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

Foreground/background segmentation via change detection in video sequences is often
used as a step** stone in high-level analytics and applications. Despite the wide variety of …

Change detection is one of the most commonly encountered low-level tasks in computer
vision and video processing. A plethora of algorithms have been developed to date, yet no …

Most of the recently published background subtraction methods can still be classified as
pixel-based, as most of their analysis is still only done using pixel-by-pixel comparisons …

Most background subtraction approaches offer decent results in baseline scenarios, but
adaptive and flexible solutions are still uncommon as many require scenario-specific …

In general, the problem of change detection is studied in color space. Most proposed
methods aim at dynamically finding the best color thresholds to detect moving objects …

Change detection is one of the most commonly encountered low-level tasks in computer
vision and video processing. A plethora of algorithms have been developed to date, yet no …

The objective of this study is to compare several change detection methods for a monostatic
camera and identify the best method for different complex environments and backgrounds in …

Background information is crucial for many video surveillance applications such as object
detection and scene understanding. In this paper, we present a novel pixel-to-model (P2M) …

The proposed work describes an efficient methodology for adaptive background modeling
and foreground extraction from video data using the newly proposed Spatio-temporal region …