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» Robust Incremental Subspace Learning for Object Tracking
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ICRA
2005
IEEE
105views Robotics» more  ICRA 2005»
15 years 5 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
13 years 2 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»
14 years 3 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»
14 years 11 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
16 years 1 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