• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.923-930
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• 2002

This study aims at developing dialog system to improve the quality of life of the elderly with a dementia. The proposed system mainly consists of three modules including speech recognition, automatic search of the time-sorted dialog database, and agreeable responses with the recorded voices of caregivers. For the first step, the dialog that dementia patients often utter at a nursing home is first investigated. Next, the system is organized to recognize the utterances in order to meet their requests or demands. The system is then responded with recorded voices of professional caregivers. For evaluation of the system, the comparison study was carried out when the system was introduced or not, respectively. The occupational therapists then evaluated a male subjects reaction to the system by photographing his behaviors. The evaluation results showed that the dialog system was more responsive in catering to the needs of dementia patient than professional caregivers. Moreover, the proposed system led the patient to talk more than caregivers did in mutual communication.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.685-697
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• 2020

Immersive media videos, such as panorama and 360-degree videos, must provide a sense of realism as if the user visited the space in the video, so they should be able to represent the reality of the real world. However, in panorama and 360-degree videos, objects appear to overlap or disappear due to parallax between cameras, and such parallax distortion may interfere with immersion of the user's content. Accordingly, although many video stitching algorithms have been proposed to overcome parallax distortion, parallax distortion still occurs due to the low performance of the Object detection module and limitations of the Seam generation method. Therefore, this paper analyzes the limitations of the existing video stitching technology and proposes a method for detecting and correcting parallax distortion of video stitching using the LDPM (Local Differential Pixel Mean) image evaluation method that overcomes the limitations of the video stitching technique.

• 한국지형공간정보학회:학술대회논문집
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• 2002.03a
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• pp.145-149
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• 2002

CORONA는 미국이 1960년에서 1972년까지 냉전시대 관심지역에 대한 첩보영상을 취득하기 위하여 운영한 영상취득시스템으로 1995년 일반에 자료가 공개됨에 따라 과거의 고해상도 영상자료를 이용할 수 있는 길이 열리게 되었다. 그러나 현재까지 CORONA 영상처리를 위한 모듈을 제공하는 원격탐측 소프트웨어가 개발되어 있지 않기 때문에 CORONA 영상을 이용하여 수치표고모형이나 정사영상을 제작하기 위해서는 적절한 모델링 방법이 필요하다. CORONA 영상은 파노라마 영상으로 필름 가장자리로 갈수록 왜곡이 많이 생기며 사진기 지표가 없고 위성의 궤도와 위치, 자세, 속도, IMC(Image Motion Compensation)에 대한 자세한 자료를 제공하지 않는 문제점이 있다. 따라서 본 논문에서는 지형복원을 위하여 지상기준점을 이용하는 2가지 모델링 방법을 이용하였다. 첫 번째는 파노라마 왜곡과 촬영 비행체 이동에 의한 왜곡, IMC에 의한 왜곡을 보정하는 모형식을 구성하여 이용하였으며, 두 번째는 위성과 센서에 대한 정보를 필요로 하지 않는 다항식비례모형(RFM; Rational Function Model)을 이용하였다. 대상지역은 서울지역의 입체영상으로 대략 $33km{\times}26km$ 지역이다. 영상은 지상해상도 약 2.7m로 스캐닝하였고 1:1000 수치지도를 통해 20개의 기준점과 36개의 검사점을 관측하였다. 검사점의 위치정확도를 평가해 본 결과 첫 번째 방법은 수평방향으로 평균 3.9m(X), 2.8m(Y)의 오차를 보였으며 표고의 경우 4.2m의 오차를 보여주었다. 두 번째 방법은 수평방향으로 평균 3.2m(X), 2.8m(Y)의 오차를 보였으며 표고의 경우 5.5m의 오차를 보여주었다. 지형복원 정확도를 검증하기 위하여 첫 번째 방법을 이용하여 대상지역 중 일부인 서울 남산지역에 대해 정사영상과 10m간격의 DEM을 제작하였으며 1:1000 수치지도를 통해 제작된 DEM과 비교한 결과 총 43990개 격자점의 표고 차이는 평균 5.98m였다.

• Journal of Biomedical Engineering Research
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• v.23 no.6
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• pp.459-465
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• 2002

The goat of the present research is to improve the quality of life of both the elderly patients with dementia and their caregivers. For this Purpose, we developed a communication aid system that is consisted of three modules such as speech recognition engine, graphical agent. and database classified by a nursing schedule. The system was evaluated in an actual environment of nursing facility by introducing the system to an older mail patient with dementia. The comparison study was then carried out with and without system, respectively. The occupational therapists then evaluated subject"s reaction to the system by photographing his behaviors. The evaluation results revealed that the proposed system was more responsive in catering to needs of subject than professional caregivers. Moreover we could see that the frequency of causing the utterances of subject increased by introducing the system.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.105-116
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• 1996

This study is based upon the thermal modeling, analysis and operational results of KITSAT-1 and KITSAT-2 microsatellites launched on August 11, 1992 and Septermber 26, 1993, respectively. As KITSAT-1/2 was designed to be launched as an auxiliary payload of ARIANE launcher, the constraints on volume, power consumption, and mass were required to adopt passive thermal control method controlling absorptivity, emissivity, and conductivities among adjacent modules. The main of KITSAT was to take Earth images using CCD cameras positioned at the bottom of spacecraft, in which the cameras were always pointing to the center of Earth. This study is concerned with orbital analysis, thermal modeling, simulation results, and its verification by utilizing in-orbit telemetry data of KITSAT-2. The results of telemetry analysis show that the thermal modeling is matched to actual temperature data within 10 degrees of error range in average.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.461-467
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• 2019

As the convergence solutions become more common, the use of Arduino and Raspberry Pi boards has been increasing. These control boards has to be executed under power blackout. In this environment, we take advantage of solar power system to overcome the power out. In this paper, we poposed a effficient power control strategy. Our experimental device is a DSLR shooting device executed based a predesigned interval time. The control module of our experimental device is the compound system of Raspberry Pi and Arduino boards. Arduino board send the force signals to wake up Raspberry Pi. We developed a new control strategy algorithm for the efficient use of solar power energy. In this paper, we mesured the efficiency of solar enery consuming of our system. We programmed a control system to send DSLR shooting signals. In experimentals, we ensured a stable consuming of electricity during 10 days. In the end, it was found that the consumption power of the Raspberry was reduced by about 81% when the Aduino was combined to save power.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.14-25
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• 2021

Change detection, which finds changes in remote sensing images of the same location captured at different times, is very important because it is used in various applications. However, registration errors, building displacement errors, and shadow errors cause false positives. To solve these problems, we propose a novle deep convolutional network called CADNet (Change Attention Dense Siamese Network). CADNet uses FPN (Feature Pyramid Network) to detect multi-scale changes, applies a Change Attention Module that attends to the changes, and uses DenseNet as a feature extractor to use feature maps that contain both low-level and high-level features for change detection. CADNet performance measured from the Precision, Recall, F1 side is 98.44%, 98.47%, 98.46% for WHU datasets and 90.72%, 91.89%, 91.30% for LEVIR-CD datasets. The results of this experiment show that CADNet can offer better performance than any other traditional change detection method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.249-256
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• 2022

In the case of Drone Photogrammetry, the "pixel to point tool" module of Metashape, Pix4D Mapper, ContextCapture, and Global MapperGIS, which is a simple software, are widely used. Each SW has its own logic for the analysis of aerial triangulation, but from the user's point of view, it is necessary to select a SW by comparative analysis of the coordinate values of geospatial information for the result. Taking aerial photos for drone photogrammetry, surveying GCP reference points through VRS-GPS Survey, processing the acquired basic data using each SW to construct ortho image and DSM, and GCPSurvey performance and acquisition from each SW The coordinates (X,Y) of the center point of the GCP target on the Ortho-Image and the height value (EL) of the GCP point by DSM were compared. According to the "Public Surveying Work Regulations", the results of each SW are all within the margin of error. It turned out that there is no problem with the regulations no matter which SW is included within the scope.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.185-193
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• 2023

As many different over-the-top (OTT) services become ubiquitous, demands for high-quality content are increasing. However, high dynamic range (HDR) contents, which can provide more realistic scenes, are still insufficient. In this regard, we propose a new HDR video reconstruction technique using multi-exposure low dynamic range (LDR) videos. First, we align a reference and its neighboring frames to compensate for motions between them. In the alignment stage, we perform content-based alignment to improve accuracy, and we also present a high-resolution (HR) module to enhance details. Then, we merge the aligned features to generate a final HDR frame. Experimental results demonstrate that our method outperforms existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.535-538
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• 2022

For Plug & Play of IoT devices, we develop a module that recognizes the type of USB, which is a typical wired interface of IoT devices, through image recognition. In order to drive an IoT device, a driver for communication and device hardware is required. The wired interface for connecting to the IoT device is recognized by using the image obtained through the camera of smartphone shooting to recognize the corresponding communication interface. For USB, which is a most popular wired interface, types of USB are classified through artificial neural network-based machine learning. In order to secure sufficient data set of artificial neural networks, USB images are collected through the Internet, and additional image data sets are secured through image processing. In addition to the convolution neural networks, recognizers are implemented with various deep artificial neural networks, and their performance is compared and evaluated.