelligence, 24, 9. PDF
    • P. Prez, A. Blake, and M. Gangnet (2001). JetStream: Probabilistic contour extraction with particles. Proc. Int. Conf. on Computer Vision (ICCV), II:524-531. PDF
    • J. Vermaak, A. Blake, M. Gangnet, and P. Perez (2001). Sequential Monte Carlo fusion of sound and vision for speaker tracking. Proc. Int. Conf. on Computer Vision (ICCV), I:741-746. PDF
    • J. Sullivan, A. Blake, M. Isard and J. MacCormick (2001). Bayesian Object Localisation in Images. Int. J. Computer Vision, 44, 2, 111-136. PDF
    • J. Deutscher, A. Blake and I. Reid (2000). Articulated Body Motion Capture by Annealed Particle Filtering Proc. Conf. Computer Vision and Pattern Recognition, 2, 126 133. Abstract and .ps.gz and movies
    • B. North, A. Blake, M. Isard and J. Rittscher. (2000). Learning and Classification of Complex Dynamics. IEEE Trans. Pattern Analysis and Machine Intelligence, 22, 9, 10161034. PDF
    • J. MacCormick and A. Blake (2000). Probabilistic exclusion and partitioned sampling for multiple object tracking. Int. J. Computer Vision, 39(1), 57-71, 2000. PDF
    • R. A. Eagle, M.A. Hogervorst and A. Blake. (1999). Does the visual system exploit projective geometry to help solve the motion correspondence problem? Vision Research, 39, 373-385.
    • E. Rimon and A. Blake (1999). Caging planar bodies by 1-parameter, two-fingered gripping systems. Int. J. Robotics Research, 18, 3, 299-318.
    • A. Blake and M. Isard (1998). Active Contours. Springer-Verlag.
    • A. Blake, B. Bascle, M. Isard and J. McCormick (1998). Statistical models of visual shape and motion. Phil. Trans. Roy. Soc. B, 356, 1283-1302. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). CONDENSATION – Conditional density propagation for visual tracking. Int. J. Computer Vision, 29, 1, 5-28. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). A mixed-state Condensation tracker with automatic model switching. Proc 6th Int. Conf. Computer Vision, 107-112. Abstract and .ps.gz
    • B. Bascle and A. Blake (1998). Separability of pose and expression in facial tracking and animation. Proc 6th Int. Conf. Computer Vision, 323-328. Abstract and .ps.gz
    • J. MacCormick and A. Blake (1998). A probabilistic contour discriminant for object localisation. Proc 6th Int. Conf. Computer Vision, 390-395. Abstract and .ps.gz
    • R. Kaucic and A. Blake (1998). Accurate, Real-Time, Unadorned Lip Tracking. Proc 6th Int. Conf. Computer Vision, 370-375. Abstract and .ps.gz
    • C. Davidson and A. Blake (1998). Caging planar objects with a three-finger, one-parameter gripper Proc IEEE Int. Conf. Robotics and Automation, 2722-2727. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). A smoothing filter for Condensation model switching. Proc European Conf. Computer Vision, 768-781. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). ICondensation: Unifying low-level and high-level tracking in a stochastic framework Proc European Conf. Computer Vision, 893-908. Abstract and .ps.gz
    • R. Cipolla and A. Blake (1997). Image divergence and deformation from closed curves. Int. J. Robotics Research, 16, 1, 77-96. Abstract and .ps.gz
    • D. Buckley, J.P. Frisby and A. Blake (1996). Does the human visual system implement an ideal observer theory of slant from texture? Vision Research, 36, 8, 1163-1176.
    • D. Sinclair and A. Blake. (1996) Quantitative planar region detection. International Journal of Computer Vision, 18, 1, 77-91.
    • S. Rowe and A. Blake (1996). Statistical mosaics for tracking. J. Image and Vision Computing, 14, 8, 549-564. Abstract, .ps.gz
    • M. Isard and A. Blake (1996). Contour tracking by stochastic propagation of conditional density. Proc European Conf. Computer Vision, Cambridge, UK, 343-356. Abstract and .ps.gz
    • B. Bascle, A. Blake and A. Zisserman (1996). Motion deblurring and super-resolution from an image sequence. Proc European Conf. Computer Vision, Cambridge, UK, 573-582. Abstract and .ps.gz
    • D. Reynard, A. Wildenberg, A. Blake and J. Marchant (1996). Learning Dynamics of Complex Motions from Image Sequences. Proc European Conf. Computer Vision, Cambridge, UK, 357-368. Abstract and .ps.gz
    • E. Rimon and A. Blake (1996). Caging 2D bodies by one-parameter, two-fingered gripping systems. Proc Int. Conf. Robotics and Automation, 1458-1464, IEEE Press. PDF
    • A. Blake (1995). A symmetry theory of planar grasp. Int. J. Robotics Research, 14, 5, 425-444. Abstract and .ps.gz
    • A. Blake, M. Isard and D. Reynard (1995). Learning to track the visual motion of contours. Artificial Intelligence, 78, 101-134. Abstract and .ps.gz
    • R. A. Eagle and A. Blake. (1995). Two-dimensional constraints on three-dimensional structure from motion tasks. Vision Research, 35, 20, 2927-2941. PDF
    • A. Blake- (1994). Uncertain views. Nature, 368, 498-499.
    • D. Sinclair, A. Blake and D. Murray. (1994). Robust estimation of ego-motion from normal flow. Int. J. Computer Vision, 13, 1, 57-69.
    • A. Blake and M. Isard (1994). 3D position, attitude and shape input using video tracking of hands and lips. Proc. ACM SIGGRAPH Conference, Orlando, USA, 185-192. Abstract and .ps.gz
    • R. Brockett and A. Blake (1994). Estimating the shape of a moving planar curve. Proc. IEEE Int. Conf. Decision Theory and Control, 3247-3252. PDF
    • A. Blake, D. McCowen, H.R. Lo, P.J. Lindsey (1993). Trinocular active range sensing. IEEE Trans. Pattern Analysis and Machine Intelligence, 15, 5, 477-483. PDF
    • A. Blake, H.H. B-ulthoff and D. Sheinberg (1993). Shape from Texture: Ideal Observers and Human Psychophysics Vision Research, 33, 12, 1723-1737. PDF
    • A. Blake, R. Curwen and A. Zisserman (1993). A framework for spatio-temporal control in the tracking of visual contours. Int. J. Computer Vision, 11, 2, 127-145. Abstract and .ps.gz
    • A. Blake, M. Taylor and A. Cox (1993). Grasping visual symmetry. Proc 4th Int. Conf. Computer Vision, Berlin, 724-733. PDF
    • -A. Blake (1992). Computational modelling of hand-eye coordination. Phil. Trans. Roy. Soc. B, 337, 351-360.
    • R. Cipolla and A. Blake (1992). Surface shape from the deformation of apparent contours. Int. J. Computer Vision, 9, 2, 83-112. PDF
    • R. Cipolla and A. Blake (1992). Surface orientation and time to contact from image divergence and deformation. Proc. 2nd European Conf. Computer Vision, Springer-Verlag, 465 474
    • A. Blake and A. Yuille, editors, (1992). Active Vision. MIT Press.
    • A. Blake and H.H. B-ulthoff (1991). Shape from specularities: computation and psychophysics. Phil. Trans. Roy. Soc. B, 331, 237-252. PDF
    • L. Tarassenko and A. Blake (1991). Analogue computation of collision-free paths. Proc. IEEE Int. Conf. Robotics and Automation, 540-545. PDF
    • A. Blake and C. Marinos (1990). Shape from texture: estimation, isotropy and moments. J. Artificial Intelligence, 45(3), 323-380. PDF
    • A. Blake and H. B-ulthoff (1990). Does the brain know the physics of specular reflection? Nature, 343(6254):165-168. PDF
    • A. Blake and R. Cipolla (1990). Robust estimation of surface curvature from deformation of apparent contours. Proc. 1st European Conf. on Computer Vision, Springer-Verlag, 465-474.
    • R. Cipolla and A. Blake. (1990). The Dynamic Analysis of Apparent Contours. Proc. 3rd Int. Conf. Computer Vision, Osaka, Japan, 616-625. PDF
    • C. Marinos and A. Blake (1990). Shape from texture: the homogeneity hypothesis. Proc. 3rd Int. Conf. Computer Vision, Osaka, Japan, 350-334. PDF
    • A. Blake (1989). Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction. IEEE Trans. Pattern Analysis and Machine Intelligence, 11, 1, 2-12. PDF
    • A.Blake and A. Zisserman. (1987). Visual Reconstruction. MIT Press, Cambridge, USA. PDF
    • A. Blake (1985). Boundary conditions for lightness computation in Mondrian World. Computer Vision, Graphics and Image Processing, 32, 314-327. PDF
    • A. Blake (1985). Specular stereo. Proc. Int. Joint Conf. on Artificial Intelligence 973-976.
    • A. Blake (1984). Reconstructing a visible surface. Proc. Conf. American Association for Artificial Intelligence, 23-26.
    • A. Blake (1983). The least-disturbance principle and weak constraints. Pattern Recognition Letters, 1, 393-399. PDF
    • A. Blake (1982). Fixed point solutions of recursive operations on boolean arrays. Computer Journal, 25, 2, 231-233.J.
  • Books

