this paper presents a grid connected photovoltaic system, which acts as both power generator and active power filter (apf), based on flying capacitor multicell (fcm) converter. increase in the number of output voltage levels, natural self-balancing of flying capacitors and dc link voltage and lower power rating of components are the main futures of fcm converter compared with conventional multi...

Particle filters is now established as one of the most popular method for visual tracking. Within this framework, it is generally assumed that the data are temporally independent given the sequence of object states. In this paper, we argue that in general the data are correlated, and that modeling such dependency should improve tracking robustness. To take data correlation into account, we prop...

We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video ...

The Kalman filter is widely applied in target tracking problems. It is known to be the linear optimal filter in the white Gaussian noise environment. In some radar applications [1–9], the measurement noise may deviate from the Gaussian assumption. For instance, complex targets can cause irregular electromagnetic wave reflection. This phenomenon varies the target center in a radar and gives rise...

The problem of tracking an object in an image sequence involves challenges like translation, in-plane and out-of-plane rotations, scaling, variations in ambient light and occlusions. A model of an object to be tracked is built off-line by making a training set with images of the object with different poses. A dimensionality reduction technique is used to capture the variations in the training i...

Control of a class of uncertain nonlinear systems, which estimates unavailable state variables, is considered. A new approach for robust tracking control problem of satellite for large rotational maneuvers is presented in this paper. The features of this approach include a strong algorithm to estimate attitude, based on discrete extended Kalman filter combined with a continuous extended Kalman ...

This paper presents design and implementation of three new Infrared Counter-Countermeasure (IRCCM) efficient methods using Neural Network (NN), Fuzzy System (FS), and Kalman Filter (KF). The proposed algorithms estimate tracking error or correction signal when jamming occurs. An experimental test setup is designed and implemented for performance evaluation of the proposed methods. The methods v...

Human tracking in video is required for interactive multimedia, action recognition, and surveillance. Two of the main challenges in tracking are modelling adequately features for tracking and resolving data (measurement) ambiguities in order to map out trajectories. A silhouette based tracker with reduced complexity joint probabilistic data association filter for resolution of measurement-to-tr...

Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated surveillance. In this paper, we introduce a specified object tracking based particle filter used in an e...

Probabilistic approaches to tracking often use single-source Bayesian models; applying these to multi-source tasks is problematic. We apply a principled multi-object tracking implementation, the Gaussian mixture probability hypothesis density filter, to track multiple sources having fixed pitch plus vibrato. We demonstrate high-quality filtering in a synthetic experiment, and find improved trac...