Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Interactive image search or relevance feedback is the process which helps a user refining his query and finding difficult target categories. This consists in partially labeling a ...
Hichem Sahbi, Patrick Etyngier, Jean-Yves Audibert...
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...