• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• 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%.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.444-448
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• 2008

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2:image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.451-465
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• 2017

This paper presents a novel discriminative visual tracking algorithm with an adaptive incremental extreme learning machine. The parameters for an adaptive incremental extreme learning machine are initialized at the first frame with a target that is manually assigned. At each frame, the training samples are collected and random Haar-like features are extracted. The proposed tracker updates the overall output weights for each frame, and the updated tracker is used to estimate the new location of the target in the next frame. The adaptive learning rate for the update of the overall output weights is estimated by using the confidence of the predicted target location at the current frame. Our experimental results indicate that the proposed tracker can manage various difficulties and can achieve better performance than other state-of-the-art trackers.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.330-332
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• 2006

In this paper, sun tracking system using Sun position sensor is proposed, the sun tracking system designed as which raises the efficiency of solar power generation. It design the structure being simple and it develops the system which is economical efficiency. It develops the hazard technique such as location tracking method of the sun which uses the sensor and to use the motor solar cell module movement. The Sun tracking system makes the drive in order to do with one axis and to use the sensor and to know in order to put out, the location of the sun and it makes. To make the solar location tracking sensor where the structure is simple it used two solar cells.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.296-299
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• 2004

KARI precision attitude determination system has been developed for high accurate geo-coding of KOMPSAT-2 image. Sensor data from two star trackers and a IRU are used as measurement and dynamic data. Sensor data from star tracker are composed of QUEST and unit vector filter. Filter algorithms consists of extended Kalman filter, unscented Kalman filter, and least square batch filter. The type of sensor data and filter algorithm can be chosen by user options. Estimated parameters are Euler angle from 12000 frame to optical bench frame, gyro drift rate bias, gyro scale factor, misalignment angle of star tracker coordinate frame with respect to optical bench frame, and misalignment angle of gyro coordinate frame with respect to optical bench frame. In particular, ground control point data can be applied for estimating misalignment angle of star tracker coordinate frame. Through the simulation, KPADS is able to satisfy the KOMPSAT-2 mission requirement in which geo-location accuracy of image is 80 m (CE90) without ground control point.

• Aerospace Engineering and Technology
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• v.4 no.1
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• pp.114-121
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• 2005

다목적실용위성 2호 영상의 geo-location 정밀도 80 m (CE90) 요구사항을 만족시키기 위하여, 1개의 IRU 와 2개의 star tracker 들로부터 획득되는 데이터를 이용하여 지상에서 후처리 추정 과정을 거쳐 위성의 자세를 결정하는 정밀자세결정 시스템이 개발되었다. 정밀자세결정 시스템의 정밀도를 극대화하기 위해서는 우주 공간의 극심한 열적 환경으로 인해 발생하는 star tracker 정렬 오차를 효율적으로 보정하여야 한다. 정밀한 정렬 오차의 보정을 위해서는 영상 내에 촬영된 지상의 ground control point 데이터를 이용하여야 하는데, 현실적으로 한반도 모든 지역에 대해 ground control point 를 확보할 수 없다. 현재 항공우주연구원이 확보하고 있거나 이후 확보할 예정에 있는 고해상도 영상을 위한 ground control point 들은 대전지역에 국한될 예정이다. 이와 같은 상황에서 정밀자세결정 시스템의 성능을 높이기 위한 최적의 시스템 운용 개념을 본 연구에서 제시하였으며, 시뮬레이션을 통해 그 타당성을 분석하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1244-1251
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• 2003

In the paper, we develop the ‘Navigation Mechanism’ that can present the 3D space and trace the location in the user's viewpoint. Especially, using this mechanism, VRML tools are used to develop the virtual reality space in the internet. These mechanism can effectively represent the 3D virtual reality space and apply the many 3D related parts like architefure, education, entertainment and so on.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.740-745
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• 2023

This study proposes the development of an antenna tracker system using a satellite system to stabilize the communication status of drones and extend the communication distance. The location information of the drone and the ground station was used to maximize communication gain in the general fixed antenna method between the ground station and the drone. We developed a tracker system that can automatically and continuously aim the ground station's antenna at the drone. It is expected that the use of antenna trackers will improve the stabilization of communication conditions and expand the communication distance, thereby leading to the advancement of the drone industry.

• 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.