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The multi target tracking problem is considered in this paper and a parallel kalman filter algorithm (Decentralized Kalman Filter) is presented. The proposed algorithm designed to make early and more accurate estimate for dynamic multi-targets in the area and to determine whether the sensor data representing the same targets or not, when the ability to track targets is essential in missile defense...
One of the applications of wireless sensor networks is target tracking. There are several methods to target tracking and among these methods, particle filter has high capability in solving nonlinear/non-Gaussian systems. Particle filter is one of the methods for Bayesian recursive estimation for position estimation in wireless sensor networks. Clustered management of dense networks is a famous known...
In this article, we present an algorithm to track objects in complex environments like, large variations in scale and orientation, background clutters, illumination changes, pose variation and occlusion. A multilayer perceptron based discriminative appearance model is constructed to distinguish the objects from their cluttered backgrounds. Moments of the binary image are used to estimate scale and...
One factor of human sperm health is sperm motility. Motility is the ability of sperm to move. Sperm with healthy motility move forward promptly, not inactive and not moving in circles. In this paper, we would like to analyse sperm motility by considering the problem of multi object tracking in video sequences of human sperms. The challenges in multi-sperm tracking are many human sperms have fast and...
Autonomous surface vehicle (ASV) is developed to fulfill requirement of many offshore applications. One of the examples is tracking an underwater target of interests. Tracking underwater target involves two general steps, target position estimation and target following. In this paper, a control strategy for ASV performing underwater acoustic source tracking is presented. Firstly, method of acoustic...
This paper proposes a dynamic waveform selection algorithm for radar target tracking. Following the waveform auto-adaptive ideas in the classical control theory, the Cramer-Rao lower bound (CRLB) of the covariance of target range and range rate estimations is utilized to describe the statistic characteristics of the measurement noises in tracking. Then the relationship between waveform parameters...
Object tracking is one of the important tasks for mobile robot, and developing a robust and real-time visual tracking algorithm which can adaptively capture the varying appearance of target under challenging conditions for mobile robot is still an open problem. The main challenges of visual tracking for mobile robot come from variation of target's appearance and disturbance of environment. To cope...
This paper addresses the problem of multi-sensor multi-target tracking. The main contribution is an efficient implementation of the multi-sensor δ-Generalized labeled Multi-Bernoulli (δ-GLMB) update. To truncate the weighted sums of the multi-target exponentials, the ranked assignment algorithm is used in the update to determine the most important terms without computing all the terms. Simulation...
This paper considers multiple resolvable group target estimation under clutter environment. We first build the structure for the resolvable group targets using graph theory. Then, the group estimation involves two stages of the target state estimation and group state (group size, shape, etc) estimation. In the first stage, based on the given group dynamic models, we derive the target estimated state...
This paper presents a tracking algorithm of an Autonomous Underwater Vehicle (AUV) using an Autonomous Surface Vehicle (ASV) equipped with a ranger interrogator system. Worldwide, there has been increasing interest in the use of ASVs to execute missions of increasing complexity without direct supervision by human operators. A key-enabling element for the execution of such missions is the availability...
In this paper consensus based algorithms for distributed target tracking in large scale camera networks are discussed and a new adaptive algorithm is proposed. Camera networks are typically characterized by sparse communication and coverage topologies, as well as by the presence of multiple targets and clutter. The proposed algorithm (IPDA-ACF) is a result of the introduction of the probabilities...
Multi-object tracking is a difficult problem underlying many computer vision applications. In this work, we focus on sediment transport experiments in a flow were sediments are represented by spherical calibrated beads. The aim is to track all beads over long time sequences to obtain sediment velocities and concentration. Classical algorithms used in fluid mechanics fail to track the beads over long...
Robust scale and rotation estimation is an important and challenging problem in visual object tracking. There have been proposed many sophisticated trackers to track the location of a target accurately, but most of them do not take much attention to the scale and rotation estimation. Inspired by the success of the correlation filters in visual tracking, we proposed a novel scale-and-rotation correlation...
This paper puts forward a new tracking algorithm based on Mean Shift algorithm and the Particle Filter algorithm. We combined the two algorithms efficiently based on the open structure system of both Mean Shift algorithm and the Particle Filter algorithm, and the model similar expression of establishment of the target, similarity measure and the selection of kernel function they have. The new algorithm...
This paper investigates the problem of distributed angle-of-arrival (AOA) target tracking in 3D space using unmanned aerial vehicles (UAVs). Because of communication constraints arising from distance and bandwidth constraints in a distributed UAV system, some UAVs may not be able to share their information with all other UAVs. This will lead to reduced tracking performance. In order to improve the...
This paper addresses the coordinated target tracking problem by mobile sensor agents with bearing-range measurements. The strategy is divided into two steps. Firstly, a distributed unscented information filter is designed to estimate the states of the moving target. Secondly, a distributed control law is presented to drive each sensor agent of the network to the next position which maximizes the determinant...
Multistatic radar system has a great potential for human detection and tracking for its fine localization precision, wide coverage and good observability. Traditional human detection and tracking are performed on the one dimensional (1-D) range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets and obtain the measurements for target tracking. It can...
This paper presents a novel object tracking system that combines support vector machines (SVM) and Kalman filter. Objective tracking in videos is a challenging problem due to loss of information, which may be caused by varying illuminance in a scene, occlusions, similar target appearances, and so on. In this paper, we use Kalman filter to predict the dynamics of target object, so as to generate candidate...
When the signal-to-noise ratio (SNR) is reduced in case of track-before-detect (TBD) for weak target detection, the TBD algorithm based on Gaussian mixture probability hypothesis density (GM-PHD) filter cannot estimate the number or status of targets accurately. In order to solve this problem, a TBD algorithm based on GM-PHD smoothing filter (SGM-PHD-TBD) is proposed. Within the framework of TBD standard...
Feature extractor plays an important role in visual tracking due to the changing appearance of the object. In this paper, we propose a novel approach in correlation filter framework, which decomposes the task of tracking into translation and scale estimation. We employ two correlation filters with hierarchical convolutional features to estimate the translation. Furthermore, we use a discriminative...
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