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» A Graph-matching Kernel for Object Categorization
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MVA
2007
133views Computer Vision» more  MVA 2007»
13 years 9 months ago
Selection of Object Recognition Methods According to the Task and Object Category
Service robots need object recognition strategy that can work on various objects in complex backgrounds. Since no single method can work in every situation, we need to combine sev...
Al Mansur, Yoshinori Kuno
BMVC
2010
13 years 5 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
ICCV
2009
IEEE
13 years 5 months ago
Incremental Multiple Kernel Learning for object recognition
A good training dataset, representative of the test images expected in a given application, is critical for ensuring good performance of a visual categorization system. Obtaining ...
Aniruddha Kembhavi, Behjat Siddiquie, Roland Miezi...
CVPR
2009
IEEE
15 years 2 months ago
Efficient Kernels for Identifying Unbounded-Order Spatial Features
Higher order spatial features, such as doublets or triplets have been used to incorporate spatial information into the bag-of-local-features model. Due to computational limits, ...
Yimeng Zhang (Carnegie Mellon University), Tsuhan ...
ICCV
2007
IEEE
14 years 9 months ago
Proximity Distribution Kernels for Geometric Context in Category Recognition
We propose using the proximity distribution of vectorquantized local feature descriptors for object and category recognition. To this end, we introduce a novel "proximity dis...
Haibin Ling, Stefano Soatto