In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Proportional data (normalized histograms) have been frequently occurring in various areas, and they could be mathematically abstracted as points residing in a geometric simplex. A...
In partial-duplicate image retrieval, images are commonly represented using Bag-of-visual-Words (BoW) built from image local features, such as SIFT. Therefore, the discriminative ...
This paper introduces BoostMap, a method that can significantly reduce retrieval time in image and video database systems that employ computationally expensive distance measures, ...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...
In plenty of scenarios, data can be represented as vectors mathematically abstracted as points in a Euclidean space. Because a great number of machine learning and data mining app...