— Since we can accumulate a huge amount of data including useless information in these years, it is important to investigate various extraction method of clusters from data inclu...
We present a clustering technique addressing redundancy for bounded-distance clusters, which means being able to determine the minimum number of cluster-heads per node, and the ma...
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
In this paper we propose a novel framework for 3D object categorization. The object is modeled it in terms of its sub-parts as an histogram of 3D visual word occurrences. We introd...
Roberto Toldo, Umberto Castellani, Andrea Fusiello
Using visualization techniques to assist conventional data mining tasks has attracted considerable interest in recent years. This paper addresses a challenging issue in the use of...