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CVPR
2007
IEEE
14 years 9 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
CVPR
2009
IEEE
1561views Computer Vision» more  CVPR 2009»
15 years 2 months ago
SURFTrac: Efficient Tracking and Continuous Object Recognition using Local Feature Descriptors
We present an efficient algorithm for continuous image recognition and feature descriptor tracking in video which operates by reducing the search space of possible interest poin...
Duy-Nguyen Ta (Georgia Institute of Technology), W...
CVPR
2005
IEEE
14 years 9 months ago
Generative versus Discriminative Methods for Object Recognition
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Ilkay Ulusoy, Christopher M. Bishop
ECCV
2008
Springer
14 years 9 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
ECCV
2008
Springer
14 years 9 months ago
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
Viewpoint invariant pedestrian recognition is an important yet under-addressed problem in computer vision. This is likely due to the difficulty in matching two objects with unknown...
Douglas Gray, Hai Tao