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CVGIP
2006
163views more  CVGIP 2006»
15 years 3 months ago
SVD-matching using SIFT features
The paper tackles the problem of feature points matching between pair of images of the same scene. This is a key problem in computer vision. The method we discuss here is a versio...
Elisabetta Delponte, Francesco Isgrò, Franc...
CVPR
2007
IEEE
16 years 5 months ago
Connecting the Out-of-Sample and Pre-Image Problems in Kernel Methods
Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is more approp...
Pablo Arias, Gregory Randall, Guillermo Sapiro
CVPR
2008
IEEE
16 years 5 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
ISMIS
2005
Springer
15 years 8 months ago
Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms
Most recommendation systems employ variations of Collaborative Filtering (CF) for formulating suggestions of items relevant to users’ interests. However, CF requires expensive co...
Manos Papagelis, Ioannis Rousidis, Dimitris Plexou...
ECCV
2004
Springer
16 years 5 months ago
A Robust Probabilistic Estimation Framework for Parametric Image Models
Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
Maneesh Kumar Singh, Himanshu Arora, Narendra Ahuj...