Background subtraction is a widely used operation in the video surveillance, aimed at separating the expected scene (the background) from the unexpected entities (the foreground). There are several problems related to this task, mainly due to the blurred boundaries between background and foreground definitions. Therefore, background subtraction is an open issue worth to be addressed under diffe...

This paper presents an efficient method for ship target segmentation in infrared (IR) images. It consists of mainly two procedures: iterative image segmentation and ship target selection. First, based on the intensity distribution of an IR image, we design a global background subtraction filter (GBSF) to suppress the background, and an adaptive row mean subtraction filter (ARMSF) to enhance the...

Background modeling is a key step of background subtraction methods used in the context of static camera. The goal is to obtain a clean background and then detect moving objects by comparing it with the current frame. Mixture of Gaussians Model [1] is the most popular technique and presents some limitations when dynamic changes occur in the scene like camera jitter, illumination changes and mov...

Visual surveillance in dynamic scenes, especially for human and some objects is one of the most active research areas. An attempt has been made to this issue in this work. It has wide spectrum of promising application including human identification to detect the suspicious behavior, crowd flux statistics, and congestion analysis using multiple cameras. In this paper deals with the problem of de...

This article proposes a novel background subtraction (BGS) technique to detect local changes corresponding to the movement of the objects in video scenes. Here we propose an efficient combination of six local features; three existing and three newly proposed. For background modeling and subtraction here a statistical parametric biunique model is proposed. In the proposed BGS scheme, during the ...

Recently developed statistical methods for background subtraction have made increasingly complicated environments amenable to automated analysis. Here we illustrate results for spatio-temporal background modeling, anomaly detection, shape description, and object localization on relevant parts of the PETS2005 data set. The results are analyzed both to distinguish between difficulties caused by d...

In this paper, we introduce a fast and robust method for tracking positions of the centers and the ngertips of both right and left hands. Our method makes use of infrared camera images for reliable detection of user's hands, and uses template matching strategy for nding ngertips. This method is an essential part of our augmented desk interface in which a user can, with natural hand gestures, si...