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» Unsupervised learning of visual taxonomies
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CVPR
2008
IEEE
14 years 9 months ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele
ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
14 years 1 months ago
Hierarchy-Regularized Latent Semantic Indexing
Organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. Beside textual features, the hierarchical structure of directories reflect...
Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, V...
CORR
2010
Springer
193views Education» more  CORR 2010»
13 years 6 months ago
A Probabilistic Approach for Learning Folksonomies from Structured Data
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor

Publication
218views
11 years 12 months ago
Comparing Visual Feature Coding for Learning Disjoint Camera Dependencies
This paper systematically investigates the effectiveness of different visual feature coding schemes for facilitating the learning of time-delayed dependencies among disjoint multi-...
Xiatian Zhu, Shaogang Gong, and Chen Change Loy
CVPR
2003
IEEE
14 years 9 months ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai