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» Incremental Learning for Visual Tracking
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CVPR
2010
IEEE
14 years 6 months ago
Tracking the Invisible: Learning Where the Object Might be
Objects are usually embedded into context. Visual context has been successfully used in object detection tasks, however, it is often ignored in object tracking. We propose a metho...
Helmut Grabner, Jiri Matas, Philippe Cattin, Luc V...
ICRA
2009
IEEE
121views Robotics» more  ICRA 2009»
14 years 4 months ago
Learning sequential visual attention control through dynamic state space discretization
² Similar to humans and primates, artificial creatures like robots are limited in terms of allocation of their resources to huge sensory and perceptual information. Serial process...
Ali Borji, Majid Nili Ahmadabadi, Babak Nadjar Ara...
ICPR
2004
IEEE
14 years 11 months ago
Switching Particle Filters for Efficient Real-time Visual Tracking
Particle filtering is an approach to Bayesian estimation of intractable posterior distributions from time series signals distributed by non-Gaussian noise. A couple of variant par...
Kenji Doya, Shin Ishii, Takashi Bando, Tomohiro Sh...
FGR
1996
IEEE
117views Biometrics» more  FGR 1996»
14 years 2 months ago
Tracking and Learning Graphs and Pose on Image Sequences of Faces
We demonstrate a system capable of tracking, in real world image sequences, landmarks such as eyes, mouth, or chin on a face. In the standard version, knowledge previously collect...
Thomas Maurer, Christoph von der Malsburg
WACV
2008
IEEE
14 years 4 months ago
Likelihood Map Fusion for Visual Object Tracking
Visual object tracking can be considered as a figure-ground classification task. In this paper, different features are used to generate a set of likelihood maps for each pixel i...
Zhaozheng Yin, Fatih Porikli, Robert T. Collins