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CVPR
2004
IEEE
15 years 3 months ago
Scale-Invariant Shape Features for Recognition of Object Categories
We introduce a new class of distinguished regions based on detecting the most salient convex local arrangements of contours in the image. The regions are used in a similar way to ...
Frédéric Jurie, Cordelia Schmid
CVPR
2007
IEEE
16 years 1 months ago
Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features
We present a discriminative shape-based algorithm for object category localization and recognition. Our method learns object models in a weakly-supervised fashion, without requiri...
Marius Leordeanu, Martial Hebert, Rahul Sukthankar
ICMCS
2007
IEEE
223views Multimedia» more  ICMCS 2007»
15 years 6 months ago
An Effective Local Invariant Descriptor Combining Luminance and Color Information
Extraction of stable local invariant features is very important in many computer vision applications, such as image matching, object recognition and image retrieval. Most existing...
Dong Zhang, Weiqiang Wang, Wen Gao, Shuqiang Jiang
CVPR
2003
IEEE
16 years 1 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
2007
IEEE
16 years 1 months ago
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists...
Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau,...