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School of technology • |
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Phone +44 1865 484 592• Fax +44 1865 484 545• E—mail philiptorr@brookes.ac.uk |
Philip Hilaire Sean Torr
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For vision group publications see also Oxford Brookes Computer Vision Group Publications. For latex style bib entries see the excellent Keith Price Bibliography Note: The top 3 computer vision conferences (ICCV, ECCV, CVPR) are highly competitive with low acceptance rates of <30%. ICCV and ECCV have CiteSeer impact factor rankings in the top 5% and 7%, respectively, of all computer science journals and conferences. SIGGRAPH (ACM Transaction graphics) is the 9th ranked publication for all computer science (in the top 0.57% of computer science), ICCV: 58th (top 4.75%), ECCV: 88th (top 7.20%), IEEE Transactions on Pattern Analysis and Machine Intelligence: 103rd (top 8.43%), The International Journal of Computer Vision is at 147th (top 12.03%), Neural Information Processing Systems (NIPS) is at 256th (top 20.96%). |
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Patents and publications |
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Refereed Journal G. Rogez, J. Rihan, C. Orrite,
and P.H.S. Torr. Fast
Human Pose Detection Using Randomized Hierarchical Cascades of Rejectors, In International Journal of
Computer Vision, 2012. L. Ladick´y, C. Russell, P.
Kohli and P.H.S. Torr. Inference Methods for
CRFs’ with Co-occurrence Statistics, In International Journal of
Computer Vision, ECCV special award issue, 2011. P. Kumar, O. Veksler and P.H.S. Torr, Improved Moves for Truncated Convex Models, In Journal of Machine Learning Research, Vol 12(Jan), pages 31-67, 2011. L. Ladick´y, P. Sturgess, C.
Russell, S. Sengupta, Y. Bastanlar, W. Clocksin and P.H.S. Torr. Joint Optimisation for Object Class
Segmentation and Dense Stereo Reconstruction, In International
Journal of Computer Vision, BMVC special award issue, 2011. K. Alahari, P. Kohli, and P.H.S. Torr, Dynamic Hybrid Algorithms for Discrete MAP MRF Inference, In Proceedings IEEE Trans Pattern Analysis and Machine Intelligence, Vol 32, no 10, pages 1846-1857, 2010. M. Pawan. Kumar, P.H.S. Torr, and A. Zisserman. OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues. In Proceedings IEEE Trans Pattern Analysis and Machine Intelligence,, Vol 32, no 3, pages 530-545, 2010. P. Kohli, L’ubor Ladick´y, and P.H.S. Torr, Robust Higher Order Potentials for Enforcing Label Consistency, In International Journal of Computer Vision, Volume 82, Issue 3, pages 302-324, 2009. O. Woodford, P.H.S. Torr, I. Reid, and A.W. Fitzgibbon, Global Stereo Reconstruction under Second Order Smoothness Priors, In Proceedings IEEE Trans Pattern Analysis and Machine Intelligence, Volume 31, Issue 12, pages 2115-2128, 2009. M. Pawan Kumar, V. Kolmogorov and P.H.S. Torr An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs', In Journal of Machine Learning Research (JMLR), Volume 10, pages 71-106, 2009. P. Kohli, M. Pawan Kumar and P.H.S. Torr. P3 & Beyond: Move Making Algorithms for Solving Higher Order Functions. In IEEE Trans Pattern Analysis and Machine Intelligence, Volume 31, Issue 9, Pages 1645-1656 , 2008. P. Kohli, and P.H.S. Torr. Measuring Uncertainty in Graph Cut Solutions. In Journal of Computer Vision and Image Understanding, special issue Discrete Optimization in Computer Vision, Volume 112, Issue 1, Pages 30-38, 2008. P. Kohli, J. Rihan, M. Bray and P.H.S. Torr. Simultaneous Segmentation and Pose Estimation of Humans using Dynamic Graph Cuts. In International Journal of Computer Vision, Volume 79, Issue 3 pages 285-298, 2008. G. Vogiatzis, P.H.S. Torr, S.M. Seitz and R. Cipolla. Reconstructing relief surfaces. In Image and Vision Computing 26(3): 397-404 2008. M. Pawan Kumar, P.H.S. Torr and Andrew Zisserman. Learning Layered Motion Segmentations of Video, In International Journal of Computer Vision, 76, pages 301-319, 2008. A. Thayananthan, R. Navaratnam, B. Stenger, P.H.S. Torr and R. Cipolla. Pose Estimation and Tracking using Multivariate Regression , In Pattern Recognition Letters, Volume 29, Issue 9, 1, Pages 1302-1310, July 2008. A. Hengel, A. Dick, T. Thormahlen, B. Ward and P.H.S. Torr, VideoTrace: Rapid interactive scene modelling from video, In ACM Transactions on Graphics (SIGGRAPH special issue), Volume 26, Issue 3, 86, 2007. G. Vogiatzis, C. H. Esteban, P.H.S. Torr, and R. Cipolla. Multi-view stereo via Volumetric Graph-cuts and Occlusion Robust Photo Consistency. In IEEE Trans Pattern Analysis and Machine Intelligence, 29(12): 2241-2246 2007. B. Stenger, A. Thayananthan, P.H.S. Torr, and R. Cipolla. Estimating 3D hand pose using hierarchical multi-label classification, In Image and Vision Computing, 25(12), pages 1885-1894, 2007. P. Kohli and P.H.S. Torr. Dynamic Graph Cuts for Efficient Inference in Markov Random Fields. In IEEE Trans Pattern Analysis and Machine Intelligence, 29(12), pages 2079-2088, 2007. A Criminisi, J. Shotton, A. Blake, C. Rother and P.H.S. Torr. Efficient Dense Stereo with Occlusions for New View Synthesis by Four State Dynamic Programming, In International Journal of Computer Vision, 71(1), pages 89-110, 2007. B. Stenger, A. Thayananthan, P.H.S. Torr, and R. Cipolla. Model-Based Hand Tracking Using a Hierarchical Bayesian Filter, In IEEE Trans Pattern Analysis and Machine Intelligence, 28(9), pages 1372-1384, 2006. P.H.S. Torr and A. Fitzgibbon. Invariant Fitting of Two View Geometry or “In Defiance of the eight point algorithm”, In IEEE Trans Pattern Analysis and Machine Intelligence, 26(5), pages 648-651, 2004. S. Romdhani, P.H.S. Torr, B. Schölkopf, and A Blake. Efficient Face Detection by a Cascaded Reduced Support Vector Expansion. In Proceedings of the Royal Society Series A, 460(2501):3283-3297, Nov. 2004. A. R. Dick, P.H.S. Torr and R. Cipolla. Modelling and Interpretation of Architecture from Several Images. In International Journal of Computer Vision, 60(2), pages 111—134, 2004. P.H.S. Torr and A. Criminisi. Dense Stereo using Pivoted Dynamic Programming. In Image and Vision Computing, 22(10), pages 795-806, 2004. P.H.S. Torr and C. Davidson. IMPSAC: A synthesis of importance sampling and random sample consensus. In IEEE Trans Pattern Analysis and Machine Intelligence, 25(3), pages 354-365, 2003. P.H.S. Torr. Bayesian Model Estimation and Selection for Epipolar Geometry and Generic Manifold Fitting. In International Journal of Computer Vision, 50(1), pages 27—45, 2002. P.H.S. Torr, R. Szeliski, P. Anandan. An integrated Bayesian Approach to
Layer Extraction from Image Sequence. In IEEE Trans Pattern Analysis and Machine Intelligence, 23(3) 297-304, 2001. P.H.S. Torr and A. Zisserman. MLESAC: A New Robust Estimator with Application to Estimating Image Geometry. In Journal of Computer Vision and Image Understanding, pages 138—156, 78(1), 2000. P.H.S. Torr, A. Fitzgibbon and A. Zisserman. The Problem of Degeneracy in Structure and Motion Recovery from Uncalibrated Image Sequences. In International Journal of Computer Vision, 32(1), pages 27—45, 1999. P.H.S. Torr, A. Zisserman and S. Maybank. Robust Detection of Degeneracy. In Journal of Computer Vision and Image Understanding, pages 312—333, v 71, n 3, 1998. P.H.S. Torr. Geometric Motion Segmentation and Model Selection. In Philosophical Transactions of the Royal Society A, pages 1321—1340, 1998. P.H.S. Torr, and D.W. Murray. The Development and Comparison of Robust Methods for Estimating the Fundamental Matrix. In International Journal of Computer Vision, pages 271—300, v 24, n 3, 1997. P.H.S. Torr, A. Zisserman. Robust Parameterization and Computation of the Trifocal Tensor. Image and Vision Computing, pages 591—607, v 15, 1997. P.H.S. Torr, A. Zisserman. Performance Characterisation of Fundamental Matrix Estimation Under Image Degradation. In Machine Vision and Applications, pages 321—333, v 9, 1997. P.H.S. Torr and D.W. Murray. Statistical detection of nonrigid motion. In Image and Vision Computing, pages 180—187, v 11, May 1993.
Edited Books & Conferences Organized David A. Forsyth, Philip H. S. Torr, Andrew Zisserman (Eds.): Computer Vision - ECCV 2008, 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part I, II, III, IV. Lecture Notes in Computer Science 5302 Springer 2008, ISBN 978-3-540-88681-5, ISBN 978-3-540-88685-3, ISBN 978-3-540-88689-1, ISBN 978-3-540-88692-1 R. Horaud, C Schnörr, P.H.S. Torr, J. Tsostsos. International Workshop on the Representation and Use of Prior Knowledge in Vision, Graz, 2006. W.F. Clocksin, A.W. Fitzgibbon, P.H.S. Torr. British Machine Vision Conference. ISBN 1-901725-29-4. Oxford, 2005. J. Mollon, FRS, P.H.S. Torr Rank Mini Symposium on Machine Understanding of People and their Responses; 30th Jan-3rd Feb 2005 F. Dellaert, P.H.S. Torr, S. B. Kang and R. Cipolla. First International Workshop on use of Higher Level Knowledge in Vision. ISBN 0-7695-2049-9. Nice, France, 2003.
