Background modeling has emerged as a popular foreground detection technique for various
applications in video surveillance. Background modeling methods have become increasing …

Intrusion detection systems (IDSs) must be capable of detecting new and unknown attacks,
or anomalies. We study the problem of building detection models for both pure anomaly …

A public, complete, compact, and well structured database is proposed, which allows to test
moving object detection strategies. The database is composed of many real indoor and …

Abandoned objects detection is one of the most challenging tasks in intelligent video
surveillance systems. In this paper we present a new method for detecting abandoned …

Component-based software engineering has been increasingly adopted for software
development. This approach relies on using reusable components as the building blocks for …

In this paper, we propose a hybrid background model that relies on edge and non-edge
features of the image to produce the model. We encode these features into a coding …

Unattended object detection is an important task in surveillance. Thus, we propose a new
method to detect unattended object by modeling the objects as newly learned temporal …

In this paper, we propose a novel edge descriptor method for background modeling. In
comparison to previous edge-based local-pattern methods, it is more robust to noise and …

In this paper, a reliable pixel-based foreground-background segmentation technique for
detecting object (s) of interest (OOI) from video sequence captured by a fixed camera is …

In this thesis, we present a robust descriptor for background subtraction which is able to
describe texture from an image sequence. The descriptor is less sensitive to noisy pixels …