• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.84-86
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• 2001

A new navigation method is developed and implemented for mobile robot. The mobile robot navigation problem has traditionally been decomposed into the path planning and path following. Unlike tracking-based system, which minimize intercept time and moved mobile robot distance for optimal rendezvous point selection. To research of random moving object uses algorithm of Adaptive Control using Auto-regressive Model. A fine motion tracking object's trajectory is predicted of Auto-regressive Algorithm. Thus, the mobile robot can travel faster than the target wi thin the robot's workspace. The can select optimal rendezvous point of various intercept time.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.2
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• pp.48-55
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• 2010

This paper proposes a realtime tracking algorithm of mobile object in indoor or outdoor environment. For this purpose the proposed system selects location data closer to mobile objects in real time using Triangulation method and DCM (Database Correlation Method). Also, this system utilizes the adjusted location data selected by using Kalman filter to improve the location accuracy of transfer object. Be studied in existing the Kalman filter have unstable location data until its settlement because of it extracts current values by using the past the information. However, proposed location tracking system don't apply existent Kalman filter to this system and it permits precisional tracking location by using more effective methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.191-196
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• 2006

This paper presents the moving object tracking method using vision system. In order to track object in real time, the image of moving object have to be located the origin of the image coordinate axes. Accordingly, Fuzzy Control System is investigated for tracking the moving object, which control the camera module with Pan/Tilt mechanism. Hereafter, so the this system is applied to mobile robot, we design and implement image processing board for vision system. Also fuzzy controller is implemented to the StrongArm board. Finally, the proposed fuzzy controller is useful for the real-time moving object tracking system by experiment.

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.291-297
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• 2018

In this paper, we present an automatic image object tracking system for Studio cameras on the stage. For object tracking, we use the OpenCV-based Python program using PC, Raspberry Pi 3 and mobile devices. There are many methods of image object tracking such as mean-shift, CAMshift (Continuously Adaptive Mean shift), background modelling using GMM(Gaussian mixture model), template based detection using SURF(Speeded up robust features), CMT(Consensus-based Matching and Tracking) and TLD methods. CAMshift algorithm is very efficient for real-time tracking because of its fast and robust performance. However, in this paper, we implement an image object tracking system for studio cameras based CMT algorithm. This is an optimal image tracking method because of combination of static and adaptive correspondences. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the stage in real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.347-354
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• 2004

The provision of location tracking for mobile agents is designed to deliver a message to a moving object in a network. Most tracking methods exploit relay stations that hold location information to forward messages to a target mobile agent. In this paper, we propose an efficient location tracking method for mobile agents using the domain-based proxy as a relay station. Mobile agents can reduce the length of their migration paths by visiting hosts in the same domain first, rather than selecting hosts randomly. The proposed method exploits the domain-based moving patterns of mobile agents and minimizes registration and message delivery costs. Since the long proxy chain can contribute to the high message delivery cost, we also propose a compressing method to reduce the message delivery cost.

• Journal of the Semiconductor & Display Technology
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• v.17 no.3
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• pp.113-116
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• 2018

This paper proposes a mobile image search system which uses a sensor information of smart phone, and enables running in a variety of environments, which is implemented on Android platform. The implemented system deals with a new image descriptor using combination of the visual feature (CEDD) with EXIF attributes in the target of JPEG image, and image matching scheme, which is optimized to the mobile platform. Experimental result shows that the proposed method exhibited a significant improved searching results of around 80% in precision in the large image database. Considering the performance such as processing time and precision, we think that the proposed method can be used in other application field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1537-1545
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• 2016

In real time video sequence, object segmentation and tracking method are actively applied in various application tasks, such as surveillance system, mobile robots, augmented reality. This paper propose a robust object tracking method. The background models are constructed by learning the initial part of each video sequences. After that, the moving objects are detected via object segmentation by using background subtraction method. The region of detected objects are continuously tracked by using the HSV color histogram with particle filter. The proposed segmentation method is superior to average background model in term of moving object detection. In addition, the proposed tracking method provide a continuous tracking result even in the case that multiple objects are existed with similar color, and severe occlusion are occurred with multiple objects. The experiment results provided with 85.9 % of average object overlapping rate and 96.3% of average object tracking rate using two video sequences.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.71-76
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• 2019

In this paper, we propose a simple one-click marketing solution for mobile devices which can advertise a product which is embedded in a mobile video while watching the video on a smartphone. If a specific product of interest appears in the video to the user, one can simply click on the product in the video and a pop-up window with information about the product is proposed. The implementation of the system is expected to enable users to gain real-time information about the product while watching the video without having to search for the product again after watching the movie, and thereby facilitating more mobile commerce. We use a two-fold system to prevent the failure of tracking which often occurs on a single online tracking system, so that the user cannot always get the commercial product information.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.3-41
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• 2002

Motion estimation using Full-Search(FS) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data because these schemes suffer the heavy computational load. When the image size of moving object is changed in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object may decline with these methods because of the shortage of active handling. In this paper, the variable-representative block that can reduce a lot of data computations, is defined and optimized by changing the size of representative block accor...