As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.
The flood prevention capacity of drainage facilities in urban areas has weakened because of the increase in impervious surface areas downtown owing to rapid urbanization as well as localized heavy rains caused by climate change. Detention can be installed in trunk sewers and linked to existing drainage facilities for the efficient drainage of runoff in various urban areas with increasing stormwater discharge and changing runoff patterns. In this study, the concept of detention in trunk sewers, which are storage facilities linked to existing sewer pipes, was applied. By selecting a virtual watershed with a different watershed shape, the relationship between the characteristic factors of detention in the trunk sewer and the design parameters was analyzed. The effect of reducing stormwater runoff according to the installation location and capacity of the reservoir was examined. The relationship between the installation location and the capacity of the detention trunk sewer in the Dowon district of the city of Yeosu, South Korea was verified. The effects of the existing water runoff reduction facility and the detention trunk sewer were also compared and analyzed. As a result of analyzing the effects of reducing internal inundation, it was found that the inundation area decreased by approximately 66.5% depending on the installation location of the detention trunk sewer. The detention trunk sewer proposed in this paper could effectively reduce internal inundation in urban areas.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.13
no.6
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pp.496-502
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2020
The electronic attendance management system is being introduced and operated on a pilot basis by some universities and educational institutions. However, most of the related systems have installed and operated the existing barcode and magnetic card systems. Classroom attendance is managed by introducing RF cards, but it causes problems such as recognition distance (less than 5cm) and the need for a check process in which students have to read the card each time with a reader for attendance. Also, it is not possible to respond in real time to the situation of midterm (early leave, absence from the second lecture time, etc.) because it is used in the lecture time of one subject with the record checked once. In order to solve these problems, the various mobile attendance systems proposed to solve these problems are also unable to fundamentally solve problems such as interim attendance and proxy attendance because they check attendance using only the application of a smartphone. In this paper, we use geofencing technology, which is a positioning-based technology that detects the entry and exit of people, objects, etc. in areas separated by virtual boundaries. The proposed system solves the problem of intermediate attendance and alternate attendance by setting the student to automatically record the access record when entering and leaving the classroom set as a geofence with a smartphone. In addition, it also provides a function to prevent unintentional mistakes that occur through the smartphone by limiting some of the functions of the smartphone such as silence, vibration, and Internet use when entering the classroom.
Lee, Ghang Shin;Lee, Dong Min;Hwang, Soon Cheon;Kwon, Wan Taeg
The Journal of The Korea Institute of Intelligent Transport Systems
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v.20
no.6
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pp.117-132
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2021
Due to the terrain in Korea, there are many road sections passing through mountainous areas. During the winter, there is a higher risk of traffic accidents, due to black ice caused by the lack of sunlight. Despite domestic road freezing safety measures, accidents caused by road freezing results in severe traffic accidents. Under these considerations, this study analyzed whether traffic safety signs that change in response to the external temperature help drivers recognize frozen road segments. The study was conducted through analysis of the effect of the signs on a driver's perspective. For the signs under development, out of the signs designed by experts, the sign design which received the highest visibility and effectiveness evaluation ratings from the general public was selected. The sign was implemented through Virtual Reality (VR) and installed on the right side of the road to analyze the effect on gazing and driving behavior. As a result of analyzing the driver's driving behavior, a speed reduction of about 7km/h or more was found in the sign section. Therefore, It was found that the existence of the sign had a strong relationship with the rate of the drivers' speed reduction.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.5
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pp.334-342
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2021
In Korea, the training is performed through independent environments without interoperability among L-V-C systems. In the L system, training for large units is limited due to civil complaints at the training grounds and road restrictions. The V system is insufficient in training related to tactical training, and the C system lacks practicality due to a lack of combat friction elements. To achieve synchronicity and integration training between upper and lower units, it is necessary to establish a system to ensure integrated training for each unit by interoperating the currently operating L, V, and C systems. The interoperability between the C-C system supports Korea-US Combined Exercise. On the other hand, the actual development of the training system through the interoperability of L, V, and C has not been made. Although efforts are being made to establish the L, V, and C system centering on the Army, the joint composite battlefield and LVC integrated architecture technology are not yet secured. Therefore, this paper proposes a new plan for the future training system by designing and implementing the LVC integrated architecture technology, which is the core technology that can build the L-V-C interoperability training system. In conclusion, a division-level L-V-C interoperability training system can be established in the future by securing the LVC integrated architecture technology.
