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VISUALIZATION
1998
IEEE
15 years 2 months ago
Extremal feature extraction from 3-D vector and noisy scalar fields
We are interested in feature extraction from volume data in terms of coherent surfaces and 3-D space curves. The input can be an inaccurate scalar or vector field, sampled densely...
Chi-Keung Tang, Gérard G. Medioni
SIAMAM
2008
170views more  SIAMAM 2008»
14 years 9 months ago
Absolute Stability and Complete Synchronization in a Class of Neural Fields Models
Neural fields are an interesting option for modelling macroscopic parts of the cortex involving several populations of neurons, like cortical areas. Two classes of neural field equ...
Olivier D. Faugeras, François Grimbert, Jea...
ECCV
2008
Springer
15 years 11 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher
APVIS
2009
14 years 11 months ago
Visualizing time-varying features with TAC-based distance fields
To analyze time-varying data sets, tracking features over time is often necessary to better understand the dynamic nature of the underlying physical process. Tracking 3D time-vary...
Teng-Yok Lee, Han-Wei Shen
SIAMIS
2010
378views more  SIAMIS 2010»
14 years 4 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert