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» Incremental Multiple Kernel Learning for object recognition
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ICCV
2005
IEEE
14 years 1 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
IJCV
2000
180views more  IJCV 2000»
13 years 7 months ago
Probabilistic Models of Appearance for 3-D Object Recognition
We describe how to model the appearance of a 3-D object using multiple views, learn such a model from training images, and use the model for object recognition. The model uses pro...
Arthur R. Pope, David G. Lowe
ICPR
2006
IEEE
14 years 8 months ago
A Semi-supervised SVM for Manifold Learning
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
Zhili Wu, Chun-hung Li, Ji Zhu, Jian Huang
EMMCVPR
2007
Springer
14 years 1 months ago
Compositional Object Recognition, Segmentation, and Tracking in Video
Abstract. The complexity of visual representations is substantially limited by the compositional nature of our visual world which, therefore, renders learning structured object mod...
Björn Ommer, Joachim M. Buhmann
ICRA
2010
IEEE
227views Robotics» more  ICRA 2010»
13 years 5 months ago
Efficient multi-view object recognition and full pose estimation
We present an approach for efficiently recognizing all objects in a scene and estimating their full pose from multiple views. Our approach builds upon a state of the art single-vie...
Alvaro Collet, Siddhartha S. Srinivasa