    Markov Random Fields for Vision and Image Processing (2011)

    Edited by Andrew Blake, Pushmeet Kohli and Carsten Rother

    Markov Random Fields for Vision and Image Processing demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications.

    Markov Random Fields for Vision and Image Processing MIT Press

    Markov Random Fields for Vision and Image Processing (2011)

    Active Contours (1998)

    By Andrew Blake and Michael Isard

    Active Contours is about the computer analysis of moving video images. It develops geometric and probabilistic models for shapes and their dynamics. The models are applied to the real-time analysis of shapes in motion, and addresses issues of learning, temporal filtering and the problems of visual clutter. Numerous applications are illustrated from computer graphics animation, user-interface design, medical imaging, automated surveillance and robotics.

    Active Contours Springer-Verlag

    Active Contours (1998)

    Active Vision (1992)

    Edited by Andrew Blake and Alan Yuille

    Active Vision explores important themes emerging from the active vision paradigm at the time of publication, which had only recently become an established area of machine vision. In four parts the contributions look in turn at tracking, control of vision heads, geometric and task planning, and architectures and applications, presenting research that marked a turning point for both the tasks and the processes of computer vision.

    Active Vision (1992)

    Visual Reconstruction (1987)

    By Andrew Blake and Andrew Zisserman

    Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. Two concepts, which were new at the time of publication, are introduced, analyzed, and illustrated.

    Visual Reconstruction (1987)

  • Short CV

    1974-77 Scholar in mathematics, Trinity College Cambridge.
    1977 BA Electrical Sciences, 1st class with distinction.
    1977-78 Kennedy Fellow at Massachusetts Institute of Technology, Cambridge, USA.
    1978-80 Scientist with Ferranti Edinburgh, Electro-optics group.
    1980-83 Research Associate and Ph.D. student at Edinburgh University. Awarded Ph.D. in Computer Vision, 1983.
    1983-87 Lecturer in Computer Science, Edinburgh University.
    1984-87 Royal Society Research Fellow.
    1987-96 Lecturer in Image Processing, Dept. Engineering Science, University of Oxford.
    1987-99 Fellow of Exeter College, Oxford.
    1996-9 Professor of Engineering Science, University of Oxford.
    1998-9 Royal Society Senior Research Fellow.
    1999-02 Senior Research Scientist, Microsoft Research, Cambridge.
    1999 Visiting Professor of Engineering Science, University of Oxford.
    2000 Fellow of Clare Hall, University of Cambridge.
    2002 Principal Research Scientist, Microsoft Research.
    2005 Partner, Microsoft Corporation.
    2006 Visiting Professor of Informatics University of Edinburgh.
    2007 Visiting Professor of Machine Intelligence, University of Cambridge.
    2008 Deputy Laboratory Director Microsoft Research Cambridge
    2010 Microsoft Distinguished Scientist & Laboratory Director, Microsoft Research Cambridge
    1977 Lamb prize of the University of Cambridge for Electrical Sciences.
    1977 ver Heyden der Lancey prize, Trinity College, Cambridge.
    1977-78 John F. Kennedy Fellow, MIT, USA.
    1984 Nominated for publisher-s prize at the American Association for Artificial Intelligence (AAAI) conference, in Austin, Texas.
    1984-87 Awarded the Royal Society IBM Research Fellowship.
    1986 Commendation for paper presented to the IEEE Conference on Computer Vision and Pattern Recognition, Miami, USA.
    1987 Appointed Associate Editor of J. Image and Vision Computing, Butterworth.
    1991-92 Associate Editor of Transactions on Pattern Analysis and Machine Intelligence of the IEEE.
    1991-90 Editorial board, Vision Research, Pergamon Press.
    1991 Appointed joint organiser (with Professors D.Mumford, Harvard and B.Ripley, Oxford) of a 6 month programme in Computer Vision for 1993, at the Isaac Newton Institute, Cambridge, UK.
    1992 Winner (with R. Cipolla) of the biennial prize of the European Vision Society.
    1993 Visiting Fellowship at Clare Hall, Cambridge, July-December.
    1993 Appointed to the Editorial board, International Journal Computer Vision, Kluwer.
    1994 Elected Fellow of the Institute of Electrical Engineers.
    1994-5 Program Chairman, IEEE International Conference on Computer Vision, Cambridge, USA.
    1996 Winner (with M. Isard) of the biennial prize of the European Vision Society.
    1996 Paper (with E. Rimon) nominated for the annual prize of the IEEE Robotics and Automation society.
    1997-02 Editorial board member for Computer Vision and Image Understanding, Academic Press.
    1998 Elected Fellow of the Royal Academy of Engineering.
    1998-9 Program Chairman, IEEE International Conference on Computer Vision, Greece.
    1998-9 Royal Society Senior Research Fellow (Amersham).
    2000 Elected Fellow of Clare Hall College, Cambridge.
    2000-5 Appointed to the Technical Advisory Board of the Max Planck Institute for Biological Cybernetics, T-ubingen.
    2001-4 Appointed to the Governing Body of the BBSRC Silsoe Research Institute, UK.
    2001 Awarded (with K. Toyama) the David Marr Prize of the IEEE, for Computer Vision.
    2004 Elected the Distinguished Fellow of the British Machine Vision Association for 2004.
    2005 Awarded (with V. Kolmogorov, A. Criminisi, G. Cross, C. Rother) honourable mention for best paper at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
    2005 Promoted to Partner, Microsoft Corporation.
    2005 Elected Fellow of the Royal Society.
    2006 Awarded Silver Medal of Royal Academy of Engineers.
    2007 Awarded Mountbatten Medal of the Institution of Engieering and Technology.
    2008 Elected fellow of the IEEE.
    2010 Elected to the Council of the Royal Society
    2010 Appointed Laboratory Director, Microsoft Research Cambridge
    2011 Recipient of Royal Academy of Engineering MacRobert Award
    2012 Elected to the Board of the EPSRC
  • Favourite Publications

    • A. Blake (1985). Boundary conditions for lightness computation in Mondrian World. Computer Vision, Graphics and Image Processing, 32, 314-327. PDF
    • A. Blake (1989). Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction. IEEE Trans. Pattern Analysis and Machine Intelligence, 11, 1, 2-12. PDF
    • A. Blake and C. Marinos (1990). Shape from texture: estimation, isotropy and moments. J. Artificial Intelligence, 45(3), 323-380. PDF
    • A. Blake and H. B-ulthoff (1990). Does the brain know the physics of specular reflection? Nature, 343(6254):165-168. PDF
    • A. Blake and H.H. B-ulthoff (1991). Shape from specularities: computation and psychophysics. Phil. Trans. Roy. Soc. B, 331, 237-252. PDF
    • L. Tarassenko and A. Blake (1991). Analogue computation of collision-free paths. Proc. IEEE Int. Conf. Robotics and Automation, 540-545. PDF
    • R. Cipolla and A. Blake (1992). Surface shape from the deformation of apparent contours. Int. J. Computer Vision, 9, 2, 83-112. PDF
    • A. Blake, H.H. B-ulthoff and D. Sheinberg (1993). Shape from Texture: Ideal Observers and Human Psychophysics Vision Research, 33, 12, 1723-1737. PDF
    • A. Blake, R. Curwen and A. Zisserman (1993). A framework for spatio-temporal control in the tracking of visual contours. Int. J. Computer Vision, 11, 2, 127-145. Abstract and .ps.gz
    • A. Blake and M. Isard (1994). 3D position, attitude and shape input using video tracking of hands and lips. Proc. ACM SIGGRAPH Conference, Orlando, USA, 185-192. Abstract and.ps.gz
    • R. Brockett and A. Blake (1994). Estimating the shape of a moving planar curve. Proc. IEEE Int. Conf. Decision Theory and Control, 3247-3252. PDF
    • A. Blake (1995). A symmetry theory of planar grasp. Int. J. Robotics Research, 14, 5, 425-444. Abstract and .ps.gz
    • A. Blake, M. Isard and D. Reynard (1995). Learning to track the visual motion of contours. Artificial Intelligence, 78, 101-134. Abstract and .ps.gz
    • R. A. Eagle and A. Blake. (1995). Two-dimensional constraints on three-dimensional structure from motion tasks. Vision Research, 35, 20, 2927-2941. PDF
    • M. Isard and A. Blake (1996). Contour tracking by stochastic propagation of conditional density. Proc European Conf. Computer Vision, Cambridge, UK, 343-356. Abstract and .ps.gz
    • D. Reynard, A. Wildenberg, A. Blake and J. Marchant (1996). Learning Dynamics of Complex Motions from Image Sequences. Proc European Conf. Computer Vision, Cambridge, UK, 357-368. Abstract and .ps.gz
    • E. Rimon and A. Blake (1996). Caging 2D bodies by one-parameter, two-fingered gripping systems. Proc Int. Conf. Robotics and Automation, 1458-1464, IEEE Press. PDF
    • R. Cipolla and A. Blake (1997). Image divergence and deformation from closed curves. Int. J. Robotics Research, 16, 1, 77-96. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). ICondensation: Unifying low-level and high-level tracking in a stochastic framework Proc European Conf. Computer Vision, 893-908. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). A mixed-state Condensation tracker with automatic model switching. Proc 6th Int. Conf. Computer Vision, 107-112. Abstract and .ps.gz
    • J. MacCormick and A. Blake (2000). Probabilistic exclusion and partitioned sampling for multiple object tracking. Int. J. Computer Vision, 39(1), 57-71, 2000. PDF
    • B. North, A. Blake, M. Isard and J. Rittscher. (2000). Learning and Classification of Complex Dynamics. IEEE Trans. Pattern Analysis and Machine Intelligence, 22, 9, 1016-1034. PDF
    • J. Deutscher, A. Blake and I. Reid (2000). Articulated Body Motion Capture by Annealed Particle Filtering Proc. Conf. Computer Vision and Pattern Recognition, 2, 126- 133. Abstract and.ps.gz and movies
    • J. Sullivan, A. Blake, M. Isard and J. MacCormick (2001). Bayesian Object Localisation in Images. Int. J. Computer Vision, 44, 2, 111-136. PDF
    • J. Vermaak, A. Blake, M. Gangnet, and P. P-erez (2001). Sequential Monte Carlo fusion of sound and vision for speaker tracking. Proc. Int. Conf. on Computer Vision (ICCV), I:741-746. PDF
    • P. P-erez, A. Blake, and M. Gangnet (2001). JetStream: Probabilistic contour extraction with particles. Proc. Int. Conf. on Computer Vision (ICCV), II:524-531. PDF
    • K. Toyama and A. Blake (2002). Probabilistic tracking with exemplars in a metric space. Int. J. Computer Vision, 48, 9-19. PDF
    • O. Williams, A. Blake and R. Cipolla (2003). A sparse probabilistic learning algorithm for realtime tracking. Proc. Int. Conf. on Computer Vision (ICCV), 353-360. PDF
    • P. Perez, M. Gangnet and A. Blake (2003). Poisson image editing. ACM Trans. Graphics (SIGGRAPH), 2(3):313-318. PDF
    • C. Rother, V. Kolmogorov and A. Blake (2004). GrabCut – interactive foreground extraction using iterated graph cuts. ACM Trans. Graphics (SIGGRAPH), 309-314. PDF
    • C. Rother, L. Bordeaux, Y. Hamadi and A. Blake (2006). AutoCollage. ACM Trans. Graphics (SIGGRAPH), in press. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross and C. Rother (2006). Probabilistic fusion of stereo with colour and contrast for bi-layer segmentation. IEEE Trans. Pattern Analysis and Machine Intelligence, in press. PDF
    • V. S. Lempitsky, A. Blake, C. Rother(2008).Image Segmentation by Branch-and-Mincut. Proc. Eur. Conf. on Computer Vision, 15-29. PDF
    • J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake (2011), Real-Time Human Pose Recognition in Parts from a Single Depth Image. In Proc. IEEE CVPR (Best Paper). PDF
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden (2011), A Bayesian approach to characterising multi-phase flows using magnetic resonance: Application to bubble flows. J. Magnetic Resonance, 209, 1, 83–87. PDF Download