Keynote, Plenary and Invited Talks P.H.S. Torr. Invited Speaker, Graph Cuts for Scene Understanding, 25th European Conference on Operational Research, Vilnius, Boolean and Pseudo-Boolean Optimization Stream, July, 2012. P.H.S. Torr. Keynote, Towards global energy models for scene understanding, International Conference on Digital Image Computing: Techniques and Applications (DICTA), Sydney, Dec 2010. P.H.S. Torr. Invited Speaker, Graph Cut Based Inference with Co-occurrence Statistics, The 27th Pattern Recognition and Computer Vision Colloquium, Prague, Oct 2010 P.H.S. Torr. Keynote, Towards Global Energy Models for Scene Understanding, 2010 Robotics: Science and Systems Conference, Zaragoza, June, 2010. P.H.S. Torr. Invited Speaker, Associative Hierarchical Networks for Scene Understanding, combining recognition and 3D structure recovery. ECCV Area Chair Colloquium, Paris, June 2010. P.H.S. Torr. Invited Speaker, Urban Scene Understanding from Video, International Workshop on Video 2009, Barcelona, May 2009. P.H.S. Torr. Keynote, 5th European Conference on Visual Media Production, London, Nov, 2008. P.H.S. Torr. Keynote, International Machine Vision and Image Processing Conference, Ireland, Sept, 2008. P.H.S. Torr. Invited Speaker, International Workshop on Computer Vision, Venice, May 2008. P.H.S. Torr. Invited Speaker, Convex Relaxations of MRF's, Workshop on Graph Cuts and Related Discrete or Continuous Optimization Problems, Institute for Pure & Applied Mathematics, University of California, Los Angeles, Feb 2008. P.H.S. Torr. Invited Speaker, School of Systems Engineering, Reading University, Nov 2007 P.H.S. Torr. Keynote, Weak 3D Prior Models for Recognition and Structure Recovery, IEEE workshop on 3D Representation for Recognition 3dRR-07, Oct 2007. P.H.S. Torr. Keynote, Interactive Methods, how Computer Vision can Power Assist Computer Graphics, Vision, Video and Graphics workshop, Sept 2007. P.H.S. Torr. Invited Speaker, Combinatorial Methods and Moving Images, The Rank Prize Funds mini-symposium on Interacting with Still and Moving Images: From Signals to Semantics, Lake District, July, 2007. (my student Pawan Kumar took best paper at this meeting) P.H.S. Torr. Keynote, Dynamic Markov Random Fields, Visual Information Engineering 2007: Bridging the gap between theory and applications, Royal Statistical Society, London, July, 2007. P.H.S. Torr. Invited Speaker, Computer Vision for Films, games and other media, One day symposium-the digital image, Wolfson College, Oxford, March, 2007. P.H.S. Torr. Public Lecture, Machines that See!, Oxford, Feb, 2007. P.H.S. Torr. Keynote, Combinatorial Optimization and Computer Vision, Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), Madurai, India, Dec, 2006. P.H.S. Torr. Invited Speaker, Solving Markov Random Fields using Dynamic Graph Cuts & Second Order Cone Programming Relaxations, BIRS Workshop on Mathematical Methods in Computer Vision, Banff International Research Station (BIRS) Alberta, Canada, Oct, 2006. P.H.S. Torr. Invited Speaker, Simultaneous Segmentation and 3D Pose Estimation of Humans, International Workshop on Current Trends in Computer Vision, Lhasa Tibet, Aug, 2006. P.H.S. Torr. Invited Speaker, OBJ CUT & Pose Cut, International Workshop on Current Trends in Computer Vision, Lhasa Tibet, Aug, 2006. P.H.S. Torr. Invited Speaker, MLESAC-improving the RANSAC cost function, 25 Years of RANSAC, Workshop in conjunction with CVPR 2006, New York, June, 2006. P.H.S. Torr. Invited Speaker, Detection + Segmentation = Tracking?, Workshop on Learning, Representation and Context for Human Sensing in Video in conjunction with CVPR 2006,, New York, June, 2006. P.H.S. Torr. Class-Specific Segmentation Using Layered Pictorial Structures, Invited Talk for PRCVC, Pattern Recognition and Computer Vision Colloquium, Czech Technical University, 2005. P.H.S. Torr. Bayesian Methods in Computer Vision and Graphics, Keynote Talk for PRASA, 15th Annual Symposium of the Pattern Recognition Association of South Africa, Cape Town, Dec, 2004. P.H.S. Torr. Bayesian Methods in Graphics, Keynote Talk for GraphiCon 13th Int. Conf. of Computer Graphics and Vision, Moscow State University 2003. P.H.S. Torr. A Bayesian analysis for fitting manifolds of varying dimensions, Invited Talk for PRCVC, Pattern Recognition and Computer Vision Colloquium, Czech Technical University, 2002. P.H.S. Torr. Invited
Speaker, Wide Baseline Matching, Invited Talk for Rank Prize Workshop on model selection, Wordsworth Hotel, P.H.S. Torr. Invited Speaker, Geometric Motion Segmentation and Model Selection, for Royal Society Meeting on Geometry in Computer Vision, 1998.
Invited Courses and Tutorials P.H.S Torr, Random Fields for Scene Understanding, Asian Conference on Computer Vision (ACCV), 2012. P.H.S. Torr, Random Fields for Scene Understanding, Vision and Sport Summer School (Prague), 2012. M.P. Kumar, P. Kohli; advisors A. Zisserman and P.H.S. Torr. MAP Estimation in Computer Vision, invited tutorial at European Conference on Computer Vision, ECCV, 2008. P.H.S. Torr. Markov Random Fields for Vision and Graphics, invited tutorial at British Machine Vision Conference 2008. Richard Hartley, Philip H. S. Torr, Fredrik Kahl, Lieven Vandenberghe, and Henrik Madsen, Discrete Optimization in Computer Vision, tutorial at Copenhagen, Mar 2008. Nikos Komodakis, Philip Torr, Vladimir Kolmogorov, Yuri Boykov. Discrete Optimization in Computer Vision, invited tutorial at International Conference on Computer Vision, ICCV, Oct 2007. P.H.S. Torr. Graph Cuts and their Use in Computer Vision, invited tutorial at International Computer Vision Summer School 2007, Detection, Recognition and Segmentation in Context, July 2007. P.H.S. Torr. Markov Random Fields for Computer Vision and Graphics, invited tutorial at Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI, 2005. Y. Boykov, P.H.S. Torr and R. Zabih. Discrete Optimization Methods, invited tutorial at Eighth European Conference on Computer Vision, ECCV, 2004. D. Huttenlocher and P.H.S. Torr. Efficient Algorithms for Matching. Short Course, invited tutorial at Ninth International Conference on Computer Vision, ICCV, 2003.
