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ICCV
2009
IEEE
1176views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Building Rome in a Day
We present a system that can match and reconstruct 3D scenes from extremely large collections of photographs such as those found by searching for a given city (e.g., Rome) on In...
Sameer Agarwal, Noah Snavely, Ian Simon, Steven M....
CIVR
2009
Springer
583views Image Analysis» more  CIVR 2009»
15 years 9 months ago
Mining from Large Image Sets
So far, most image mining was based on interactive querying. Although such querying will remain important in the future, several applications need image mining at such wide scale...
Luc J. Van Gool, Michael D. Breitenstein, Stephan ...
SPIESR
2004
117views Database» more  SPIESR 2004»
14 years 11 months ago
Image database clustering with SVM-based class personalization
To allow efficient browsing of large image collections, we have to provide a summary of its visual content. We present in this paper a robust approach to organize image databases:...
Bertrand Le Saux, Nozha Boujemaa
PAKDD
2009
ACM
263views Data Mining» more  PAKDD 2009»
15 years 4 months ago
Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval
It is a challenging and important task to retrieve images from a large and highly varied image data set based on their visual contents. Problems like how to fill the semantic gap b...
Xin Chen, Xiaohua Hu, Xiajiong Shen
ICASSP
2010
IEEE
14 years 10 months ago
A nonnegative sparsity induced similarity measure with application to cluster analysis of spam images
Image spam is an email spam that embeds text content into graphical images to bypass traditional spam filters. The majority of previous approaches focus on filtering image spam ...
Yan Gao, Alok N. Choudhary, Gang Hua