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» Learning on lie groups for invariant detection and tracking
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ICIP
2007
IEEE
14 years 9 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
ICPR
2008
IEEE
14 years 1 months ago
Ranking the local invariant features for the robust visual saliencies
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Shengping Xia, Peng Ren, Edwin R. Hancock
ECCV
2010
Springer
14 years 13 days ago
Detecting ground shadows in outdoor consumer photographs
Detecting shadows from images can significantly improve the performance of several vision tasks such as object detection and tracking. Recent approaches have mainly used illuminat...
CVPR
2007
IEEE
14 years 9 months ago
Learning Features for Tracking
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
Michael Grabner, Helmut Grabner, Horst Bischof
IROS
2007
IEEE
136views Robotics» more  IROS 2007»
14 years 1 months ago
Task-induced symmetry and reduction in kinematic systems with application to needle steering
— Lie group symmetry in a mechanical system can lead to a dimensional reduction in its dynamical equations. Typically, the symmetries that one exploits are intrinsic to the mecha...
Vinutha Kallem, Dong Eui Chang, Noah J. Cowan