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CVPR
2012
IEEE
11 years 7 months ago
Robust visual tracking using autoregressive hidden Markov Model
Recent studies on visual tracking have shown significant improvement in accuracy by handling the appearance variations of the target object. Whereas most studies present schemes ...
Dong Woo Park, Junseok Kwon, Kyoung Mu Lee
IJCV
2008
188views more  IJCV 2008»
13 years 5 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
CVPR
2003
IEEE
14 years 7 months ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...
ICCV
2011
IEEE
12 years 2 months ago
Tracking by Sampling Trackers
We propose a novel tracking framework called visual tracker sampler that tracks a target robustly by searching for the appropriate trackers in each frame. Since the real-world trac...
junseok kwon and kyoung mu lee
ICIP
2009
IEEE
14 years 6 months ago
Robust Visual Tracking Based On Simplified Biologically Inspired Features
We address the problem of robust appearance-based visual tracking. First, a set of simplified biologically inspired features (SBIF) is proposed for object representation and the B...