Refereed Conference Z. Zhang, N. Crook, and P.H.S. Torr. Robust-NBNN: A Locally Nonlinear Classifier via Nearest Neighbours, In the Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2012. (poster). V. Vineet, J. Warrell, and P.H.S. Torr, A Tiered Move-making Algorithm for General Pairwise MRF’s, In the Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2012. (poster). S. Hare, A. Saffari, and P.H.S. Torr. Efficient Online Structured Output Learning for Keypoint-Based Object Tracking, In the Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2012. (poster). L. Ladick´y and P.H.S. Torr. Locally Linear Support Vector
Machines, In Proceedings
International Conference of Machine Learning
(ICML), 2011. (oral). S. Hare, A. Saffari, and P.H.S. Torr. Struck: Structured Output Tracking
with Kernels, In the Proceedings of the Twelfth European
Conference on Computer Vision (ICCV),
2011. (poster). J. Warrell and P.H.S. Torr. Locally Multiple-Instance
Learning with Structured Bag Models, In Proceedings Energy Minimization Methods in
Computer Vision and Pattern Recognition (EMMCVPR), 2011. (oral). V. Vineet, J. Warrell, L. Ladick´y, and P.H.S. Torr, Human Instance Segmentation from Video using Detector-based Conditional Random Fields, In Proceedings British Machine Vision Conference, 2011. (poster). A. Mittal, A. Zisserman, and P.H.S. Torr, Hand detection using multiple
proposals, In Proceedings
British Machine Vision Conference, 2011.
(best poster award). Z. Zhang, L. Ladicky, P.H.S. Torr, and A. Saffari, Learning Anchor Planes for Classification, In NIPS, Neural Information Processing Conference, 2011. (poster). S. Ramalingham, S. Bouaziz, P. Sturm, and P.H.S. Torr, The Light-Path Less Traveled, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2011. (poster). Z. Zhang, J. Warrell and Philip H.S. Torr, Proposal Generation for Object Detection using Cascaded Ranking SVMs’, Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2011. (poster). L. Ladick´y, P. Sturgess, C. Russell, S. Sengupta, Y. Bastanlar, W. Clocksin and P.H.S. Torr. Joint Optimisation for Object Class Segmentation and Dense Stereo Reconstruction, In Proceedings British Machine Vision Conference, 2010. (oral) BMVA Best Science Paper Prize. J. Warrell, S. Prince, and P.H.S. Torr. StyP-Boost: A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers, In Proceedings British Machine Vision Conference, 2010. (oral) L. Ladick´y, P. Sturgess, K. Alahari, C. Russell, and P.H.S. Torr. What, Where & How Many? Combining Object Detectors and CRFs', In the Proceedings of the Eleventh European Conference on Computer Vision, 2010. (oral) L. Ladick´y, C. Russell, P. Kohli and P.H.S. Torr. Graph Cut based Inference with Co-occurrence Statistics, In the Proceedings of the Eleventh European Conference on Computer Vision, 2010. (oral). ECCV Best Science Paper Prize. C. Russell, L. Ladick´y, P. Kohli and P.H.S. Torr. Exact and Approximate Inference in Associative Hierarchical Random Fields using Graph-Cuts, In The 26th Conference on Uncertainty in Artificial Intelligence, 2010. (poster). Karteek Alahari, Chris Russell, Philip H.S. Torr, Efficient Piecewise Learning for Conditional Random Fields, Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2010. (poster). Fred Nicholls, Philip H.S. Torr, Discrete minimum ratio curves and surfaces, Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2010. (poster). L. Ladick´y, C. Russell, P. Kohli, and P.H.S. Torr, Associative Hierarchical CRFs for Object Class Image Segmentation, In Proceedings IEEE Twelfth International Conference on Computer Vision, 2009. (poster). P. Kumar, P.H.S. Torr, and A. Zisserman, Efficient Discriminative Learning of Parts-based Models, In Proceedings IEEE Twelfth International Conference on Computer Vision, 2009. (poster). P. Sturgess, K. Alahari, L. Ladick´y, and P. Torr, Combining Appearance and Structure from Motion Features for Road Scene Understanding, In Proceedings British Machine Vision Conference, 2009. (oral). P. Kohli, A. Shekhovtsov, V. Kolmogorov, C. Rother, and P.H.S. Torr, On Partial Optimality in Multi-label MRFs', In Proceedings International Conference of Machine Learning (ICML), 2008. (oral). Tech Report P. Kumar and P.H.S. Torr, Efficiently Solving Convex Relaxations for MAP Estimation, In Proceedings International Conference of Machine Learning (ICML), 2008. (oral). P. Kumar and P.H.S. Torr, Improved Moves for Truncated Convex Models, NIPS 22, Neural Information Processing Conference, 2008. (spotlight oral). P. Kohli, L’ubor Ladick´y, and P.H.S. Torr, Robust Higher Order Potentials for Enforcing Label Consistency, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2008. (oral). O. Woodford, P.H.S. Torr, I. Reid, and A.W. Fitzgibbon, Global Stereo Reconstruction under Second Order Smoothness Priors, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2008 (oral) Best Paper at Conference. G. Rogez, J. Rihan, S. Ramalingham, C. Orrite, and P.H.S. Torr, Randomized Trees for Human Pose Detection, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2008 (poster). K. Alahari, P. Kohli, and P.H.S. Torr, Reduce, Reuse & Recycle: Efficiently Solving Multi-Label MRFs', In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2008 (poster). A. Shahrokni, C. Mei, P. Torr and I. Reid, From Visual Query to Visual Portrayal, In Proceedings British Machine Vision Conference, 2008 (oral). C. H. Ek, J. Rihan, P. H. S. Torr, G. Rogez and N. D. Lawrence, Ambiguity Modeling in Latent Spaces, In Machine Learning for Multimodal Interaction, 2008. S. Ramalingham, P. Kohli, K. Alahari, and P.H.S. Torr, Exact Inference in Multi-label CRFs with Higher Order Cliques, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2008 (poster). Y. Pratheepan, P. H. S Torr, J V Condell, and G. Prasad, Body Language Based Individual Identification in Video Using Gait and Actions, In Proceedings International Machine Vision and Image Processing Conference, 2008. P. Kumar, V. Kolmorgorov, and