An important class of problems in software are race conditions. Errors of this class are becoming more common and more dangerous with the development of multi-processor and multi-core systems, especially in such a fundamentally parallel environment as an operating system kernel. The paper overviews some of existing approaches to detect race conditions including DataCollider system based on conc...

In this paper, we are discussing a video surveillance scenario with real-time moving object detection and tracking. The detection of moving object is important in many tasks, such as video surveillance and moving object tracking. The design of a video surveillance system is directed on automatic identification of events of interest, especially on tracking and classification of moving objects. N...

Topic tracking is an important task of Topic Detection and Tracking (TDT). Its purpose is to detect stories, from a stream of news, related to known topics. Each topic is “known” by its association with several sample stories that discuss it. In this paper, we propose a new method to build the keywords dependency profile (KDP) of each story and track topic basing on similarity between the profi...

The important role of surveillance and control systems in maintaining human safety in nowadays life creates a vast field for designing algorithms to fulfill security. This thesis demonstrates the procedures of implementing background modeling and evolving fuzzy rule-based classifier (eClass) for real – time novelty detection and object tracking. Initially the ways which security systems perceiv...

This is a PhD thesis proposal. We concetrate on fast visual tracking methods in videos. We are especially interested in incremental learning of new object appearances. Current state of the art methods like background subtraction, kernel-based tracking or tracking by detection are shortly described. We use linear predictors for fast object tracking and an exhaustive description of the predictor ...

For the widely demanding of adaptive multiple moving objects tracking in intelligent transportation field, a new type of traffic video based multi-object tracking method is presented. Background is modeled by difference of Gaussians (DOG) probability kernel and background subtraction is used to detect multiple moving objects. After obtaining the foreground, shadow is eliminated by an edge detec...

Discriminative correlation filters (DCF) have recently shown excellent performance in visual object tracking area. In this paper we summarize the methods of updating model filter from discriminative correlation filter (DCF) based tracking algorithms and analyzes similarities and differences among these methods. We deduce the relationship among updating coefficient in high dimension (kernel tric...

object detection plays an important role in successfulness of a wide range ofapplications that involve images as input data. in this paper we have presented anew approach for background modeling by nonconsecutive frames differencing.direction and velocity of moving objects have been extracted in order to get anappropriate sequence of frames to perform frame subtraction. stationary parts ofbackg...