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» Supervised Image Segmentation Using Markov Random Fields
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ICIP
2006
IEEE
16 years 1 months ago
Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency
This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, w...
Sheng-Yan Yang, Chiou-Ting Hsu
ICIP
2000
IEEE
16 years 1 months ago
Motion Estimation Using Adaptive Blocksize Observation Model and Efficient Multiscale Regularization
Bayesian motion estimation requires two pdf models: observation model and motion field (prior) model. The optimization process for this method uses sequential approach, e.g. simul...
Stephanus Suryadarma Tandjung, Teddy Surya Gunawan...
ACISICIS
2007
IEEE
15 years 6 months ago
Minimum Message Length Clustering of Spatially-Correlated Data with Varying Inter-Class Penalties
We present here some applications of the Minimum Message Length (MML) principle to spatially correlated data. Discrete valued Markov Random Fields are used to model spatial correl...
Gerhard Visser, David L. Dowe
PAMI
2008
161views more  PAMI 2008»
14 years 11 months ago
Multilayered 3D LiDAR Image Construction Using Spatial Models in a Bayesian Framework
Standard 3D imaging systems process only a single return at each pixel from an assumed single opaque surface. However, there are situations when the laser return consists of multip...
Sergio Hernandez-Marin, Andrew M. Wallace, Gavin J...
CVPR
2007
IEEE
16 years 1 months ago
An MRF and Gaussian Curvature Based Shape Representation for Shape Matching
Matching and registration of shapes is a key issue in Computer Vision, Pattern Recognition, and Medical Image Analysis. This paper presents a shape representation framework based ...
Pengdong Xiao, Nick Barnes, Tibério S. Caet...