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» Visual Tracking Using Learned Linear Subspaces
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ECCV
2004
Springer
16 years 2 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
BVAI
2007
Springer
15 years 6 months ago
Incremental Subspace Learning for Cognitive Visual Processes
In real life, visual learning is supposed to be a continuous process. Humans have an innate facility to recognize objects even under less-than-ideal conditions and to build robust ...
Bogdan Raducanu, Jordi Vitrià
ICCV
2003
IEEE
16 years 2 months ago
Weighted and Robust Incremental Method for Subspace Learning
Visual learning is expected to be a continuous and robust process, which treats input images and pixels selectively. In this paper we present a method for subspace learning, which...
Danijel Skocaj, Ales Leonardis
ICIP
2005
IEEE
16 years 2 months ago
Nonlinear dimensionality reduction for classification using kernel weighted subspace method
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
Guang Dai, Dit-Yan Yeung
NIPS
2000
15 years 1 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick