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» Visual Object Tracking using Adaptive Correlation Filters
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CVPR
2008
IEEE
14 years 9 months ago
Sequential particle swarm optimization for visual tracking
Visual tracking usually involves an optimization process for estimating the motion of an object from measured images in a video sequence. In this paper, a new evolutionary approac...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
CVPR
2005
IEEE
14 years 9 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
CVPR
2008
IEEE
14 years 9 months ago
A recursive filter for linear systems on Riemannian manifolds
We present an online, recursive filtering technique to model linear dynamical systems that operate on the state space of symmetric positive definite matrices (tensors) that lie on...
Ambrish Tyagi, James W. Davis
SIP
2001
13 years 9 months ago
Convergence acceleration of the LMS algorithm using successive data orthogonalization
We propose a new adaptive filtering algorithm whose convergence rate is very fast even for a highly correlated input signal. It is well-known that convergence rate gets worse when...
H.-C. Shin, W.-J. Song
TROB
2008
118views more  TROB 2008»
13 years 7 months ago
A New Kalman-Filter-Based Framework for Fast and Accurate Visual Tracking of Rigid Objects
The best of Kalman-filter-based frameworks reported in the literature for rigid object tracking work well only if the object motions are smooth (which allows for tight uncertainty ...
Youngrock Yoon, Akio Kosaka, Avinash C. Kak