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Research Article | 13-December-2017

COOPERATIVE MULTI TARGET TRACKING USING MULTI SENSOR NETWORK

tracking system using multiple mobile sensors. For the purposes of surveillance and security, trackers use an Extended Kohonen neural network to track the moving targets in their environments. The proposed tracking algorithm can be used for single and multiple target tracking. A clustering algorithm is used in order to minimize the number of active trackers over time and hence save energy. An auction based algorithm is used for the purpose of optimizing the cooperation between trackers. Quantitative

Ahmed M. Elmogy, Fakhreddine O. Karray

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 3, 716–734

Article | 01-March-2016

IMAGE PROCESSING AND RECOGNITION ALGORITHM FOR TARGET TRACKING

to improve target tracking performance in dynamic target track system, this paper propose the processing method of positive and negative difference image to extract target information; research target image preprocessing algorithm, the separation and segmentation processing algorithm of target and background, target edge detection and extraction based on the collected images; use Laplace operator, Canny operator. Gauss-Laplace operator to gain target information and improved recognition target

Liping Lu, Jinfang Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 1, 353–376

Article | 01-September-2015

PERFORMANCE MEASUREMENT OF PHOTOELECTRIC DETECTION AND TARGET TRACKING ALGORITHM

To solve the unstable problem of target tracking detection system, this paper proposes an improved mean-shift algorithm for object tracking, establishes object tracking processing model;provides the processing algorithm of object tracking. According to the principal of object tracking, papersets up sky background brightness calculation model in photoelectric tracking optical detection area and detection capability calculation model of space object, analyzes the effect of background illumination

Haidou Yang, Wei Li

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1554–1575

Research paper | 01-September-2014

POSTERIOR BELIEF CLUSTERING ALGORITHM FOR ENERGY-EFFICIENT TRACKING IN WIRELESS SENSOR NETWORKS

In this paper, we propose a novel posterior belief clustering (PBC) algorithm to solve the tradeoff between target tracking performance and sensors energy consumption in wireless sensor networks. We model the target tracking under dynamic uncertain environment using partially observable Markov decision processes (POMDPs), and transform the optimization of the tradeoff between tracking performance and energy consumption into yielding the optimal value function of POMDPs. We analyze the error of

Bo Wu, Yanpeng Feng, Hongyan Zheng

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 3, 628–641

Article | 09-April-2018

Multi - scale Target Tracking Algorithm with Kalman Filter in Compression Sensing

Real-time Compressive Tracking (CT) uses the compression sensing theory to provide a new research direction for the target tracking field. The algorithm is simple, efficient and real-time. But there are still shortcomings: tracking results prone to drift phenomenon, cannot adapt to tracking the target scale changes. In order to solve these problems, this paper proposes to use the Kalman filter to generate the distance weights, and then use the weighted Bayesian classifier to correct the

Yichen Duan, Xue Li, Peng Wang, Dan Xu

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 10–14

Article | 01-December-2012

A MODEL FOR FUZZY DATA CORREALATION OF AIS AND RADAR

proposed a fuzzy correlation method for target tracking and data fusion. The experiment shows that the proposed method is correct and efficient and it can improve the performance and the stability of VTS.

Liu Chang, Cao Ming-zhi, Han Feng, Shi Gui-ming, Liu Ren-jie

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 4, 843–858

Research Article | 02-November-2017

MULTI-TARGET, MULTI-SENSOR TRACKING BASED ON QUALITY-OF-INFORMATION AND FORMAL BAYESIAN FRAMEWORKS

We consider a multi-target tracking problem that aims to simultaneously determine the number and state of mobile targets in the field. Conventional paradigms tend to report only the existence and state of targets according to centralized detection and data fusion. On the contrary, we investigate a multi-target, multi-sensor scenario in which (a) both the number and the state of the targets are unknown a priori; and (b) the detection with respect to targets is employed in a distributed manner

Juo-Yu Lee, Kung Yao

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 4, 842–857

Article | 07-May-2018

Levenberg-Marquardt Method Based Iterative Square Root Cubature Kalman Filter and its Applications to Maneuvering Re-entry Target Tracking

algorithm to the state estimation of maneuvering re-entry target tracking, the simulation results demonstrate that the ISRCKFLM algorithm has better accuracy of state estimation, comparable to Unscented Kalman filter and square root Cubature Kalman filter, according to estimation error analysis of the position, velocity, drag coefficient, turn coefficient and climbing force coefficient, and has fast convergence rate.

