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ECCV
2008
Springer
14 years 9 months ago
A Probabilistic Cascade of Detectors for Individual Object Recognition
A probabilistic system for recognition of individual objects is presented. The objects to recognize are composed of constellations of features, and features from a same object shar...
Pierre Moreels, Pietro Perona
NIPS
2004
13 years 8 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
ICPR
2006
IEEE
14 years 8 months ago
Efficient, Simultaneous Detection of Multiple Object Classes
At present, the object categorisation literature is still dominated by the use of individual class detectors. Detecting multiple classes then implies the subsequent application of...
Esther Koller-Meier, Luc J. Van Gool, Philipp Zehn...
DAGM
2007
Springer
13 years 11 months ago
Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification
Cascades of classifiers constitute an important architecture for fast object detection. While boosting of simple (weak) classifiers provides an established framework, the design of...
Rezaul Karim, Martin Bergtholdt, Jörg H. Kapp...
CVPR
2008
IEEE
13 years 9 months ago
Optimizing discrimination-efficiency tradeoff in integrating heterogeneous local features for object detection
A large variety of image features has been invented for detection of objects of a known class. We propose a framework to optimize the discrimination-efficiency tradeoff in integra...
Bo Wu, Ram Nevatia