P.H.S. Torr, An Analysis of Convex Relaxations for MAP Estimation, In NIPS 21, Neural Information Processing Conference, 2007 (oral & Honourable Mention at Conference). A. Hengel, A. Dick, T. Thormahlen, B. Ward and P.H.S. Torr, VideoTrace: Rapid interactive scene modelling from video, In ACM SIGGRAPH, The 34th International Conference on Computer Graphics and Interactive Techniques, 2007 (oral). P. Kumar, P.H.S. Torr, and A. Zisserman, An Invariant Large Margin Nearest Neighbour Classifier, In IEEE Eleventh International Conference on Computer Vision, 2007 (poster). C. Russell, C. Restif, D. Metaxas, and P.H.S. Torr, Using the Pn Potts model with learning methods to segment live cell images, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis, 2007. (oral). P. Kohli, P. Kumar, and P.H.S. Torr, P3 & Beyond: Solving Energies with Higher Order Cliques, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2007 (oral). O. Woodford, I. Reid, P.H.S. Torr, and A.W. Fitzgibbon, On New View Synthesis Using Multiview Stereo, In Proceedings British Machine Vision Conference, 2007 (oral). C. H. Ek, N. Laurence, and P.H.S. Torr, Gaussian Process Latent Variable Models for Human Pose Estimation, In 4th Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms, 2007. (poster) Y. Sun, P. Kohli, M. Bray, and P.H.S. Torr, Using Strong Shape Priors for Stereo, In ICVGIP, 2006. IAPR Best paper award at conference. (oral) J. Rihan, P. Kohli, and P.H.S. Torr, ObjCut for Face Detection, In ICVGIP, 2006. (oral) M. Prasad, A. Zisserman, A. Fitzgibbon, P. Kumar, P. H. S. Torr, Learning Class-specific Edges for Object Detection and Segmentation, in ICVGIP, 2006. (oral) Y. Sun, M. Bray, A. Thayananthan, B. Yuanand, and P.H.S. Torr, Regression-Based Human Motion Capture From Voxel Data, In Proceedings British Machine Vision Conference, 2006. (poster) O. Woodford, I. Reid, P.H.S. Torr, and A.W. Fitzgibbon, Fields of Experts for Image-based Rendering, In Proceedings British Machine Vision Conference, 2006. (poster) A. Hengel, A. Dick, T. Thormahlen, B. Ward and P.H.S. Torr, Building Models of Regular Scenes from Structure and Motion, In Proceedings British Machine Vision Conference, 2006. (poster) A. Hengel, A. Dick, T. Thormahlen, B. Ward and P.H.S. Torr, Hierarchical model fitting to 2D and 3D data, In Proceedings of the Third International Conference on Computer Graphics, Imaging and Visualisation, IEEE Computer Society Press, Sydney, Australia, July, 2006. A. Hengel, A. Dick, T. Thormahlen, B. Ward and P.H.S. Torr, Rapid Interactive Modelling from Video with Graph Cuts, In Proceedings Eurographics, 2006. A. Hengel, A. Dick, T. Thormahlen, B. Ward and P.H.S. Torr, Fitting multiple models to multiple images with minimal user interaction, In International Workshop on the Representation and Use of Prior Knowledge in Vision (WRUPKV) held in association with ECCV’06, May 2006, Graz, Austria P. Kumar, P.H.S. Torr and A. Zisserman, Solving Markov Random Fields Using Second Order Cone Programming, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2006 (poster). P. Kohli and P.H.S. Torr. Measuring Uncertainty in Graph Cut Solutions - Efficiently Computing Min-marginal Energies using Dynamic Graph Cuts, In the Proceedings of the Ninth European Conference on Computer Vision, 2006. (oral). P. Kohli, P.H.S. Torr and M. Bray. PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans using Dynamic Graph-Cuts, In the Proceedings of the Ninth European Conference on Computer Vision, 2006. (oral). P. Kumar, P.H.S. Torr. Fast Memory-Efficient Generalized Belief Propagation, In the Proceedings of the Ninth European Conference on Computer Vision, 2006 .(poster). A. Thayananthan, R. Navaratnam, B. Stenger, P.H.S. Torr, and R. Cipolla, Multivariate Relevance Vector Machines for Tracking, In the Proceedings of the Ninth European Conference on Computer Vision, 2006. (poster). P. Kohli and P.H.S. Torr. Efficiently Solving Dynamic Markov Random Fields Using Graph Cuts. In IEEE Tenth International Conference on Computer Vision, 2005. (oral). (patent pending). M. Pawan. Kumar, P.H.S. Torr, and A. Zisserman. Learning Layered Motion Segmentations of Video. In IEEE Tenth International Conference on Computer Vision, 2005. (oral). R. Navaratnam, A. Thayananthan, P.H.S. Torr, and R. Cipolla. Hierarchical Part-Based Human Body Pose Estimation. In Proceedings British Machine Vision Conference, 2005. (oral). G. Vogiatzis, P.H.S. Torr, and R. Cipolla. Multi-view stereo via Volumetric Graph-cuts. In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, pages 391-398, 2005. (oral). M. Pawan. Kumar, P.H.S. Torr, and A. Zisserman. OBJCUT. Accepted to IEEE Conference of Computer Vision and Pattern Recognition, pages 18-25, 2005. (oral). M. Pawan. Kumar, P.H.S. Torr, and A. Zisserman. Learning Layered Pictorial Structures from Video. In Proceedings of The Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), pages 158-163, 2004. IAPR Best paper award at conference. (oral). G. Vogiatzis, P.H.S. Torr, S.M. Seitz, and R. Cipolla. Reconstructing Relief Surfaces. In Proceedings British Machine Vision Conference, pages 117-126, 2004. (oral). A. Thayananthan, R. Navaratnam, P.H.S. Torr, and R. Cipolla. Likelihood Models for Template Matching. In Proceedings British Machine Vision Conference, pages 949-958, 2004. (oral). M. Pawan. Kumar, P.H.S. Torr, and A. Zisserman. Detecting Articulated Objects Using Pictorial Structures. In Proceedings British Machine Vision Conference, pages 789-798, 2004. (poster). A. Blake, C. Rother, M. Brown, P. Perez, P.H.S. Torr. Interactive Image Segmentation Using an Adaptive GMMRF Model, In The Proceedings Eighth European Conference on Computer Vision, pages 428—442, 2004. (poster). B. Stenger, A. Thayananthan, P.H.S. Torr, and R. Cipolla. Hand Pose Estimation Using Hierarchical Detection. In Intl. Workshop on Human-Computer Interaction, pages 105-116, 2004. (oral). A. Thayananthan, B. Stenger, P.H.S. Torr, and R.
