Understanding video events, ie, the translation of low-level content in video sequences into
high-level semantic concepts, is a research topic that has received much interest in recent …

From the streets of London to subway stations in New York City, hundreds of thousands of
surveillance cameras ubiquitously collect hundreds of thousands of videos, often running …

Mobile cameras on robotic platforms can support fixed multi-camera installations to improve
coverage and target localization accuracy. We propose a novel collaborative framework for …

Extracting the hidden and useful knowledge embedded within video sequences and thereby
discovering relations between the various elements to help an efficient decision-making …

Understanding motion patterns is of great importance to analyze the behavior of objects in
the vigilance area. Grouping the motion patterns into clusters in such a way that similar …

This paper presents an algorithm for camera localization using trajectory estimation
(CLUTE) in a distributed network of nonoverlapping cameras. The algorithm recovers the …

In many classification problems, it is necessary to consider the specific location of an n-
dimensional space from which features have been calculated. For example, considering the …

The present work presents a new method for activity extraction and reporting from video
based on the aggregation of fuzzy relations. Trajectory clustering is first employed mainly to …

The present work introduces a new method for activity extraction from video. To achieve this,
we focus on the modelling of context by developing an algorithm that automatically learns …

In this paper we propose an innovative approach for behaviour recognition, from a
multicamera environment, based on translating video activity into semantics. First, we fuse …