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CVPR
2007
IEEE
16 years 8 months ago
Detecting Pedestrians by Learning Shapelet Features
In this paper, we address the problem of detecting pedestrians in still images. We introduce an algorithm for learning shapelet features, a set of mid?level features. These featur...
Payam Sabzmeydani, Greg Mori
CVPR
2008
IEEE
16 years 8 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
ECCV
2008
Springer
16 years 8 months ago
Learning for Optical Flow Using Stochastic Optimization
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Yunpeng Li, Daniel P. Huttenlocher
ICML
2005
IEEE
16 years 7 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
ICML
2004
IEEE
16 years 7 months ago
Learning large margin classifiers locally and globally
A new large margin classifier, named MaxiMin Margin Machine (M4 ) is proposed in this paper. This new classifier is constructed based on both a "local" and a "globa...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...