: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
This paper presents a method for evaluating multiple feature spaces while tracking, and for adjusting the set of features used to improve tracking performance. Our hypothesis is t...
Abstract. In this paper we present a boosting based approach for automatic detection of micro-calcifications in mammographic images. Our proposal is based on using local features e...
Arnau Oliver, Albert Torrent, Meritxell Tortajada,...
This paper presents an interactive video event retrieval system based on improved adaboost learning. This system consists of three main steps. Firstly, a long video sequence is pa...
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...