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CVPR
2003
IEEE
14 years 9 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2005
IEEE
14 years 9 months ago
Efficient Image Matching with Distributions of Local Invariant Features
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
Kristen Grauman, Trevor Darrell
CVPR
2001
IEEE
14 years 9 months ago
Local Feature View Clustering for 3D Object Recognition
There have been important recent advances in object recognition through the matching of invariant local image features. However, the existing approaches are based on matching to i...
David G. Lowe
CVPR
2009
IEEE
15 years 2 months ago
View-Invariant Dynamic Texture Recognition using a Bag of Dynamical Systems
In this paper, we consider the problem of categorizing videos of dynamic textures under varying view-point. We propose to model each video with a collection of Linear Dynamics S...
Avinash Ravichandran, René Vidal, Rizwan Ch...
CVPR
2010
IEEE
14 years 1 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia