• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.176-187
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• 1996

This paper deals with the accurate estimation of 3- D pose (position and orientation) of a moving object with reference to the world frame (or robot base frame), based on a sequence of stereo images taken by cameras mounted on the end - effector of a robot manipulator. This work is an extension of the previous work[1]. Emphasis is given to the 3-D pose estimation relative to the world (or robot base) frame under the presence of not only the measurement noise in 2 - D images[ 1] but also the camera position errors due to the random noise involved in joint angles of a robot manipulator. To this end, a new set of discrete linear Kalman filter equations is derived, based on the following: 1) the orientation error of the object frame due to measurement noise in 2 - D images is modeled with reference to the camera frame by analyzing the noise propagation through 3- D reconstruction; 2) an extended Jacobian matrix is formulated by combining the result of 1) and the orientation error of the end-effector frame due to joint angle errors through robot differential kinematics; and 3) the rotational motion of an object, which is nonlinear in nature, is linearized based on quaternions. Motion parameters are computed from the estimated quaternions based on the iterated least-squares method. Simulation results show the significant reduction of estimation errors and also demonstrate an accurate convergence of the actual motion parameters to the true values.

• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.1-10
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• 2015

One way to create a visually immersive environment is to utilize a front projection system. Especially, when enough space is not available behind the screen, it becomes difficult to install a back projection system, making the front projection an appropriate choice. A drawback associated with the front projection is, however, the interference of shadow. The shadow can be cast on the screen when the user is located between the screen and the projector. This shadow can negatively affect the user experience and reduce the sense of immersion by removing important information. There have been various attempts to eliminating shadows cast on the screen by using multiple projectors that compensate for each other with missing information. There is trade-off between calculataion time and desired accuracy in this mutual compensation. Accurate estimation of the shadow usually requires heavy computation while simple approaches suffer from inclusion of non-shadow regions in the result. We propose a novel approach to removing shadows created in the front projection system using the skeleton data obtained from a depth camera. The skeleton data helps accurately extract the shape of the shadow that the user cast without requiring much computation. Our method also utilizes a distance field to remove the afterimage of shadow that may occur when the user moves. We verify the effectiveness of our system by performing various experiments in an interactive environment created by a front projection system.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.4
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• pp.344-351
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• 2009

Purpose: Optical imaging is providing great advance and improvement in genetic and molecular imaging of animals and humans. Optical imaging system consists of optical imaging devices, which carry out major function for monitoring, tracing, and imaging in most of molecular in-vivo researches. In bio-luminescent imaging, small animals containing luciferase gene locally irradiate light, and emitted photons transmitted through skin of the small animals are imaged by using a high sensitive charged coupled device (CCD) camera. In this paper, we introduced optical imaging system for the image acquisition of bio-luminescent signals emitted from small animals. Materials and Methods: In the system, Nikon lens and four LED light sources were mounted at the inside of a dark box. A cooled CCD camera equipped with a control module was used. Results: We tested the performance of the optical imaging system using effendorf tube and light emitting bacteria which injected intravenously into CT26 tumor bearing nude mouse. The performance of implemented optical imaging system for bio-luminescence imaging was demonstrated and the feasibility of the system in small animal imaging application was proved. Conclusion: We anticipate this system could be a useful tool for the molecular imaging of small animals adaptable for various experimental conditions in future.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.1-6
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• 2014

In this study, we propose optimized RBFNNs based on night vision face recognition simulator with the aid of $(2D)^2$ PCA algorithm. It is difficult to obtain the night image for performing face recognition due to low brightness in case of image acquired through CCD camera at night. For this reason, a night vision camera is used to get images at night. Ada-Boost algorithm is also used for the detection of face images on both face and non-face image area. And the minimization of distortion phenomenon of the images is carried out by using the histogram equalization. These high-dimensional images are reduced to low-dimensional images by using $(2D)^2$ PCA algorithm. Face recognition is performed through polynomial-based RBFNNs classifier, and the essential design parameters of the classifiers are optimized by means of Differential Evolution(DE). The performance evaluation of the optimized RBFNNs based on $(2D)^2$ PCA is carried out with the aid of night vision face recognition system and IC&CI Lab data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• Journal of Space Technology and Applications
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• v.1 no.2
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• pp.199-216
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• 2021

In 2020, the solar and space environment division at the Korea Space Science Society surveyed the status of data archives in solar physics, magnetosphere, and ionosphere/upper atmosphere in Korea to promote broader utilization of the data and research collaboration. The survey includes ground- and satellite-based instruments and developing models by research institutes and universities in Korea. Based on the survey results, this study reports the status of the ground-based instruments, data products in the ionosphere and upper atmosphere, and documentation of them. The ground-based instruments operated by the Korea Polar Research Institute and Korea Astronomy and Space Science Institute include ionosonde, Fabry-Perot interferometer in Arctic Dasan stations, Antarctic King Sejong/Jang Bogo stations, and an all-sky camera, VHF radar in Korea. We also provide information on total electron content and scintillation observations derived from the Global Navigation Satellite System (GNSS) station networks in Korea. All data are available via the webpage, FTP, or by request. Information on ionospheric data and models is available at http://ksss.or.kr. We hope that this report will increase data accessibility and encourage the research community to engage in the establishment of a new Space Science Data Ecosystem, which supports archiving, searching, analyzing, and sharing the data with diverse communities, including educators, industries, and the public as wells as the research scientist.

• Knowledge Management Research
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• v.23 no.2
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• pp.123-142
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• 2022

The non-face-to-face environment accelerated by COVID-19 has speeded up the dissemination of digital virtual ecosystems and metaverse. In order for the metaverse to be sustainable, digital twins that are compatible with the real world are key, and critical technology for that is AR (Augmented Reality). In this study, we examined research trends about AR, and will propose the directions for future AR research. We conducted LDA based topic modeling on 11,049 abstracts of published domestic and foreign AR related papers from 2009 to Mar 2022, and then looked into AR that was comprehensive research trends, comparison of domestic and foreign research trends, and research trends before and after the popularity of metaverse concepts. As a result, the topics of AR related research were deduced from 11 topics such as device, network communication, surgery, digital twin, education, serious game, camera/vision, color application, therapy, location accuracy, and interface design. After popularity of metaverse, 6 topics were deduced such as camera/vision, training, digital twin, surgical/surgical, interaction performance, and network communication. We will expect, through this study, to encourage active research on metaverse AR with convergent characteristics in multidisciplinary fields and contribute to giving useful implications to practitioners.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• Smart Media Journal
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• v.13 no.3
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• pp.18-26
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• 2024

Road surface monitoring is essential for maintaining road environment safety through managing risk factors like rutting and crack detection. Using autonomous driving-based UGVs with high-performance 2D laser sensors enables more precise measurements. However, the increased energy consumption of these sensors is limited by constrained battery capacity. In this paper, we propose a fusion sensor system for efficient surface monitoring with UGVs. The proposed system combines color information from cameras and depth information from line laser sensors to accurately detect surface displacement. Furthermore, a dynamic sampling algorithm is applied to control the scanning frequency of line laser sensors based on the detection status of monitoring targets using camera sensors, reducing unnecessary energy consumption. A power consumption model of the fusion sensor system analyzes its energy efficiency considering various crack distributions and sensor characteristics in different mission environments. Performance analysis demonstrates that setting the power consumption of the line laser sensor to twice that of the saving state when in the active state increases power consumption efficiency by 13.3% compared to fixed sampling under the condition of λ=10, µ=10.