Clustering is an efficient way to group data into different classes on basis of the internal and
previously unknown schemes inherent of the data. With the development of the location …

Rapid advance of location acquisition technologies boosts the generation of trajectory data,
which track the traces of moving objects. A trajectory is typically represented by a sequence …

Focus on movement data has increased as a consequence of the larger availability of such
data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in …

The processes that cause and influence movement are one of the main points of enquiry in
movement ecology. However, ecology is not the only discipline interested in movement: a …

Background Longitudinal data are data in which each variable is measured repeatedly over
time. One possibility for the analysis of such data is to cluster them. The majority of clustering …

Keyframe selection has been crucial for effective and efficient video content analysis. While
most of the existing approaches represent individual frames with global features, we, for the …

Outlier detection acts as one of the most important analysis tasks for trajectory stream. In
stream scenarios, such properties as unlimitedness, time-varying evolutionary, sparsity, and …

We propose a model for subtrajectory clustering---the clustering of subsequences of
trajectories; each cluster of subtrajectories is represented as a pathlet, a sequence of points …

Many devices generate large amounts of data that follow some sort of sequentiality, eg,
motion sensors, e-pens, eye trackers, etc. and often these data need to be compressed for …

The process of computing a representative trajectory for a set of raw (or even semantically
enriched) trajectories is an attractive solution to minimize several challenges related to …