0957-4174/$ see front matter 2013 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2013.01.028 ⇑ Corresponding author. Address: Laboratory of Co Software Engineering, Department of Electronics, Tec tute of Crete, Romanou 3, Chania 73133, Greece. Tel.: E-mail address: [email protected] ( In this research work a new hybrid approach to spatio-temporal seismic clustering is proposed....

Agglomerative hierarchical clustering methods based on Gaussian probability models have recently shown promise in a variety of applications. In this approach, a maximum-likelihood pair of clusters is chosen for merging at each stage. Unlike classical methods, model-based methods reduce to a recurrence relation only in the simplest case, which corresponds to the classical sum of squares method. ...

Estimating the number of speakers in an audio segment is a necessary step in the process of speaker diarization, but current diarization algorithms do not explicitly define a prior probability on this estimation. This work proposes a process for including priors in speaker diarization with agglomerative hierarchical clustering (AHC). It is also shown that the exclusion of a prior with AHC is it...

We present a novel clustering approach for moving object trajectories that are constrained by an underlying road network. The approach builds a similarity graph based on these trajectories then uses modularity-optimization hiearchical graph clustering to regroup trajectories with similar profiles. Our experimental study shows the superiority of the proposed approach over classic hierarchical cl...

In this paper we tackle the issue of clustering trajectories of geolocalized observations. Using clustering technics based on the choice of a distance between the observations, we first provide a comprehensive review of the different distances used in the literature to compare trajectories. Then based on the limitations of these methods, we introduce a new distance : Symmetrized Segment-Path Di...

The proposed divisive clustering method performs simultaneously a hierarchy of a set of objects and a monothetic characterization of each cluster of the hierarchy. A division is performed according to the within-cluster inertia criterion which is minimized among the bipartitions induced by a set of binary questions. In order to improve the clustering, the algorithm revises at each step the divi...

The goal of video cosegmentation is to jointly extract the common foreground regions and/or objects from a set of videos. In this paper, we present an approach for video cosegmentation that uses graphbased hierarchical clustering as its basic component. Actually, in this work, video cosegmentation problem is transformed into a graph-based clustering problem in which a cluster represents a set o...

Via training, dance experts develop special experience-based embodied representations of body and movement. Professional dancers, amateurs and novices sorted central functional nodes of two dance movements according to their spatial equivalence. Results of a hierarchical cluster analysis and classification probabilities revealed movement-specific differences in mental representations related to...

A novel approach to the extraction of image regions of uniform color and its application to automatic texture detection is discussed. The method searches for alternating color patterns, through hierarchical clustering of color pairs from adjacent image regions. The final result is a hierarchy of texture regions, described by their boundaries and a set of features, detected at multiple accuracy ...

Algorithms of agglomerative hierarchical clustering using asymmetric similarity measures are studied. Two different measures between two clusters are proposed, one of which generalizes the average linkage for symmetric similarity measures. Asymmetric dendrogram representation is considered after foregoing studies. It is proved that the proposed linkage methods for asymmetric measures have no re...