• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1066-1079
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• 2023

Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.336-344
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• 2012

As an important part of the Computer Vision, the object recognition and tracking function has infinite possibilities range from motion recognition to aerospace applications. One of methods to improve accuracy of the object recognition, are uses colors which have robustness of orientation, scale and occlusion. Computational cost for extracting features can be reduced by using color. Also, for fast object recognition, predicting the location of the object recognition in a smaller area is more effective than lowering accuracy of the algorithm. In this paper, we propose a method that uses SURF descriptors which applied with color model for improving recognition accuracy and combines with Kalman filter which is Motion estimation algorithm for fast object tracking. As a result, the proposed method classified objects which have same patterns with different colors and showed fast tracking results by performing recognition in ROI which estimates future motion of an object.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1529-1536
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• 2011

Recently, worldwide government policy is pursuing saving energy and preservation. add to this, the solar cells are getting the spotlight nonpolluting energy source, using a variety of products for solar cell. in this paper, we'll make solar tracking system for suitable of dynamic boat. we knew that general boats are using fixed solar cell, it's first time to use tracking system of solar cells for boats so it is hard to application. To solve this problem in this paper we use to a magnetic compass and GPS for suitable solar tracking system of dynamic movement and to analyze fixed and tracking solar system. frist. solar tracking device is designed two-axis control system. one-axis control system is taken a magnetic compass for making efficiency defence solar tracking sensor, two-axis control system apply GPS latitude and longitude data for SPA(Solar position algorithm) so we know the azimuth and altitude. it analyze data value of accuracy comparison from result. so the proposed algorithm confirm to have validity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1287-1300
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• 2018

Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.175-182
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• 1998

An advanced visual tracking and stable grasping algorithm for a moving object is proposed. The stable grasping points for a moving 2D polygonal object are obtained through the visual tracking system with the Kalman filter and image prediction technique. The accuracy and efficiency are improved more than any other prediction algorithms for the tracking of an object. In the processing of a visual tracking. the shape predictors construct the parameterized family and grasp planner find the grasping points of unknown object through the geometric properties of the parameterized family. This algorithm conducts a process of ‘stable grasping and real time tracking’.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.407-412
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• 2015

In model-based tracking, an accurate 3D model of a target object or scene is mostly assumed to be known or given in advance, but the accuracy of the model should be guaranteed for accurate pose estimation. In many application domains, on the other hand, end users are not highly distracted by tracking errors from certain levels of modeling errors. In this paper, we examine perceptual tracking errors, which are predominantly caused by modeling errors, on subjective evaluation and compare them to computational tracking errors. We also discuss the tolerance of modeling errors by analyzing their permissible ranges.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.349-359
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• 1998

A robot control scheme for specific application a line-tracking system is newly presented. To improve the performance of line-tracking, robot arm dynamics and torque constraints are incorporated into the control scheme. The tracking problem for the workpiece on a variable-speed conveyor is formulated as an optimal tracking problem with specific criteria. Dividing the conveyor speed into the nominal term and the perturbed term, a two-stage control strategy is employed to cope with the nonlinearity and uncertainty of the robot-conveyor system. Simulation results are given to verify good tracking performance with fast cycle time and high accuracy in a robotic workcell.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.344-358
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• 2019

Surveillance cameras have installed in many places because security and safety is becoming important in modern society. Through surveillance cameras installed, we can deal with troubles and prevent accidents. However, watching surveillance videos and judging the accidental situations is very labor-intensive. So now, the need for research to analyze surveillance videos is growing. This study proposes an algorithm to track multiple persons using SURF and background subtraction. While the SURF algorithm, as a person-tracking algorithm, is robust to scaling, rotating and different viewpoints, SURF makes tracking errors with sudden changes in videos. To resolve such tracking errors, we combined SURF with a background subtraction algorithm and showed that the proposed approach increased the tracking accuracy. In addition, the background subtraction algorithm can detect persons in videos, and SURF can initialize tracking targets with these detected persons, and thus the proposed algorithm can automatically detect the enter/exit of persons.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.153-156
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• 1996

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.73-77
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• 2002

The requirements for higher productivity call for high speed of the machine tool axes. Iron core type linear DC motor is growly accepted far a viable candidate of the high speed machine tool feed unit. LDM, however, has inherent disturbance force components: cogging and force ripple. These disturbance force directly affects tracking accuracy of the carrage and must be eliminated or reduced. Reducing motor ripple, this paper adapted the feed forward compensation method and neural network control. Experiments carried 7ut on the linear motor test setup show that this control methods is usable in order to reduce the motor ripple.