In this paper, a pixel-based background modeling method, which uses nonparametric kernel
density estimation, is proposed. To reduce the burden of image storage, we modify the …

Robust detection of moving objects from video sequences is an important task in machine
vision systems and applications. To detect moving objects, accurate background subtraction …

A novel background subtraction method that can work under complex environments is
presented in this paper. The proposed method consists of two stages: coarse foreground …

Traditional background subtraction methods perform poorly when scenes contain dynamic
backgrounds such as waving tree branches, spouting fountain, illumination changes …

This paper presents an approach to background subtraction based on rectangular regions
(blocks). The general principle is to successively divide the image into blocks and detect …

Background subtraction is a powerful mechanism for detecting change in a sequence of
images that finds many applications. The most successful background subtraction methods …

Although it has been widely discussed in video surveillance, background subtraction is still
an open problem in the context of complex scenarios, eg, dynamic backgrounds …

The estimation of the background image from a video sequence is necessary in some
applications. Computing the median for each pixel over time is effective, but it fails when the …

We propose a novel adaptive maintenance scheme for the codebook-based background
subtraction algorithm. With this technique, the accuracy and efficiency of the model are …

Object detection is an important basis for tracking and recognition in visual surveillance
systems via stationary cameras. The traditional background subtraction method is difficult to …