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» Probabilistic Location Recognition using Reduced Feature Set
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IROS
2007
IEEE
134views Robotics» more  IROS 2007»
14 years 2 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...
CVPR
2007
IEEE
14 years 9 months ago
A Probabilistic Model for Object Recognition, Segmentation, and Non-Rigid Correspondence
We describe a method for fully automatic object recognition and segmentation using a set of reference images to specify the appearance of each object. Our method uses a generative...
Ian Simon, Steven M. Seitz
ECCV
2010
Springer
13 years 9 months ago
Location Recognition Using Prioritized Feature Matching
We present a fast, simple location recognition and image localization method that leverages feature correspondence and geometry estimated from large Internet photo collections. Suc...
Yunpeng Li, Noah Snavely, Daniel P. Huttenlocher
CORR
2010
Springer
221views Education» more  CORR 2010»
13 years 5 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...
CVPR
2001
IEEE
14 years 9 months ago
3D Object Recognition from Range Images using Local Feature Histograms
This paper explores a view-based approach to recognize free-form objects in range images. We are using a set of local features that are easy to calculate and robust to partial occ...
Bastian Leibe, Bernt Schiele, Günter Hetzel, ...