• Maxillofacial Plastic and Reconstructive Surgery
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• v.34 no.1
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• pp.41-52
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• 2012

Purpose: Triangulation is the process of determining the location of a point by measuring angles to it from known points at either end of a fixed baseline. This point can be fixed as the third point of a triangle with one known side and two known angles. The aim of this study was to find a clinically adaptable method for applying an optical tracking navigation system to orthognathic surgery and to estimate its accuracy of measuring the bone displacement by use of triangulation methods. Methods: In orthognathic surgery, the head position is not fixed as in neurosurgery, so that a head tracker is needed to establish the reference point on the head surface byusing an optical tracking system. However, the operation field is interfered by its bulkiness that makes its clinical use difficult. To solve this problem, we designed a method using an Aquaplast splinting material and a mini-screw in applying a head tracker on a patient's forehead. After that, we estimated the accuracy of measuring displacements of the ball marker by an optical tracking system with a conventional head tracker (Group A) and with a newly designed head tracker (Group B). Measured values of ball markers' displacements by each optical tracking system were compared with values obtained from fusion CT images for an estimation of accuracy. Results: The accuracy of the optical tracking system with a conventional head tracker (Group A) is not suitable for clinical usage. Measured and predictable errors are larger than 10 mm. The optical tracking system with a newly designed head tracker (Group B) shows 1.59 mm, 6.34 mm, and 9.52 mm errorsin threeclinical cases. Conclusion: Most errors were brought on mainly from a lack of reproducibility of the head tracker position. The accuracy of the optical tracking system with a newly designed head tracker can be a useful method in further orthognathic navigation surgery even though the average error is higher than 2.0 mm.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

• IE interfaces
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• v.25 no.1
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• pp.114-126
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• 2012

This study describes a real-time location monitoring system developed for efficient operation of workplace in plant equipment maker. This monitoring system can be applied for indoor and outdoor working environment respectively. By using the real-time tracking system based on RTLS, it is possible to track worker's movement and location of working object under indoor working environment. For outdoor working environment, the real-time monitoring system based on IDGPS is applied for work safety and balanced workload. A case study is provided to evaluate the performance of the real-time monitoring system.

• Journal of the Semiconductor & Display Technology
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• v.12 no.2
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• pp.85-91
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• 2013

In this paper, the parabolic antenna aims to the precise location of a moving ship or car that can be designed system using the gyro sensor. The parabolic antenna has controlled by stepping motor that is a lot of noise and slow response of speed. It has solved the problem which is noise and slow response using the BLDC motor. Also, in order to suppress the noise two-axis control and a separate encoder to the six degrees of freedom motion system was implemented in a precise location. Generally, the gyro sensor is not required to system that doesn't move the six degrees of freedom motion system. But the system will be applied to the moving such as ships or cars. Finally, we presented the position control algorithm at the sometimes controlled both gyro sensor and BLDC motor. This system was tracking that the location of the antenna to the desired angle and errors almost didn't happen when the system was moved 6 degrees of freedom.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.25-35
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• 2016

Since a sophisticated location determination technology (LDT) is necessary for accurate positioning in urban area environments, numerous studies related to the LDT using the RFID (Radio Frequency IDentification) technology have been implemented for real-time positioning and data transferring. However, there are still lots of unsolved questions especially regarding what to use as base stations and what are corresponding results under the intrinsic complexity of alignment and configuration of components used for the RFID positioning. This study proposes the street light fixtures as base stations where the RFID receivers will be embedded for the mobile tracking scheme. As street light fixtures are usually installed at a certain distance interval, they can be used as base stations for the RFID receiver installation. Using the principle of the single row triangle network, the RFID receiver organization is determined based on the experiments such as recognition distance measurement and tag position accuracy estimation at inside and outside of the single row triangle network. The results verify that the mobile tracking scheme which uses RFID-embedded street light fixtures, suggested and configured in this study, is effective for the real-time outdoor positioning.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.781-787
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• 2015

This paper proposes a hybrid visual servoing algorithm for the object tracking by a mobile robot with the stereo camera. The mobile robot with the stereo camera performs an object recognition and object tracking using the SIFT and CAMSHIFT algorithms for the hybrid visual servoing. The CAMSHIFT algorithm using stereo camera images has been used to obtain the three-dimensional position and orientation of the mobile robot. With the hybrid visual servoing, a stable balance control has been realized by a control system which calculates a desired angle of the center of gravity whose location depends on variations of link rotation angles of the manipulator. A PID controller algorithm has adopted in this research for the control of the manipulator since the algorithm is simple to design and it does not require unnecessary complex dynamics. To demonstrate the control performance of the hybrid visual servoing, real experiments are performed using the mobile manipulator system developed for this research.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.90-94
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• 2010

In this paper, we propose a vehicle tracking method that can be applied in the intelligent traffic information system. The proposed method mainly consists of two steps: overlap removal and background updating. In order to remove overlap, we detect the overlap based on the location of the vehicle from successive images. Background updating is to calculate a background using statistical analysis of successive images. We collected a set of test images from the traffic monitoring system and experimented. The experimental results show more than 96% of tracking accuracy.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3211-3218
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• 1997

This paper addresses an eye location algorithm which is essential process of human face tracking system for natural video-conferencing. In current video-conferencing systems, user's facial movements are restricted by fixed camera, therefore it is inconvenient to users. We Propose an eye location algorithm for automatic face tracking. Because, locations of other facial features guessed from locations of eye and scale of face in the image can be calculated using inter-ocular distance. Most previous feature extraction methods for face recognition system are approached under assumption that approximative face region or location of each facial feature is known. The proposed algorithm in this paper uses no prior information on the given image. It is not sensitive to backgrounds and lighting conditions. The proposed algorithm uses the valley representation as major information to locate eyes. The experiments have been performed for 213 frames of 17 people and show very encouraging results.