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CVPR
2003
IEEE
15 years 11 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
BMVC
2010
14 years 7 months ago
Weakly Supervised Object Recognition and Localization with Invariant High Order Features
High order features have been proposed to incorporate geometrical information into the "bag of feature" representation. We propose algorithms to perform fast weakly supe...
Yimeng Zhang, Tsuhan Chen
WACV
2005
IEEE
15 years 3 months ago
Incorporating Background Invariance into Feature-Based Object Recognition
Current feature-based object recognition methods use information derived from local image patches. For robustness, features are engineered for invariance to various transformation...
Andrew N. Stein, Martial Hebert
CVPR
2004
IEEE
15 years 1 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
100
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ICIAP
2003
ACM
15 years 2 months ago
Detection and recognition of moving objects using statistical motion detection and Fourier descriptors
Object recognition, i. e. classification of objects into one of several known object classes, generally is a difficult task. In this paper we address the problem of detecting an...
Daniel Toth, Til Aach