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» Simultaneous Modeling and Tracking (SMAT) of Feature Sets
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80
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ICCV
2009
IEEE
16 years 2 months ago
Tracking in Unstructured Crowded Scenes
This paper presents a target tracking framework for unstructured crowded scenes. Unstructured crowded scenes are defined as those scenes where the motion of a crowd appears to b...
Mikel Rodriguez, Saad Ali, Takeo Kanade
ICDM
2008
IEEE
107views Data Mining» more  ICDM 2008»
15 years 4 months ago
Graph-Based Iterative Hybrid Feature Selection
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
ErHeng Zhong, Sihong Xie, Wei Fan, Jiangtao Ren, J...
NAR
2007
85views more  NAR 2007»
14 years 9 months ago
The TIGR Rice Genome Annotation Resource: improvements and new features
In The Institute for Genomic Research Rice Genome Annotation project (http://rice.tigr.org), we have continued to update the rice genome sequence with new data and improve the qua...
Shu Ouyang, Wei Zhu, John A. Hamilton Jr., Haining...
CVPR
2010
IEEE
1208views Computer Vision» more  CVPR 2010»
15 years 6 months ago
Visual Tracking Decomposition
We propose a novel tracking algorithm that can work robustly in a challenging scenario such that several kinds of appearance and motion changes of an object occur at the same time....
Junseok Kwon (Seoul National University), Kyoung M...
78
Voted
ICCV
2001
IEEE
15 years 11 months ago
Model-Based Bundle Adjustment with Application to Face Modeling
We present a new model-based bundle adjustment algorithm to recover the 3D model of a scene/object from a sequence of images with unknown motions. Instead of representing scene/ob...
Ying Shan, Zicheng Liu, Zhengyou Zhang