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» A New Discriminative Kernel From Probabilistic Models
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88
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ICIP
2005
IEEE
15 years 11 months ago
Visual tracking via efficient kernel discriminant subspace learning
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
PR
2010
186views more  PR 2010»
14 years 8 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang
UIC
2009
Springer
15 years 4 months ago
Mining and Visualizing Mobile Social Network Based on Bayesian Probabilistic Model
Social networking has provided powerful new ways to find people, organize groups, and share information. Recently, the potential functionalities of the ubiquitous infrastructure le...
Jun-Ki Min, Su-Hyung Jang, Sung-Bae Cho
62
Voted
ICDAR
2007
IEEE
15 years 4 months ago
Exploiting Fisher Kernels in Decoding Severely Noisy Document Images
Decoding noisy document images is commonly needed in applications such as enterprise content management. Available OCR solutions are still not satisfactory especially on noisy ima...
J. Chen, Y. Wang
CVPR
2001
IEEE
15 years 11 months ago
Constructing Facial Identity Surfaces in a Nonlinear Discriminating Space
Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, selfshadi...
Yongmin Li, Shaogang Gong, Heather M. Liddell