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» Learning Image Components for Object Recognition
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ICCV
2005
IEEE
16 years 1 months ago
Learning Object Categories from Google's Image Search
Current approaches to object category recognition require datasets of training images to be manually prepared, with varying degrees of supervision. We present an approach that can...
Robert Fergus, Fei-Fei Li 0002, Pietro Perona, And...
AAI
2010
195views more  AAI 2010»
14 years 8 months ago
Automatic Extraction of Go Game Positions from Images: a Multi-Strategical Approach to Constrained Multi-Object Recognition
Here, we present a constrained object recognition task that has been robustly solved largely with simple machine learning methods, using a small corpus of about 100 images taken u...
Alexander K. Seewald
CLOR
2006
15 years 3 months ago
A Discriminative Framework for Texture and Object Recognition Using Local Image Features
This chapter presents an approach for texture and object recognition that uses scale- or affine-invariant local image features in combination with a discriminative classifier. Text...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
ICDAR
2011
IEEE
13 years 11 months ago
Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning
—Reading text from photographs is a challenging problem that has received a signicant amount of attention. Two key components of most systems are (i) text detection from images a...
Adam Coates, Blake Carpenter, Carl Case, Sanjeev S...
CVPR
2008
IEEE
16 years 1 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen