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ECCV
2008
Springer
15 years 19 days ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert
EPIA
2009
Springer
14 years 5 months ago
Learning Visual Object Categories with Global Descriptors and Local Features
Different types of visual object categories can be found in real-world applications. Some categories are very heterogeneous in terms of local features (broad categories) while oth...
Rui Pereira, Luís Seabra Lopes
MM
2010
ACM
462views Multimedia» more  MM 2010»
13 years 11 months ago
KPB-SIFT: a compact local feature descriptor
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...
Gangqiang Zhao, Ling Chen, Gencai Chen, Junsong Yu...
ICPR
2010
IEEE
14 years 5 months ago
Object Recognition and Localization Via Spatial Instance Embedding
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Nazli Ikizler Cinbis, Stan Sclaroff
IJCAI
1997
14 years 2 days ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling