Publications
. (2003). Algorithms from statistical physics for generative models of images. Image And Vision Computing, 21, 29–36.
. (2003). A bayesian network framework for relational shape matching. In Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on (pp. 671–678). IEEE.
. (2003). The generic viewpoint assumption and planar bias. Ieee Transactions On Pattern Analysis And Machine Intelligence, 25, 775–778.
. (2003). The KGBR viewpoint-lighting ambiguity. Journal Of The Optical Society Of America (Josa) A, 20(1).
. (2003). A large deviation theory analysis of Bayesian tree search. Ima Volumes In Mathematics And Its Applications, 133, 1–18.
. (2003). Manhattan world: Orientation and outlier detection by bayesian inference. Neural Computation, 15, 1063–1088.
. (2003). A statistical approach to multi-scale edge detection. Image And Vision Computing, 21, 37–48.
. (2003). Statistical edge detection: Learning and evaluating edge cues. Pattern Analysis And Machine Intelligence, Ieee Transactions On, 25, 57–74.
. (2002). Bayesian A* tree search with expected O (N) node expansions: applications to road tracking. Neural Computation, 14, 1929–1958.
. (2002). Fundamental bounds on edge detection: learning and evaluating edge cues. Pattern Anal. Machine Intell.
. (2001). The g Factor: Relating Distributions on Features to Distributions on Images. In NIPS (pp. 1231–1238).
. (2001). The KGBR viewpoint-lighting ambiguity and its resolution by generic constraints. Computer Vision, 2001. Iccv 2001. Proceedings. Eighth Ieee International Conference On, 2, 376–382.
. (2001). Order Parameters for Detecting Target Curves in Images: When does high level knowledge help?. International Journal Of Computer Vision, 41, 9–33.
. (2000). An A∗ perspective on deterministic optimization for deformable templates. Pattern Recognition, 33, 603–616.
. (2000). Efficient deformable template detection and localization without user initialization. Computer Vision And Image Understanding, 78, 303–319.
. (2000). Fundamental limits of Bayesian inference: order parameters and phase transitions for road tracking. Pattern Analysis And Machine Intelligence, Ieee Transactions On, 22, 160–173.
. (2000). The generic viewpoint constraint resolves the generalized bas relief ambiguity. Proc. Of Conference On Information Scienes And Systems (Ciss 2000), 15–17.
. (2000). The Manhattan world assumption: Regularities in scene statistics which enable Bayesian inference. In NIPS (pp. 845–851).
. (2000). Order Parameters for Minimax Entropy Distributions: When does high level knowledge help?. In Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on (Vol. 1, pp. 558–565). IEEE.
. (2000). Unified framework for performance analysis of Bayesian inference. In AeroSense 2000 (pp. 333–346). International Society for Optics and Photonics.
. (1999). Bayesian A* tree search with expected O (N) convergence rates for road tracking. In Energy Minimization Methods in Computer Vision and Pattern Recognition (pp. 189–204). Springer Berlin Heidelberg.
. (1999). From Generic to Specific: An Information Theoretic Perspective on the Value of High-Level Information. Probabilistic Models Of The Brain, 135.
. (1999). Fundamental bounds on edge detection: An information theoretic evaluation of different edge cues. In Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on. (Vol. 1). IEEE.
. (1999). High-Level and Generic Models for Visual Search: When does high level knowledge help?. In Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on. (Vol. 2). IEEE.
. (1999). Manhattan world: Compass direction from a single image by bayesian inference. In Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on (Vol. 2, pp. 941–947). IEEE.