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» Joint Optimization of Cascaded Classifiers for Computer Aide...
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CVPR
2006
IEEE
14 years 7 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman
ICIP
2009
IEEE
13 years 3 months ago
Cat face detection with two heterogeneous features
In this paper, we propose a generic and efficient object detection framework based on two heterogeneous features and demonstrate effectiveness of our method for a cat face detecti...
Tatsuo Kozakaya, Satoshi Ito, Susumu Kubota, Osamu...
CVPR
2007
IEEE
14 years 7 months ago
Kernel Sharing With Joint Boosting For Multi-Class Concept Detection
Object/scene detection by discriminative kernel-based classification has gained great interest due to its promising performance and flexibility. In this paper, unlike traditional ...
Wei Jiang, Shih-Fu Chang, Alexander C. Loui
BMVC
2010
13 years 2 months ago
StyP-Boost: A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers
We introduce a novel bilinear boosting algorithm, which extends the multi-class boosting framework of JointBoost to optimize a bilinear objective function. This allows style param...
Jonathan Warrell, Philip H. S. Torr, Simon Prince
ECCV
2008
Springer
14 years 7 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele