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ICCV
2005
IEEE
14 years 7 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah
ICCV
2009
IEEE
13 years 3 months ago
Dense 3D reconstruction method using a single pattern for fast moving object
Dense 3D reconstruction of extremely fast moving objects could contribute to various applications such as body structure analysis and accident avoidance and so on. The actual case...
Ryusuke Sagawa, Yuichi Ota, Yasushi Yagi, Ryo Furu...
AMCS
2008
146views Mathematics» more  AMCS 2008»
13 years 5 months ago
Fault Detection and Isolation with Robust Principal Component Analysis
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
Yvon Tharrault, Gilles Mourot, José Ragot, ...
PR
2007
96views more  PR 2007»
13 years 5 months ago
Weighted and robust learning of subspace representations
A reliable system for visual learning and recognition should enable a selective treatment of individual parts of input data and should successfully deal with noise and occlusions....
Danijel Skocaj, Ales Leonardis, Horst Bischof
ICMCS
2005
IEEE
116views Multimedia» more  ICMCS 2005»
13 years 11 months ago
Video Object Boundary Reconstruction by 2-Pass Voting
In this paper we propose a voting-based object boundary reconstruction approach. Tensor voting has been studied by many people recently, and it can be used for boundary estimation...
Like Zhang, Qi Tian, Nicu Sebe, Jingsheng Ma