Cipolla. Shape Context and Chamfer
Matching in Cluttered Scenes. In
Proceedings IEEE Conference
of Computer Vision and Pattern Recognition, pages 127-133, 2003. (oral).
Slides P.H.S. Torr. Solving
Markov Random Fields using Semi Definite Programming, In Ninth
International Workshop on Artificial Intelligence and Statistics, 2003. (oral). B. Stenger, A. Thayananthan, P.H.S. Torr, and R.
Cipolla. Bayesian Tracking using
Tree-Based Density Estimation, In IEEE Ninth International Conference on
Computer Vision, pages 1063-1072, 2003. J. Shotton, A Criminisi, A. Blake, and P.H.S. Torr. Gaze Manipulation for One-to-one
Teleconferencing, In IEEE Ninth International Conference on
Computer Vision, pages 191-200, 2003. P.H.S. Torr and A. Fitzgibbon. Invariant Fitting of Two View Geometry or “In
Defiance of the eight point algorithm”, In Proceedings British
Machine Vision Conference, pages 83-92, 2003. (oral). A. Thayananthan, B. Stenger, P.H.S. Torr, and R.
Cipolla. Tracking Articulated Hand
Motion using a Kinematic Prior, In
Proceedings British Machine
Vision Conference, pages 589-598, 2003.
(oral). G. Vogiatzis, P.H.S. Torr, and R. Cipolla. Bayesian Stochastic Mesh Optimization for 3D Reconstruction, In Proceedings British Machine Vision Conference, pages 711-718, 2003. Slides (oral). R. Cipolla, B. Stenger, A. Thayananthan, and P.H.S.
Torr. Hand Tracking Using A Quadric
Surface Model. R. Cipolla Invited
Key Note Speech, for The
Mathematics of Surfaces X, P.H.S. Torr and A. Criminisi. Dense Stereo using Pivoted Dynamic Programming, In Proceedings British Machine Vision Conference, pages 414-423, 2002. This paper was nominated for best paper at conference. (oral). D. Myatt, P.H.S. Torr, S. Nasuto, and R. Craddock. NAPSAC: High Noise, High Dimensional Robust Estimation, In Proceedings British Machine Vision Conference, pages 458-467, 2002. (oral). W. Clocksin, K. Chivers, and P.H.S. Torr. Inspection of Surface Strain in Materials Using Dense Displacement. In 4th International Conference on New Challenges in Mesomechanics,vol 2, pages 467-474, 2002. W. Clocksin, F. Quinta, P. Withers, and P.H.S. Torr. Image processing issues in digital strain mapping. Proceedings
of the SPIE Vol.4790, 384-395, 2002. A. R. Dick, P.H.S. Torr, and R. Cipolla. A Bayesian Estimation of Building Shape using
MCMC. In The Seventh European
Conference on Computer Vision, pages 852-866, 2002. (oral). A. R. Dick, P.H.S. Torr, and R. Cipolla. Combining Single View Recognition and Multiple View for Stereo for Architectural Scenes. In IEEE Eighth International Conference on Computer Vision, pages 268—274, 2001. (poster). S. Romdhani, P.H.S. Torr, B. Schölkopf, and A Blake. Fast Face Detection, Using a Sequential Reduced Support Vector Evaluation. In IEEE Eighth International Conference on Computer Vision, pages 695—700, 2001. (poster). P.H.S. Torr and C. Davidson. IMPSAC: A synthesis of importance sampling and random sample consensus. In The Sixth European Conference on Computer Vision, pages 819—833, 2000. This paper was nominated for best paper at conference. (oral). F. Schaffalitzky, A. Zisserman, R. Hartley and P.H.S. Torr. A Six Point Solution for Structure and Motion. In The Sixth European Conference on Computer Vision, pages 632—648, 2000. (poster). P.H.S. Torr, A. Dick, and R. Cipolla. Layer Extraction with a Bayesian Model of Shapes. In The Sixth European Conference on Computer Vision, pages 273—289, 2000. (poster). A. R. Dick, P.H.S. Torr, and R. Cipolla. Automated 3D Modelling of Architecture. In Proceedings British Machine Vision Conference, pages 273—289, 2000. (oral). P.H.S. Torr, R. Szeliski, P. Anandan. An integrated Bayesian Approach to Layer Extraction from Image Sequence. In IEEE Seventh International Conference on Computer Vision, pages 983—991, v 2, 1999. (oral). P.H.S. Torr and A. Zisserman. Feature Based Methods for Structure and
Motion Estimation. In International
Workshop on Vision Algorithms, pages 278-295, 1999. (oral-panel discussion). P.H.S. Torr, A. Fitzgibbon and A. Zisserman. Maintaining Multiple Motion Model
Hypotheses through Many Views to Recover Matching and Structure. In IEEE Sixth International Conference on
Computer Vision, pages 485—492, 1998. This work was awarded the IEEE Marr Prize at the ICCV conference. (oral). P.H.S. Torr and A. Zisserman. Concerning Bayesian Motion Segmentation, Model Averaging, Matching and the Trifocal Tensor. In The Fifth European Conference on Computer Vision, pages 511—528, v 1, 1998. (oral). P.H.S. Torr. Bayesian Model Estimation and Selection for Epipolar Geometry and Generic Manifold Fitting. In Workshop on Shape, Contour and Grouping, pages 69—113, 1998. (oral). R. Szeliski, P.H.S. Torr. Geometrically constrained structure from motion: Points on planes. In 3D Structure from Multiple Images of Large-Scale Environments, European Workshop SMILE'98, pages 171—186, 1998. (oral). P.H.S. Torr and A. Zisserman. Robust Computation and Parameterization of Multiple View Relation. In IEEE Sixth International Conference on Computer Vision, pages 727—732, 1998. (poster). P.H.S. Torr, An Assessment of Information Criteria for Motion Model Selection. In IEEE Conference on Computer Vision and Pattern Recognition, pages 47—53, 1997. (poster). P.A. Beardsley, P.H.S. Torr and A. Zisserman. 3D Model Acquisition from Extended Image Sequences. In The Fourth European Conference on Computer Vision, pages 683—695, 1996. (oral). P.H.S. Torr, A. Zisserman. Robust Parameterization and Computation of the Trifocal Tensor. In Proceedings British Machine Vision Conference, pages 655—664, 1996. This paper was nominated for best paper at conference. (oral). P.H.S. Torr, A. Zisserman and S. Maybank. Robust detection of Degenerate Configuration whilst estimating the Fundamental Matrix. In The Fifth International Conference on Computer Vision, pages 1037—1044, 1995. (oral). P.H.S. Torr, A. Zisserman, and D.W. Murray. Motion Clustering using the Trilinear Constraint. In Europe-China workshop on Geometric Modelling and Invariants for Computer Vision, pages 118—125, 1995. (oral). P.H.S. Torr, P.A. Beardsley and D.W. Murray. Robust Vision. In Proceedings British Machine Vision Conference, pages 145-155, 1994. (oral). P.H.S. Torr and D.W. Murray. Stochastic motion clustering. In The Fourth European Conference on Computer Vision pages 328—338, 1994. (oral). P.H.S. Torr and D.W. Murray. Outlier detection and motion segmentation. In SPIE sensor fusion conference VI, pages 432—443, Sept. 1993. (oral). P.H.S. Torr and D.W. Murray. Statistical detection of
nonrigid motion. In Proc. British
Machine Vision Conference, pages 79—88. Springer-Verlag
1992. P.H.S. Torr, T. Wong, D.W. Murray and A. Zisserman. Cooperating motion processes. In Proceedings of the British Machine Vision Conference, pages 126—129, 1991. (oral).
Book Chapters P. Kumar, V. Kolmogorov, and P.H.S. Torr, Analyzing Convex Relaxations for MAP estimation, In Markov Random Fields for Vision and Image Processing, Andrew Blake, Pushmeet Kohli, Carsten Rother (eds.), MIT press, 2011 P. Kohli, L. Ladicky, and P.H.S. Torr, Enforcing Label Consistency Using Higher-Order Potentials, In Markov Random Fields for Vision and Image Processing, Andrew Blake, Pushmeet Kohli, Carsten Rother (eds.), MIT press, 2011 P. Kumar, P.H.S. Torr and A. Zisserman. An Object Category Specific MRF for Segmentation, In Toward Category-Level Object Recognition, J. Ponce, M. Hebert, C. Schmid, and A. Zisserman (eds.), Springer-Verlag LNCS, pages 531-561, 2006. R. Cipolla, B. Stenger, A. Thayananthan and P. H. S. Torr. Template-based hand detection and tracking. In M. Tistarelli, J. Bigün and E. Grosso, editors, Advanced Studies in Biometrics, 114-125, Springer, 2005. P.H.S. Torr and A. Criminisi. Dense Stereo using Pivoted
Dynamic Programming. Vision. Technical newsletter of Society of
Manufacturing Engineers (SME), P.H.S. Torr. Model Selection for Structure and Motion Recovery from Multiple Images. In Data Segmentation and Model Selection for Computer Vision, Springer-Verlag ISBN 0-387-988815-7, pages 143—182, 1999. J.M. Bishop and P.H.S. Torr. The stochastic search network. In Neural Networks for Images, Speech and Natural Language, pages 370—388, 1992.
PhD Thesis P.H.S. Torr. Thesis: Outlier
Detection and Motion Segmentation,
PhD Theses Supervised C. Russell, PhD Thesis: Higher-Order Inference for Vision Problems, Department of Computing, Oxford Brookes University, July, 2011. L. Ladick´y, PhD Thesis: Global Structured Models towards Scene Understanding, Department of Computing, Oxford Brookes University, April, 2011 Jon Rihan, PhD Thesis: Computer Vision Based Interfaces for Computer Games, Department of Computing, Oxford Brookes University, Jan, 2011. Tom Shannon, PhD Thesis: Dynamic Surface Topography and its application to the evaluation of adolescent idiopathic scoliosis, Department of Computing, Oxford Brookes University, Oct, 2010. Karteek Alahari, PhD Thesis: Efficient inference and learning for computer vision labelling problems, Department of Computing, Oxford Brookes University, Aug, 2010. Co Supervised with Dr N. Lawrence, Manchester University Carl Ek, PhD Thesis: Shared Gaussian Process Latent Variable Models, Department of Computing, Oxford Brookes University 2009. Co Supervised with Dr A Fitzgibbon, Microsoft Research and Dr I. Reid Oxford University. Oliver Woodford, DPhil Thesis: Priors for New View Synthesis, Department of Engineering, Oxford University, May 2009. Pushmeet Kohli PhD Thesis: Minimizing Dynamic and Higher Order Energy Functions using Graph Cuts, Department of Computing, Oxford Brookes University Nov. 2007. Winner of Sullivan Prize, runner up for the CPHC/British Computer Society Distinguished Dissertation competition. Co Supervised with Professor Zisserman, Oxford University. Pawan Kumar Mudigonda PhD Thesis: Combinatorial and Convex Optimization for Probabilistic Models in Computer Vision, Department of Computing, Oxford Brookes University, Feb 2008. awarded Sullivan Doctoral thesis prize 2009. Co Supervised with Professor Clocksin, Oxford Brookes University. Chistophe Restif PhD Thesis: Segmentation and Evaluation of Fluorescence Microscopy Images, Department of Computing, Oxford Brookes University Oct 2006. Co Supervised with Professor Cipolla, Cambridge University. George Vogiatzis PhD Thesis: View Estimation of Shape, Reflectance and Illumination, Department of Engineering, University of Cambridge, April 2006. A. Thayananthan. PhD Thesis: Template-based Pose Estimation and Tracking of 3D Hand Motion, Department of Engineering, University of Cambridge, Oct, 2005. B. Stenger. PhD Thesis: Model-Based Hand Tracking Using A Hierarchical Bayesian Filter, Department of Engineering, University of Cambridge, March 2004. Winner of Sullivan Prize. A. R. Dick. PhD Thesis: Modelling and Interpretation of
Architecture from Several Images, Department of Engineering, Technical Reports S. Ramalingham, C. Russell, L. Ladicky, and P.H.S. Torr, Efficient Minimization of Higher Order Submodular Functions using Monotonic Boolean Functions, ArXiv.org, Sept, 2011. Prizes L. Ladick´y, C. Russell, P. Kohli and P.H.S. Torr. Graph Cut based Inference with Co-occurrence Statistics, In the Proceedings of the Eleventh European Conference on Computer Vision ,2010. (oral). ECCV Best Science Paper Prize. L. Ladick´y, P. Sturgess, C. Russell, S. Sengupta, Y. Bastanlar, W. Clocksin and P.H.S. Torr. Joint Optimisation for Object Class Segmentation and Dense Stereo Reconstruction, In Proceedings British Machine Vision Conference, 2010. (oral) BMVA Best Science Paper Prize. Pawan Kumar Mudigonda PhD Thesis: Combinatorial and Convex Optimization for Probabilistic Models in Computer Vision, awarded Sullivan Doctoral thesis prize 2009. O. Woodford, P.H.S. Torr, I. Reid, and A.W. Fitzgibbon, Global Stereo Reconstruction under Second Order Smoothness Priors, In Proceedings IEEE Conference of Computer Vision and Pattern Recognition, 2008 (oral) Best Paper at Conference. P. Kumar, V. Kolmorgorov, and P.H.S. Torr, An Analysis of Convex Relaxations for MAP Estimation, In NIPS 21, Neural Information Processing Conference, 2007 (oral & Honourable Mention at Conference). P. Kohli, Pushmeet Kohli PhD Thesis: Minimizing Dynamic and Higher Order Energy Functions using Graph Cuts, Sullivan Doctoral thesis prize 2007, runner up CPHC/British Computer Society Distinguished Dissertation competition. P. Kumar, P.H.S. Torr, and A. Zisserman, An Invariant Large Margin Nearest Neighbour Classifier, Opto-Electronics Committee prize for best contributed paper at the Rank Prize Funds Mini Symposium on the still and moving image. Y. Sun, P. Kohli, M. Bray, and P.H.S. Torr, Using Strong Shape Priors for Stereo, In ICVGIP, 2006. IAPR Best paper award. (oral) M. Pawan. Kumar, P.H.S. Torr, and A. Zisserman. Learning Layered Pictorial Structures from Video. In Proceedings of The Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), pages 158-163, 2004. IAPR Best paper award. (oral). P.H.S. Torr, A. Fitzgibbon and A. Zisserman. Maintaining Multiple Motion Model Hypotheses through Many Views to Recover Matching and Structure. In IEEE Sixth International Conference on Computer Vision, pages 485—492, 1998. IEEE Marr Prize.
Theses Examined F. Viola, Ph.D. Thesis, Resolution-Independent Image Models, Department of Engineering, University of Cambridge, Feb, 2012. V. Gulshan, D.Phil. Thesis: From Interactive to Semantic Image Segmentation, Department of Engineering, University of Oxford, 2012. Timo Pylvänäinen, Ph.D. Advances in Augmented Reality Technologies. Department of Science and Engineering, Tampere University of Technology, 2011. C. Wang, Ph.D. Thesis, Distributed and Higher-Order Graphical Models towards Segmentation, Tracking and 3D Model Inference, École centrale Paris, MAS laboratory, 2011. J. Shotton, Ph.D. Thesis, Contour and Texture for Visual Recognition of Object Categories, Department of Engineering, University of Cambridge, 2007. A. Agarwal, Ph.D. Thesis: Machine Learning for Image Based Motion Capture, Institut National Polytechnique de Grenoble, 2006. C. Leung, Ph.D. Thesis: Efficient Methods for 3D Reconstruction from Multiple Images, School of Information Technology and Electrical Engineering, University of Queensland, Australia, Jan 2006. O. Chum, Ph.D. Thesis: Two-View Geometry Estimation by Random Sample and Consensus, Faculty of Electrical Engineering, Czech Technical University, Prague, Sept 2005. B. Tordoff, D.Phil. Thesis: Active Control of Zoom for Computer Vision. Department of Engineering, University of Oxford, Michaelmas, 2003. P. Smith, Ph.D. Thesis: Edge-based
Motion Segmentation. Department of Engineering, D. Lingrand, Thèse de Doctorat: Analyse adaptative du mouvement dans des séquences monoculaires non calibrées INRIA Grenoble, Juillet 1999.
Patents Awarded Method and system for generating fully-textured 3D - US
Patent 6999073, 2007
Efficient Labelling of Image Pixels Using Graphs Cuts, US patent, filed 20th June 2006, UK patent number GB2430826 2007. Virtual Camera Translation US Patent number 10/681,007, 2004. Cyclopean Virtual Imaging Via Generalized Probabilistic Smoothing, 2003. Pattern detection methods and systems and face detection methods and systems, US Patent, 7099504, 2006-08-09 Pattern detection methods and systems, and face detection methods and systems US Patent, 6804391, 2004-10-12. Feature correspondence between images using an image pyramid, US Patent 6741757, 2004-5-25. Automated layer extraction and pixel assignment from image sequences, US Patent 6668080, 2003-12-23. |