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Filters: Author is James Coughlan [Clear All Filters]
Manhattan world: Orientation and outlier detection by bayesian inference. Neural Computation, 15, 1063–1088.. (2003).
The Manhattan world assumption: Regularities in scene statistics which enable Bayesian inference. In NIPS (pp. 845–851).. (2000).
The g Factor: Relating Distributions on Features to Distributions on Images. In NIPS (pp. 1231–1238).. (2001).
A fast algorithm for finding crosswalks using figure-ground segmentation. 2Nd Workshop On Applications Of Computer Vision, In Conjunction With Eccv, 5.. (2006).
Computer vision-based terrain sensors for blind wheelchair users. In Computers Helping People with Special Needs (pp. 1294–1297). Springer Berlin Heidelberg.. (2006).
The crosswatch traffic intersection analyzer: a roadmap for the future. In Computers Helping People with Special Needs (pp. 25–28). Springer Berlin Heidelberg.. (2012).
Evaluating Author and User Experience for an Audio-Haptic System for Annotation of Physical Models. In 19th Int’l ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2017). ACM: Baltimore, MD.. (2017).
Efficient deformable template detection and localization without user initialization. Computer Vision And Image Understanding, 78, 303–319.. (2000).
Dynamic quantization for belief propagation in sparse spaces. Computer Vision And Image Understanding, 106, 47–58.. (2007).
Non-Visual Access to an Interactive 3D Map. In Joint International Conference on Digital Inclusion, Assistive Technology & Accessibility (ICCHP-AAATE '22).. (2022).
Efficient optimization of a deformable template using dynamic programming. In 2013 IEEE Conference on Computer Vision and Pattern Recognition (pp. 747–747). IEEE Computer Society.. (1998).