In this article, we proposed a surveillance video retrieval method based on detection of moving objects and researched on key problems in surveillance video, such as moving objects detection, video segmentation, selection and description of key frames, and measurement of feature similarities. We detected moving objects via movement detection algorithm based on codebook, and realized automatic s...

In this paper, we propose a novel level set based active contour model to segment textured images. The proposed methos is based on the assumption that local histograms of filtering responses between foreground and background regions are statistically separable. In order to be able to handle texture non-uniformities, which often occur in real world images, we use rotation invariant filtering fea...

The goal of multiple foreground cosegmentation (MFC) is to extract a finite number of foreground objects from an input image collection, while only an unknown subset of such objects is presented in each image. In this paper, we propose a novel unsupervised framework for decomposingMFC into three distinct yetmutually related tasks: image segmentation, segment matching, and figure/ground (F/G) as...

WMAP has provided CMB maps of the full sky. But the raw data is subject to foreground contamination , in particular near to the Galactic plane. Foreground cleaned maps have been derived , e.g., the internal linear combination (ILC) map of Bennett et al. (2003), and the reduced foreground TOH map of Tegmark et al. (2003). Using S statistics we examine the amount of the residual foreground contam...

Foreground detection plays a core role in a wide spectrum of applications such as tracking and behavior analysis. It, especially for videos captured by fixed cameras, can be posed as a component decomposition problem, the background of which is typically assumed to lie in a low dimensional subspace. However, in real world cases, dynamic backgrounds like waving trees and water ripples violate th...

A surveillance video contains two components – the background scene and the foreground targets. Foreground detection is difficult when there are illumination changes and background motions in the scene. We propose a two-step background subtraction framework for foreground detection. The background is modeled as block-based color Gaussian mixture model. In the first step of background subtractio...

The quality of outdoor surveillance videos are always degraded by bad weathers, such as fog, haze, and snowing. The degraded videos not only provide poor visualizations, but also increase the difficulty of vision-based analysis such as foreground/background segmentation. However, haze/fog removal has never been an easy task, and is often very time consuming. Most of the existing methods only co...

We developed an automatic object segmentation system to separate the foreground objects from the background scene in the MPEG video sequence. The system consists of two modules: the background modeling and updating module and the foreground object extraction module. For the first module and comparing to existing methods, the background model can be constructed no matter whether there exist movi...

Foreground segmentation is an essential task in many image processing applications and a commonly used approach to obtain foreground objects from the background. Many techniques exist, but due to shadows and changes in illumination the segmentation of foreground objects from the background remains challenging. In this paper, we present a powerful framework for detections of moving objects in re...

In this paper, a method to extract moving objects on a pixel base for MPEG-4 “sprite coding” is proposed. Sprite coding is a form of object coding: it uses a unified panoramic background image derived from a sequence having a camera motion, and a foreground object as video object planes (VOP’s). The proposed algorithm utilizes background difference, which is the difference between the original ...