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ICCV
2009
IEEE
17 years 1 days ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ICCV
2009
IEEE
2061views Computer Vision» more  ICCV 2009»
17 years 1 days ago
Background Subtraction for Freely Moving Cameras
Background subtraction algorithms define the background as parts of a scene that are at rest. Traditionally, these algorithms assume a stationary camera, and identify moving obj...
Yaser Sheikh, Omar Javed, Takeo Kanade
ICCV
2009
IEEE
17 years 1 days ago
Optimal Correspondences from Pairwise Constraints
Correspondence problems are of great importance in computer vision. They appear as subtasks in many applications such as object recognition, merging partial 3D reconstructions a...
Olof Enqvist, Klas Josephson, Fredrik Kahl
ICCV
2009
IEEE
17 years 1 days ago
Seeing 3D Objects in a Single 2D Image
A general framework simultaneously addressing pose estimation, 2D segmentation, object recognition, and 3D reconstruction from a single image is introduced in this paper. The pr...
Diego Rother, Guillermo Sapiro
ICCV
2009
IEEE
17 years 1 days ago
Detection of Human Actions From A Single Example
We present an algorithm for detecting human actions based upon a single given video example of such actions. The proposed method is unsupervised, does not require learning, segm...
Hae Jong Seo, Peyman Milanfar
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