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» Joint Optimization of Cascaded Classifiers for Computer Aide...
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CVPR
2006
IEEE
16 years 3 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
14 years 11 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...
135
Voted
CVPR
2007
IEEE
16 years 3 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
114
Voted
BMVC
2010
14 years 10 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
16 years 3 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