Mu Jing, Wang Changyuan

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 2, 10–13

Article | 01-March-2015

ROBUST VISUAL TRACKING BASED ON SUPPORT VECTOR MACHINE AND WEIGHTED SAMPLING METHOD

) and weighted multi-sample sampling method. Our method constructs a classifier by sampling positive and negative samples and then to find the best candidate that has the largest response using SVM classifier. What’s more, the proposed method integrates weighted multi-instance sampling method, which can consider the sample importance by the different weights. The experimental results on many sequences show the robustness and accuracy of the improved method. The proposed target tracking algorithm in

Gao Xiaoxing, Liu Feng

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 255–271

Article | 01-December-2015

FAST RCS MODELING FOR DYNAMIC TARGET TRACKING

Xiang Hua, Wuwei Yuan, Bin Lei

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 4, 1956–1976

research-article | 01-February-2020

Robust single target tracking using determinantal point process observations

focus on single target tracking. While the original PHD filter is based on a Poisson point process, several extensions have been proposed to cope with non-Poisson distributions. In particular, the Cardinalized PHD filter allows estimating the number of targets using arbitrary distributions and provides improved estimates (Mahler, 2007). The multi-Bernoulli and Poisson multi-Bernoulli mixture filters also allow to approximate the cardinality distribution and become especially well suited when the

S. Hernández, P. Sallis

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–8

Article | 02-November-2017

POSITIONING ACCURACY AND MULTI-TARGET SEPARATION WITH A HUMAN TRACKING SYSTEM USING NEAR FIELD IMAGING

H. Rimminen, J. Lindström, R. Sepponen

International Journal on Smart Sensing and Intelligent Systems, Volume 2 , ISSUE 1, 156–175

Article | 03-September-2013

DISTRIBUTED TARGET LOCALIZATION AND TRACKING WITH WIRELESS PYROELECTRIC SENSOR NETWORKS

Baihua Shen, Guoli Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1400–1418

Article | 01-March-2015

TRACKING OF MOVING TARGET BASED ON VIDEO MOTION NUCLEAR ALGORITHM

correlation and difference contour tracking algorithm based on a fixed background. The algorithm in the background under the condition of fixed to pay a smaller time complexity, the target detection and tracking has a good effect, so it has higher application value. Based on solving the detection and location of moving target tracking in real-time and accuracy requirements, a new moving target detection spatiotemporal correlation and difference contour tracking scheme based on the practical implementation

Wang Xiaojun, Pan Feng, Wang Weihong

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 181–198

Research Article | 01-September-2017

PERFORMANCE EVALUTION OF VIDEO SURVEILLANCE USING METE, MELT AND NIDC TECHNIQUE

To evaluate multi-target video tracking results, one needs to quantify the accuracy of the estimated target-size and the Cardinality error as the well as measure the frequency of occurrence of ID changes. By surveying existing multi-target tracking performance scores and, after discussing their limitations, the work proposes three parameter-independent measures for evaluating multi target video tracking. The measures consider target-size variations, combine accuracy and cardinality errors

M Anto Bennet, R Srinath, D Abirami, S Thilagavathi, S Soundarya, R Yuvarani

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 25–45

Research Article | 13-December-2017

A Cooperative Object Tracking System with Fuzzy-Based Adaptive Camera Selection

The intelligent environments, built upon many distributed sensors, are promising technology for ubiquitous interaction between robots and human beings. Especially, it is important to track target objects and get the positional information of them in such environments. This paper focuses on adapting camera selection for target tracking in multi-camera system. In this paper, a fuzzy automaton based camera selection method is introduced. In the proposed method, the camera selection decision is

Kazuyuki Morioka, Szilveszter Kovacs, Joo-Ho Lee, Peter Korondi

International Journal on Smart Sensing and Intelligent Systems, Volume 3 , ISSUE 3, 338–358

Research Article | 01-June-2011

BAYESIAN MULTIPLE PERSON TRACKING USING PROBABILITY HYPOTHESIS DENSITY SMOOTHING

We presents a PHD filtering approach to estimate the state of an unknown number of persons in a video sequence. Persons are represented by moving blobs, which are tracked across different frames using a first-order moment approximation to the posterior density. The PHD filter is a good alternative to standard multi-target tracking algorithms, since overrides making explicit associations between measurements and persons locations. The recursive method has linear complexity in the number of

S. Hernandez, M. Frean

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 2, 285–312

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