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IROS
2007
IEEE
134views Robotics» more  IROS 2007»
15 years 6 months ago
Feature selection for grasp recognition from optical markers
Abstract— Although the human hand is a complex biomechanical system, only a small set of features may be necessary for observation learning of functional grasp classes. We explor...
Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchel...
IJCNN
2008
IEEE
15 years 6 months ago
Feature selection based on kernel discriminant analysis for multi-class problems
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
Tsuneyoshi Ishii, Shigeo Abe
CORR
2010
Springer
221views Education» more  CORR 2010»
14 years 9 months ago
Reduction of Feature Vectors Using Rough Set Theory for Human Face Recognition
In this paper we describe a procedure to reduce the size of the input feature vector. A complex pattern recognition problem like face recognition involves huge dimension of input ...
Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nas...
ICASSP
2011
IEEE
14 years 3 months ago
Generic object recognition using automatic region extraction and dimensional feature integration utilizing multiple kernel learn
Recently, in generic object recognition research, a classification technique based on integration of image features is garnering much attention. However, with a classifying techn...
Toru Nakashika, Akira Suga, Tetsuya Takiguchi, Yas...
AVBPA
2005
Springer
226views Biometrics» more  AVBPA 2005»
15 years 5 months ago
Discriminant Analysis Based on Kernelized Decision Boundary for Face Recognition
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
Baochang Zhang, Xilin Chen, Wen Gao