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ICIP
2009
IEEE
13 years 4 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu
VMV
2008
170views Visualization» more  VMV 2008»
13 years 8 months ago
Robust contour-based object tracking integrating color and edge likelihoods
We present in this paper a novel object tracking system based on 3D contour models. For this purpose, we integrate two complimentary likelihoods, defined on local color statistics...
Giorgio Panin, Erwin Roth, Alois Knoll
CVPR
2011
IEEE
12 years 10 months ago
Robust Tracking Using Local Sparse Appearance Model and K-Selection
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Baiyang Liu, junzhou Huang, Casimir Kulikowski, Li...
MVA
1996
109views Computer Vision» more  MVA 1996»
13 years 8 months ago
Model Based Tracking on 3D Objects
In this paper, a new tracking algorithm, based on local minimum energy, is proposed for matching between a projected model and corresponding image features in real-time. The algor...
Zheng Li, Han Wang
ICCV
2003
IEEE
14 years 8 months ago
Recognition with Local Features: the Kernel Recipe
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...