Background identification is a common feature in many video processing systems. This
paper proposes two hardware implementations of the OpenCV version of the Gaussian …

The background identification methods are used in many fields like video surveillance and
traffic monitoring. In this paper we propose a hardware implementation of the Gaussian …

The processing of a high-definition video stream in real-time is a challenging task for
embedded systems. However, modern FPGA devices have both a high operating frequency …

The H. 264/Advanced Video Coding (AVC) is the industry standard in network surveillance
offering the lowest bitrate for a given perceptual quality among any MPEG or proprietary …

Although trivial background subtraction (BGS) algorithms (eg frame differencing, running
average...) can perform quite fast, they are not robust enough to be used in various computer …

Adaptive Gaussian mixtures have been used for modeling nonstationary temporal
distributions of pixels in video surveillance applications. However, a common problem for …

Adaptive Gaussian Mixture Models (GMM) have been one of the most popular and
successful approaches to perform foreground segmentation on multimodal background …

Automated video surveillance applications require accurate separation of foreground and
background image content. Cost-sensitive embedded platforms place real-time performance …

Object detection and tracking are main tasks in video surveillance systems. Extracting the
background is an intensive task with high computational cost. This work proposes a …

This paper demonstrates the use of a single-chip FPGA for the segmentation of moving
objects in a video sequence. The system maintains highly accurate background models, and …