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» Application of Level Set Methods in Computer Vision
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CVPR
2012
IEEE
11 years 10 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
JSCIC
2008
48views more  JSCIC 2008»
13 years 7 months ago
A Level-Set Method for Computing the Eigenvalues of Elliptic Operators Defined on Compact Hypersurfaces
We demonstrate, through separation of variables and estimates from the semiclassical analysis of the Schr
Jeremy Brandman
CVPR
2006
IEEE
14 years 9 months ago
On Manifold Structure of Cardiac MRI Data: Application to Segmentation
We develop theory and algorithms to incorporate image manifold constraints in a level set segmentation algorithm. This provides a framework to simultaneously segment every image o...
Qilong Zhang, Richard Souvenir, Robert Pless
CVPR
2009
IEEE
14 years 2 months ago
Resolution-Invariant Image Representation and its applications
We present a Resolution-Invariant Image Representation (RIIR) framework in this paper. The RIIR framework includes the methods of building a set of multi-resolution bases from tra...
Jinjun Wang, Shenghuo Zhu, Yihong Gong
ICCV
2001
IEEE
14 years 9 months ago
Robust Principal Component Analysis for Computer Vision
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
Fernando De la Torre, Michael J. Black