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» Robust Incremental Subspace Learning for Object Tracking
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ICRA
2005
IEEE
105views Robotics» more  ICRA 2005»
14 years 1 months ago
A New Approach to the Use of Edge Extremities for Model-based Object Tracking
— This paper presents a robust model-based visual tracking algorithm that can give accurate 3D pose of a rigid object. Our tracking algorithm uses an incremental pose update sche...
Youngrock Yoon, Akio Kosaka, Jae Byung Park, Avina...
CVPR
2012
IEEE
11 years 10 months ago
Multi-target tracking by online learning of non-linear motion patterns and robust appearance models
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...
Bo Yang, Ram Nevatia
FGR
2011
IEEE
245views Biometrics» more  FGR 2011»
12 years 11 months ago
Fast and robust appearance-based tracking
— We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently propo...
Stephan Liwicki, Stefanos Zafeiriou, Georgios Tzim...
PAMI
2007
194views more  PAMI 2007»
13 years 7 months ago
Robust Object Tracking Via Online Dynamic Spatial Bias Appearance Models
This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...
Datong Chen, Jie Yang
ECCV
2004
Springer
14 years 9 months ago
A Bayesian Framework for Multi-cue 3D Object Tracking
This paper presents a Bayesian framework for multi-cue 3D object tracking of deformable objects. The proposed spatio-temporal object representation involves a set of distinct linea...
Jan Giebel, Dariu Gavrila, Christoph Schnörr