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» Principal Component Analysis Based on L1-Norm Maximization
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CVPR
2009
IEEE
2305views Computer Vision» more  CVPR 2009»
16 years 5 months ago
Visual tracking on the affine group via geometric particle filtering using optimal importance function
We propose a geometric method for visual tracking, in which the 2-D affine motion of a given object template is estimated in a video sequence by means of coordinateinvariant partic...
Junghyun Kwon (Seoul National University), Kyoung ...
ICIP
2001
IEEE
15 years 11 months ago
Use of a probabilistic shape model for non-linear registration of 3D scattered data
In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal compon...
Isabelle Corouge, Christian Barillot
ICPR
2002
IEEE
15 years 10 months ago
Building the Topological Tree by Recursive FCM Color Clustering
In this paper we define a Topological Tree (TT) as a knowledge representation method that aims to describe important visual and spatial features of image regions, namely the color...
Rita Cucchiara, Costantino Grana, Andrea Prati, St...
84
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ICML
2007
IEEE
15 years 10 months ago
Local learning projections
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essen...
Bernhard Schölkopf, Kai Yu, Mingrui Wu, Shipe...
66
Voted
ISCC
2009
IEEE
106views Communications» more  ISCC 2009»
15 years 4 months ago
Multivariate reduction in wireless sensor networks
In wireless sensor networks, energy consumption is generally associated with the amount of sent data once communication is the activity of the network that consumes more energy. T...
Orlando Silva Junior, André L. L. de Aquino...