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ICCV
2011
IEEE
12 years 5 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
IEICET
2006
136views more  IEICET 2006»
13 years 5 months ago
Calibration Method for Misaligned Catadioptric Camera
This paper proposes a calibration method for catadioptric camera systems consisting of a surface of revolution mirror and a perspective camera, such as HyperOmni Vision. The propo...
Tomohiro Mashita, Yoshio Iwai, Masahiko Yachida
BMCBI
2008
160views more  BMCBI 2008»
13 years 5 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...
NIPS
2007
13 years 6 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
DAGM
2005
Springer
13 years 10 months ago
Three-Dimensional Shape Knowledge for Joint Image Segmentation and Pose Estimation
Abstract. This paper presents the integration of 3D shape knowledge into a variational model for level set based image segmentation and tracking. Having a 3D surface model of an ob...
Thomas Brox, Bodo Rosenhahn, Joachim Weickert