• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1047-1055
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• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.795-800
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• 2008

The paper presents research for the established experiment environment of multi vehicle robot, localization algorithm that is based on vehicle control, and path tracking. The established experiment environment consists of ultrasonic positioning system, vehicle robot, server and wireless module. Ultrasonic positioning system measures positioning for using ultrasonic sensor and generates many errors because of the influence of environment such as a reflection of wall. For a solution of this fact, localization algorithm is proposed to determine a location using vehicle kinematics and selection of a reliable location data. And path tracking algorithm is proposed to apply localization algorithm and LOS, finally, that algorithms are verified via simulation and experimental

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.124-127
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• 1997

In this paper, we propose the new face detection and tracking angorithm in sequential images which have complex background. In order to apply face deteciton algorithm efficently, we convert the conventional RGB coordiantes into CIE coordonates and make the input images insensitive to luminace. And human face shapes and colors are learned using ueural network's backpropagation. For variable face size, we make mosaic size of input images vary and get the face location with various size through neural network. Besides, in sequential images, we suggest face motion tracking algorithm through image substraction processing and thresholding. At this time, for accurate face tracking, we use the face location of previous. image. Finally, we verify the real-time applicability of the proposed algorithm by the simple simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.248-249
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• 2022

In this paper, we propose a method for classifying and tracking objects based on information of multiple users obtained using RGB-D cameras. The 3D information and color information acquired through the RGB-D camera are acquired and information about each user is stored. We propose a user classification and location tracking algorithm in the entire image by calculating the similarity between users in the current frame and the previous frame through the information on the location and appearance of each user obtained from the entire image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.364-367
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• 2007

We combined CC2431(Chipcon, Norway), as the platform for the Indoor Location Tracking, which follows Zigbee/IEEE802.15.4 standards in RSSI (Received Signal Strength Indicator) and Base Station Node and then, embodied Indoor Location Tracking System. CC2431 is composed of the Reference Node that transfer its current position at the designated place and the Blind Node. The Blind node receives the current position(X and Y coordinates) of the Reference Node fields which are being contiguous and also, calculates its current position and transfers it to the Base Station Node. The base station node is used for receiving the current position of blind node and passing its data to the PC as a gateway. We can make sure where is the Blind Node not only from the out-of-the-way place of the server side but from the outside in a real-time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.708-717
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• 2017

Tracking of sound-location is widely used in various area such as intelligent CCTV, video conference and voice commander. In this paper we introduce the real-time sound-location tracking method for smart lecture system using TDoA(Time Difference of Arrival) with orthogonal microphone array on the ceiling. Through discussion on some models of TDoA detection, cross correlation method using linear microphone array is proposed. Orthogonal array with 5 microphone could detect omni direction of sound-location. For real-time detection we adopt the threshold of received energy for eliminating no-voice interval, signed cross correlation for reducing computational complexity. The detected azimuth angles are processed using median filter for lowering the angle deviation. The proposed system is implemented with high performance MCU of TMS320F379D and MEMs microphone module and shows the accuracy of 0.5 and 6.5 in degree for white noise and lectured voice, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.578-585
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• 2012

Location tracking system through GPS and Wi-Fi is available at no additional cost in an environment of IEEE 802.11-based wireless network. It is useful for many applications in outdoor environment. However, a previous systems used for general device to tag. It is unsuitable for power aware location tracking system because general devices is more expensive and non-optimized for tracking. The hand-off method of IEEE 802.11 standard is not enough considering power consumption. This thesis analyzes the previous location tracking systems and proposes power aware system. First, we designed and implemented tag to optimize location tracking. Next, we propose low-power hand-off method and low-power behavior model in implemented tag. The proposed hand-off method resolve power problem by using the location information and behavior model minimize power consumption of tag through power-saving mode and the concept of duty cycle. To evaluating proposed methods and system performance, we perform simulations and experiments in real environment. And then, we calculate tag's power consumption based on the actual measured current consumption of each operation. In a simulation result, the proposed behavior model and hand-off method reduced about 98%, 59% than the standard's hand-off and default behavior model.

• Journal of Advanced Navigation Technology
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• v.18 no.1
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• pp.90-94
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• 2014

This paper suggests the system that allows nearby firefighters to read about the transmission direction of a distress signal and track the location by RSSI of received distress signal which is transmitted wirelessly after sensing the distress signal of a firefighter using the Wireless Sensor Network(WSN) based on IEEE 802.15.4 and Received Signal Strength Indicator(RSSI) in the building. Also, It was confirmed that the location tracking using RSSI is possible because the difference between theoretical value and experimental value is little when experiment using the proposed system.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.411-418
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• 2017

During the intramedullary nailing procedure, surgeons feel difficulty in manipulation of the X-ray device to align it to axes of nailing holes and suffer from the large radiation exposure from the X-ray device. These problems are caused by the fact the surgeon cannot see the hole's location directly and should use the X-ray device to find the hole's location and direction. In this paper, we proposed the robotic guidance of the distal screwing using an optical tracking system. To track the location of the hole for the distal screwing, the reference marker is attached to the proximal end of an intramedullary nail. To guide the drill's direction robustly, the 6-degree-of-freedom robotic arm is used. The robotic arm is controlled so as to align the drill guiding tool attached the robotic arm with the obtained the hole's location. For the safety, the robot's linear and angular velocities are restricted to the predefined values. The experimental results using the artificial bones showed that the position error and the orientation error were 0.91 mm and $1.64^{\circ}$, respectively. The proposed method is simple and easy to implement, thus it is expected to be adopted easily while reducing the radiation exposure significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.119-133
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• 2009

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.