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In this paper localization using UWB positioning system and an inertial unit containing a single accelerometer is considered. The main part of the paper describes a novel algorithm for person localization. The algorithm is based on modified Extended Kalman Filter and utilizes TDOA (Time Difference of Arrival) results obtained from UWB system and results of acceleration measurement performed by the...
In this paper, we propose an algorithm for tracking of moving objects in video sequences. Our method uses Kalman filter to predict the location of target and exploits superpixel based tracking algorithm to find the real position of target in a search region surrounding the predicted location. The motion dynamics and equations from mechanics physics are used to design a Kalman filter with assumption...
The paper explains about tracking a dynamically changing arbitrary shaped structure, important for determining their boundary and position estimation for advanced warning. The proposed algorithm uses active contour detection algorithm to construct the effective contour in each frame. Then Hungarian based Kalman filter is used to achieve best accuracy in estimation of future positions using multi-point...
In order to solve the problems of object detection and object tracking under complex scenes in video, this paper proposes a way to improve Gaussian Mixture Model algorithm based on the traditional Gaussian Mixture Model. When the model is updated, according to the characteristics of continuous video frame, the background model is divided into static regions and dynamic regions, and the background...
Synchronized measurements of electrical signals' phasors and frequencies are expected to be fundamental in the monitoring and management of future power systems, in particular in the so-called smart grid scenario. In fact, Phasor Measurement Units are conceived as the key elements of advanced wide area monitoring systems. For these reasons, the design of measurement algorithms able to track amplitude,...
The purpose of this paper is to design a Dynamic Neural Network that can effectively estimate all the states of single input non linear plants. The Kalman Filter algorithm has been used to train the weights of the Dynamic Neural Network. No a priori knowledge on the bounds of weights and errors are required. The nonlinear plant and the Dynamic Neural Network models have been simulated by the same...
In this paper, we present a consensus based distributed estimator to solve the naive node problem which exists in the distributed camera network. Due to the limited view of the camera, the camera node in the network may not be able to see the target all the time, which becomes a naive node. The existence of the naive node in the distributed network can decrease the performance of the estimator. This...
Demand response can provide services to the power network, however, coordination of spatially distributed demand response resources generally requires coping with imperfect communication networks. This work investigates methods to manage communication constraints (e.g., Delays and bandwidth limitations), faced by demand response aggregators who manipulate the on/off modes of residential thermostatically...
Many multimedia applications need to track moving objects. Consequently, designing a robust tracking system is a vital requirement for them. This paper proposes a new method for visual object tracking, which uses the mean shift tracking algorithm to derive the most similar target candidate to the target model. Bhattacharyya coefficient is employed to determine the similarities. Target's structure...
This paper presents a vision-aided method to restrain INS from drifting in GPS-denied periods. This system is composed of two cameras and an inertial measurement unit. Contrary to traditional SLAM, the coordinates of the feature points or any other priori information are not indispensable in this method. By using the tracked feature point from two consecutive frames, incremental displacement and velocity...
In this paper we introduced a theoretical framework for formation control and target tracking for a limited number of mobile robots with partially unknown dynamic models using decentralized and distributed Kalman filter. The mobile robots seek to track a stochastic target while trying to reach a pre-defined formation. Kalman-consensus filter and decentralized Kalman filter is used to infer the received...
The problem of recommending items to users is relevant to many applications and the problem has often been solved using methods developed from Collaborative Filtering (CF). Collaborative Filtering model-based methods such as Matrix Factorization have been shown to produce good results for static rating-type data, but have not been applied to time-stamped item adoption data. In this paper, we adopted...
This paper presents an effective evolutionary method to solve the Economic Dispatch (ED) problem with units having prohibited operating zones. The Kalman filter is an efficient recursive filter that estimates the state of a dynamic system from a series of noisy measurements in theTotal Power Generation (TPG). ED is an example of a dynamic system algorithm that has been widely used for determination...
Ultrasound guidance is used for many surgical applications such as biopsy and electrode insertion. This paper presents an improved method for tracking such micro tools inserted in human tissues. The RANSAC algorithm [1] has been implemented to detect the exact position of the needle in a stationary situation. In this paper, the Kalman filter is added to estimate the position of the needle in a dynamical...
The naval gun is a traditional navy weapon, which takes warship as the carrier. In modern naval ships, the small and medium caliber naval guns, which have quick response and high launch rate, is the main attack weapons in naval vessels. The level degree of the naval gun platform has a great influence on the launch accuracy. This paper mainly studied a platform angle dynamic measurement system based...
In this paper, we propose a new method for evaluating the precision of Kalman filter in video target tracking. Firstly, the performance evaluation model is presented which is different from the usual method that we handle the video. Then the parameter that used to assess the performance of the tracking algorithms is defined and utilized in effective evaluation procedure. In the end, experiments are...
The goal of target tracking is to find the targets between the consecutive frames in image sequences. Many tracking algorithms have been proposed and implemented to overcome difficulties that arise from noise, occlusion, clutter, and changes in the foreground objects or in the background environment. For the tracking methods based on traditional Kalman filter algorithm, there are several candidate...
The privacy of voice over IP (VoIP) systems is achieved by compressing and encrypting the sampled data. This paper investigates in detail the leakage of information from Skype, a widely used VoIP application. In this research, it has been demonstrated by using the dynamic time warping (DTW) algorithm, that sentences can be identified with an accuracy of 60%. The results can be further improved by...
This paper presents AMREF, an Adaptive Map Reduce Framework designed for an effective use of computational resources in data center networks to deal with real time data intensive applications. AMREF entails its adaptivity from adaptive splitter, adaptive mappers and adaptive reducers in a stochastic control manner. We use three methods, feedback control, stochastic learning with smooth filter and...
In this paper, a new algorithm for multiple maneuvering target tracking is proposed. The proposed algorithm which is based on separating the multiple maneuvering target tracking into three parts-the data association, the estimation of the single target dynamic model and the estimation of the single target tracking subproblems conditional on the data association and the target dynamic model. Where...
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