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» Mixture Densities for Video Objects Recognition
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SSD
2007
Springer
124views Database» more  SSD 2007»
13 years 11 months ago
Querying Objects Modeled by Arbitrary Probability Distributions
In many modern applications such as biometric identification systems, sensor networks, medical imaging, geology, and multimedia databases, the data objects are not described exact...
Christian Böhm, Peter Kunath, Alexey Pryakhin...
CVPR
2000
IEEE
14 years 6 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona
TMM
2008
167views more  TMM 2008»
13 years 4 months ago
Mining Appearance Models Directly From Compressed Video
In this paper, we propose an approach to learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in vide...
Datong Chen, Qiang Liu, Mingui Sun, Jie Yang
FGR
1998
IEEE
131views Biometrics» more  FGR 1998»
13 years 9 months ago
Tracking and Segmenting People in Varying Lighting Conditions Using Colour
Colour cues were used to obtain robust detection and tracking of people in relatively unconstrained dynamic scenes. Gaussian mixture models were used to estimate probability densi...
Yogesh Raja, Stephen J. McKenna, Shaogang Gong
CVPR
2004
IEEE
14 years 6 months ago
Probabilistic Expression Analysis on Manifolds
In this paper, we propose a probabilistic videobased facial expression recognition method on manifolds. The concept of the manifold of facial expression is based on the observatio...
Ya Chang, Changbo Hu, Matthew Turk