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CVPR
2007
IEEE
15 years 11 months ago
Combining local and global motion models for feature point tracking
Aeron Buchanan, Andrew W. Fitzgibbon
CVPR
2005
IEEE
15 years 11 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
BMVC
2002
15 years 5 days ago
Low Density Feature Point Matching for Articulated Pose Identification
We describe a general algorithm for identifying an arbitrary pose of an articulated subject with low density feature points. The algorithm aims to establish a one-to-one correspon...
Horst Holstein, Baihua Li
CVPR
2007
IEEE
15 years 11 months ago
Cast Shadow Removal Combining Local and Global Features
In this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM t...
Zhou Liu, Kaiqi Huang, Tieniu Tan, Liangsheng Wang
ICCV
2009
IEEE
14 years 7 months ago
SURF Tracking
Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motionbased trackin...
Wei He, Takayoshi Yamashita, Hongtao Lu, Shihong L...