The railway is widely used to transport passengers and freight due to its punctuality and large transport capacity. The recent remarkable development in construction technology enables various subsea railway tunnels for continent-continent or continent-island connectivity. In Korea, design and construction experience is primarily based on the successful completion of the Boryeong subsea tunnel (2021) and the Gadeok subsea tunnel (2010). However, frequent earthquakes with diverse magnitudes, globally induced and continuously increased the awareness of seismic risks and the frequency of domestic earthquakes. The effect of an earthquake on the subsea tunnel is very complicated. However, ground conditions and seismic waves are considered the main factors. This study simulated four ground types of 3-dimensional numerical models, such as soil, rock, composite, and fractured zone, to analyze the effect of ground type and seismic wave. A virtual subsea railway shield tunnel considering external water pressure was modeled. Further, three different seismic waves with long-term, short-term, and both periods were studied. The dynamic analyses by finite difference method were performed to investigate the displacement and stress characteristics. Consequently, the long-term period wave exhibited a predominant lateral displacement response in soil and the short-term period wave in rock. The artificial wave, which had both periodic characteristics, demonstrated predominant in the fractured zone. The effect of an earthquake is more noticeable in the stress of the tunnel segment than in displacement because of confining effect of ground and structural elements in the shield tunnel.
Journal of the Korea Society of Computer and Information
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v.27
no.10
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pp.185-193
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2022
This study attempted to compare and analyze the commercially available multi-use patterns to develop mask patterns suitable for the face types of adult women. Through this, it was intended to provide necessary data to mask pattern development and products. As a results of comparing the dimensions and shapes of commercial multi-use mask patterns, there was a significant difference in dimensions even though it was a L-size mask manufactured for adults. As a result of the appearance evaluation of the virtual outfit, there were significant differences by design in the vertical of the center front line, the cover and space of the mask, the height of the nose, and the lower part of the mask. The side also showed significant differences in the covering of the side of the face, the space of the side, and the width and length of the string. As a result of the appearance evaluation, Mask 4 received the best evaluation. The shape of the mask pattern had a large dart in the lower part of the nose so that it can cover the three-dimensional shape of the face, but there was a difference in the degree and angle of the curve depending on the mask. Although the upper part of the mask, the lower part of the mask, and the cheek part are in close contact, the evaluation of the mask pattern, which has room in the nose and mouth, was high. It is thought that the mask pattern should be set according to the upper length, lower length, and nose height of the mask through analysis of the face shape and dimensions.
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 Korean Society of Industrial and Systems Engineering
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v.45
no.2
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pp.48-55
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2022
The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.
With the popularity and the advanced graphics hardware technology of mobile devices, various mobile applications that help children with physical activities have been studied. This paper presents SandUp, a mobile application that guides the play of building sand castles using artificial intelligence and augmented reality(AR) technology. In the process of building the sandcastle, children can interactively explore the target virtual sandcastle through the smartphone display using AR technology. In addition, to help children complete the sandcastle, SandUp informs the sand shape and task required step by step and provides visual and auditory feedback while recognizing progress in real-time using the phone's camera and deep learning classification. We prototyped our SandUp app using Flutter and TensorFlow Lite. To evaluate the usability and effectiveness of the proposed SandUp, we conducted a questionnaire survey on 50 adults and a user study on 20 children aged 4~7 years. The survey results showed that SandUp effectively helps build the sandcastle with proper interactive guidance. Based on the results from the user study on children and feedback from their parents, we also derived usability issues that can be further improved and suggested future research directions.
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