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» Some Solutions to the Missing Feature Problem in Vision
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CGF
2005
311views more  CGF 2005»
13 years 7 months ago
Cubical Marching Squares: Adaptive Feature Preserving Surface Extraction from Volume Data
In this paper, we present a new method for surface extraction from volume data which preserves sharp features, maintains consistent topology and generates surface adaptively witho...
Chien-Chang Ho, Fu-Che Wu, Bing-Yu Chen, Yung-Yu C...
ECCV
2006
Springer
14 years 9 months ago
Optimal Multi-frame Correspondence with Assignment Tensors
Abstract. Establishing correspondence between features of a set of images has been a long-standing issue amongst the computer vision community. We propose a method that solves the ...
R. Oliveira, R. Ferreira, J. P. Costeira
CVPR
2008
IEEE
14 years 9 months ago
Recognizing human actions using multiple features
In this paper, we propose a framework that fuses multiple features for improved action recognition in videos. The fusion of multiple features is important for recognizing actions ...
Jingen Liu, Saad Ali, Mubarak Shah
CVPR
2005
IEEE
14 years 9 months ago
Optimal Point Correspondence through the Use of Rank Constraints
We propose a solution to the n-frame correspondence problem under the factorization framework. During the matching process, our algorithm takes explicitly into account the geometr...
João Costeira, João Xavier, Ricardo ...
ICCV
2011
IEEE
12 years 7 months ago
Latent Low-Rank Representation for Subspace Segmentation and Feature Extraction
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
Guangcan Liu, Shuicheng Yan