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PAMI
2008
161views more  PAMI 2008»
13 years 8 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
CVPR
1998
IEEE
14 years 10 months ago
Incorporating Illumination Constraints in Deformable Models
In this paper we present a method for the integration of nonlinear holonomic constraints in deformable models and its application to the problems of shape and illuminant direction...
Dimitris Samaras, Dimitris N. Metaxas
ECCV
2002
Springer
14 years 10 months ago
Building Roadmaps of Local Minima of Visual Models
Getting trapped in suboptimal local minima is a perennial problem in model based vision, especially in applications like monocular human body tracking where complex nonlinear para...
Cristian Sminchisescu, Bill Triggs
ICPR
2004
IEEE
14 years 9 months ago
BTF Image Space Utmost Compression and Modelling Method
The bidirectional texture function (BTF) describes texture appearance variations due to varying illumination and viewing conditions. This function is acquired by large number of m...
Jirí Filip, Michael Arnold, Michal Haindl
3DPVT
2006
IEEE
190views Visualization» more  3DPVT 2006»
14 years 2 months ago
3D City Modeling Using Cognitive Loops
3D city modeling using computer vision is very challenging. A typical city contains objects which are a nightmare for some vision algorithms, while other algorithms have been desi...
Nico Cornelis, Bastian Leibe, Kurt Cornelis, Luc J...