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» Visual Object Tracking using Adaptive Correlation Filters
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ICPR
2008
IEEE
14 years 9 months ago
SVD based Kalman particle filter for robust visual tracking
Object tracking is one of the most important tasks in computer vision. The unscented particle filter algorithm has been extensively used to tackle this problem and achieved a grea...
Qingdi Wei, Weiming Hu, Xi Li, Xiaoqin Zhang, Yang...
ICIP
2002
IEEE
14 years 9 months ago
Template tracking using color invariant pixel features
In our method for tracking objects, appearance features are smoothed by robust and adaptive Kalman filters, one to each pixel, making the method robust against occlusions. While t...
Hieu Tat Nguyen, Arnold W. M. Smeulders
ICIP
2005
IEEE
14 years 9 months ago
Multi-step active object tracking with entropy based optimal actions using the sequential Kalman filter
We describe an enhanced method for the selection of optimal sensor actions in a probabilistic state estimation framework. We apply this to the selection of optimal focal lengths f...
Benjamin Deutsch, Heinrich Niemann, Joachim Denzle...
CVPR
2009
IEEE
2305views Computer Vision» more  CVPR 2009»
15 years 3 months ago
Visual tracking on the affine group via geometric particle filtering using optimal importance function
We propose a geometric method for visual tracking, in which the 2-D affine motion of a given object template is estimated in a video sequence by means of coordinateinvariant partic...
Junghyun Kwon (Seoul National University), Kyoung ...
ECCV
2004
Springer
14 years 9 months ago
Adaptive Probabilistic Visual Tracking with Incremental Subspace Update
Visual tracking, in essence, deals with non-stationary data streams that change over time. While most existing algorithms are able to track objects well in controlled environments,...
David A. Ross, Jongwoo Lim, Ming-Hsuan Yang