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» Learning Similarity for Texture Image Retrieval
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MM
2005
ACM
171views Multimedia» more  MM 2005»
14 years 1 months ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen
SIGIR
2008
ACM
13 years 7 months ago
Learning to reduce the semantic gap in web image retrieval and annotation
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Changhu Wang, Lei Zhang 0001, Hong-Jiang Zhang
MIR
2003
ACM
174views Multimedia» more  MIR 2003»
14 years 27 days ago
Content-based image retrieval by clustering
In a typical content-based image retrieval (CBIR) system, query results are a set of images sorted by feature similarities with respect to the query. However, images with high fea...
Yixin Chen, James Ze Wang, Robert Krovetz
IVC
2007
176views more  IVC 2007»
13 years 7 months ago
Kernel-based distance metric learning for content-based image retrieval
ct 8 For a specific set of features chosen for representing images, the performance of a content-based image retrieval (CBIR) system 9 depends critically on the similarity or diss...
Hong Chang, Dit-Yan Yeung
3DICA
2000
13 years 9 months ago
Automatic Reconstruction of Large 3D Models of Real Environments from Unregistered Data-sets
Towards photo-realistic 3D scene reconstruction from range and color images, we present a statistical technique for multimodal image registration. Statistical tools are employed t...
Faysal Boughorbel, David L. Page, Mongi A. Abidi