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David Mumford

Affiliations: 
Brown University, Providence, RI 
 Mathematics Harvard University, Cambridge, MA, United States 
Area:
Computer vision
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"David Mumford"
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Parents

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Oscar A. Zariski grad student 1961 Harvard
 (Existence of the Moduli Scheme for Curves of Any Genus)

Children

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Tai Sing Lee grad student Harvard
Artur Y. Fridman grad student 2000 Brown
Jinggang Huang grad student 2000 Brown
Conglin Lu grad student 2002 Brown
Yan Cao grad student 2003 Brown
Kathryn Leonard grad student 2004 Brown
Matt Feiszli grad student 2008 Brown
Sergey Kushnarev grad student 2010 Brown

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Publications

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Akin A, Mumford D. (2012) "Yu laid out the lands:" Georeferencing the Chinese Yujitu [Map of the Tracks of Yu] of 1136 Cartography and Geographic Information Science. 39: 154-169
Feiszli M, Mumford D. (2007) Shape representation via conformal mapping Proceedings of Spie - the International Society For Optical Engineering. 6498
Lee TS, Mumford D. (2003) Hierarchical Bayesian inference in the visual cortex. Journal of the Optical Society of America. a, Optics, Image Science, and Vision. 20: 1434-48
Lee AB, Pedersen KS, Mumford D. (2003) The nonlinear statistics of high-contrast patches in natural images International Journal of Computer Vision. 54: 83-103
Lee TS, Yang CF, Romero RD, et al. (2002) Neural activity in early visual cortex reflects behavioral experience and higher-order perceptual saliency. Nature Neuroscience. 5: 589-97
Lu C, Cao Y, Mumford D. (2002) Surface evolution under curvature flows Journal of Visual Communication and Image Representation. 13: 65-81
Mumford D, Gidas B. (2001) Stochastic models for generic images Quarterly of Applied Mathematics. 59: 85-111
Lee AB, Mumford D, Huang J. (2001) Occlusion models for natural images: A statistical study of a scale-invariant dead leaves model International Journal of Computer Vision. 41: 35-59
Lee TS, Mumford D, Romero R, et al. (1998) The role of the primary visual cortex in higher level vision. Vision Research. 38: 2429-54
Zhu SC, Wu Y, Mumford D. (1998) Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling International Journal of Computer Vision. 27: 107-126
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