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» Markov Random Field Models in Computer Vision
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Publication
1851views
17 years 2 months ago
Cerebrovascular Segmentation from TOF Using Stochastic Models
In this paper, we present an automatic statistical approach for extracting 3D blood vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) data. The voxels of the d...
M. Sabry Hassouna, Aly A. Farag, Stephen Hushek, T...
SCALESPACE
2009
Springer
15 years 8 months ago
PDE-Driven Adaptive Morphology for Matrix Fields
Matrix fields are important in many applications since they are the adequate means to describe anisotropic behaviour in image processing models and physical measurements. A promin...
Bernhard Burgeth, Michael Breuß, Luis Pizarr...
130
Voted
CVPR
2010
IEEE
15 years 6 months ago
Motion Fields to Predict Play Evolution in Dynamic Sport Scenes
Videos of multi-player team sports provide a challenging domain for dynamic scene analysis. Player actions and interactions are complex as they are driven by many factors, such as...
Kihwan Kim, Matthias Grundmann, Ariel Shamir, Iain...
ICCV
2005
IEEE
15 years 7 months ago
HMM Based Falling Person Detection Using Both Audio and Video
Automatic detection of a falling person in video is an important problem with applications in security and safety areas including supportive home environments and CCTV surveillance...
B. Ugur Töreyin, Yigithan Dedeoglu, A. Enis &...
TSP
2008
101views more  TSP 2008»
15 years 1 months ago
Optimal Node Density for Detection in Energy-Constrained Random Networks
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject to a constraint on average (per node) energy consumption is analyzed. The spatial...
Animashree Anandkumar, Lang Tong, Ananthram Swami