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CVPR
2001
IEEE
14 years 6 months ago
Rapid Object Detection using a Boosted Cascade of Simple Features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
Paul A. Viola, Michael J. Jones
ICASSP
2011
IEEE
12 years 8 months ago
Combining generic and class-specific codebooks for object categorization and detection
Combining advantages of shape and appearance features, we propose a novel model that integrates these two complementary features into a common framework for object categorization ...
Hong Pan, Yaping Zhu, Liang-Zheng Xia, Truong Q. N...
ICPR
2004
IEEE
14 years 6 months ago
Object Recognition Using Segmentation for Feature Detection
: A new method is presented to learn object categories from unlabeled and unsegmented images for generic object recognition. We assume that each object can be characterized by a se...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
ICPR
2006
IEEE
14 years 6 months ago
Computation of Rotation Local Invariant Features using the Integral Image for Real Time Object Detection
We present a framework for object detection that is invariant to object translation, scale, rotation, and to some degree, occlusion, achieving high detection rates, at 14 fps in c...
Michael Villamizar, Alberto Sanfeliu, Juan Andrade...
CVPR
2008
IEEE
14 years 6 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