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» Learning Features for Tracking
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CVPR
2006
IEEE
15 years 8 days ago
Tunable Kernels for Tracking
We present a tunable representation for tracking that simultaneously encodes appearance and geometry in a manner that enables the use of mean-shift iterations for tracking. The cl...
Vasu Parameswaran, Visvanathan Ramesh, Imad Zoghla...
ICML
2007
IEEE
14 years 11 months ago
Two-view feature generation model for semi-supervised learning
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Rie Kubota Ando, Tong Zhang
ICRA
2002
IEEE
171views Robotics» more  ICRA 2002»
14 years 3 months ago
Robust Tracking and Structure from Motion with Sample Based Uncertainty Representation
Geometric reconstruction of the environment from images is critical in autonomous mapping and robot navigation. Geometric reconstruction involves feature tracking, i.e., locating ...
Peng Chang, Martial Hebert
FUIN
2010
114views more  FUIN 2010»
13 years 5 months ago
Feature Selection via Maximizing Fuzzy Dependency
Feature selection is an important preprocessing step in pattern analysis and machine learning. The key issue in feature selection is to evaluate quality of candidate features. In t...
Qinghua Hu, Pengfei Zhu, Jinfu Liu, Yongbin Yang, ...
ICCV
2009
IEEE
1042views Computer Vision» more  ICCV 2009»
15 years 3 months ago
Activity Recognition using the velocity histories of tracked keypoints
We present an activity recognition feature inspired by human psychophysical performance. This feature is based on the velocity history of tracked keypoints. We present a generat...
Ross Messing, Chris Pal, Henry Kautz