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» Learning Parameterized Models of Image Motion
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CVPR
2003
IEEE
16 years 1 months ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai
ICPR
2004
IEEE
16 years 21 days ago
Tracking Periodic Motion using Bayesian Estimation
This paper presents a Bayesian approach to achieve efficient and accurate motion tracking in monocular image sequences. We first extract a deterministic motion model with six degr...
Andrew M. Wallace, Huiyu Zhou, Patrick R. Green
PAMI
2006
178views more  PAMI 2006»
14 years 11 months ago
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
Jakob J. Verbeek
ICIP
2007
IEEE
16 years 1 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
MM
2004
ACM
212views Multimedia» more  MM 2004»
15 years 5 months ago
Nonparametric motion model
Motion information is a powerful cue for visual perception. In the context of video indexing and retrieval, motion content serves as a useful source for compact video representati...
Ling-Yu Duan, Min Xu, Qi Tian, Changsheng Xu