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» Robust Visual Tracking using L1 Minimization
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ICPR
2008
IEEE
15 years 6 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
SSIAI
2000
IEEE
15 years 4 months ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal
ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
14 years 9 months ago
A combination of particle filtering and deterministic approaches for multiple kernel tracking
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Céline Teuliere, Éric Marchand, Laur...
ICIP
2008
IEEE
16 years 1 months ago
Hybrid tracking approach using optical flow and pose estimation
This paper proposes an hybrid approach to estimate the 3D pose of an object. The integration of texture information based on image intensities in a more classical non-linear edge-...
Éric Marchand, Étienne Mémin,...
ICVS
1999
Springer
15 years 4 months ago
Improving 3D Active Visual Tracking
Tracking in 3D with an active vision system depends on the performance of both motor control and vision algorithms. Tracking is performed based on different visual behaviors, name...
João P. Barreto, Paulo Peixoto, Jorge Batis...