Publications

Crandall, W. F. (1981). Muscle units divided among retractor bulbi muscle slips and between the lateral rectus and retractor bulbi muscles in cat. Experimental Neurology, 71, 251–260.

Crandall, W. F., & Keller, E. L.. (1985). Visual and oculomotor signals in nucleus reticularis tegmenti pontis in alert monkey. Journal Of Neurophysiology, 54, 1326–1345.

Coughlan, J., & Manduchi, R.. (2009). Functional assessment of a camera phone-based wayfinding system operated by blind and visually impaired users. International Journal On Artificial Intelligence Tools, 18, 379–397.

Coughlan, J., & Shen, H.. (2010). An Embarrassingly Simple Speed-Up of Belief Propagation with Robust Potentials. Arxiv Preprint Arxiv:1010.0012.

Coughlan, J., & Ferreira, S. J.. (2002). Finding deformable shapes using loopy belief propagation. In Computer Vision—ECCV 2002 (pp. 453–468). Springer Berlin Heidelberg.

Coughlan, J., & Miele, J.. (2017). AR4VI: AR as an Accessibility Tool for People with Visual Impairments. In AR for Good, part of ISMAR 2017. Nantes, France: IEEE. (Original work published 2017)

Coughlan, J., & Manduchi, R.. (2007). Color targets: Fiducials to help visually impaired people find their way by camera phone. Eurasip Journal On Image And Video Processing, 2007.

Coughlan, J., & Yuille, A. L.. (1998). A phase space approach to minimax entropy learning and the minutemax approximations. In NIPS (pp. 761–767).

Coughlan, J., & Manduchi, R.. (2013). Camera-based access to visual information. In Assistive technology for blindness and low vision (pp. 219–246).

Coughlan, J. (1999). A Transparent Interpretation of the EM Algorithm.

Coughlan, J., Manduchi, R., & Shen, H.. (2006). Cell phone-based wayfinding for the visually impaired. In 1st International Workshop on Mobile Vision.

Coughlan, J., & Manduchi, R.. (2007). Functional assessment of a camera phone-based wayfinding system operated by blind users. Ieee Computer Society And The Biological And Artificial Intelligence Society.

Coughlan, J., & Yuille, A. L.. (2001). The g Factor: Relating Distributions on Features to Distributions on Images. In NIPS (pp. 1231–1238).

Coughlan, J., & Yuille, A. L.. (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.

Coughlan, J., & Shen, H.. (2012). The crosswatch traffic intersection analyzer: a roadmap for the future. In Computers Helping People with Special Needs (pp. 25–28). Springer Berlin Heidelberg.

Coughlan, J. (2009). Basic 3D Geometry for One and Two Cameras.

Coughlan, J., & Yuille, A. L.. (2003). Manhattan world: Orientation and outlier detection by bayesian inference. Neural Computation, 15, 1063–1088.

Coughlan, J., & Yuille, A. L.. (2000). The Manhattan world assumption: Regularities in scene statistics which enable Bayesian inference. In NIPS (pp. 845–851).

Coughlan, J., & Shen, H.. (2007). Terrain Analysis for Blind Wheelchair Users: Computer Vision Algorithms for Finding Curbs and other Negative Obstacles. In CVHI.

Coughlan, J., & Editor: Tyler, C. W.. (2011). Mechanisms for propagating surface information in 3-D reconstruction. In Computer Vision: From Surfaces to 3D Objects. Chapman and Hall/CRC Press.

Coughlan, J., & Shen, H.. (2006). A fast algorithm for finding crosswalks using figure-ground segmentation. 2Nd Workshop On Applications Of Computer Vision, In Conjunction With Eccv, 5.

Coughlan, J., Manduchi, R., & Shen, H.. (2006). Computer vision-based terrain sensors for blind wheelchair users. In Computers Helping People with Special Needs (pp. 1294–1297). Springer Berlin Heidelberg.

Coughlan, J. (2009). A Tutorial Introduction to Belief Propagation.

Coughlan, J., Yuille, A. L., English, C., & Snow, D.. (2000). Efficient deformable template detection and localization without user initialization. Computer Vision And Image Understanding, 78, 303–319.

Coughlan, J., & Shen, H.. (2007). Dynamic quantization for belief propagation in sparse spaces. Computer Vision And Image Understanding, 106, 47–58.