Through photogrammetry techniques, what current researches can achieve at present is rough 3D mesh and color map of objects, rather than usable photo-realistic 3D assets. This research aims to propose a new method to create photo-realistic 3D assets that can be used in the field of visualization applications. The new method combines photogrammetry with computer graphics modeling. Through the description of the production process of three objects in the real world - "Bullet Box", "Gun" and "Metal Beverage Bottle," it introduces in details the concept, functions, operating skills and software packages used in the steps including the photograph object, white balance, reconstruction, cleanup reconstruction, retopology, UV unwrapping, projection, texture baking, De-Lighting and Create Material Maps. In order to increase the flexibility of the method, alternatives to the software packages are also recommended for each step. In this research, 3D assets are produced that are accurate in shape, correct in color, easy to render and can be physically interacted with dynamic lighting in texture. The new method can obtain more realistic visual effects at a faster speed. It does not require large-scale teams, expensive equipment and software packages, therefore it is suitable for small studios and independent artists and educational institutions.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.40
no.3
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pp.187-193
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2022
In the Yeongdong region of Gangwon-do, coastal areas are important resources in terms of cultural, social and economic aspects. However, the coast of Gangwon-do is experiencing severe erosion, and it is concerned that its adverse effects will gradually increase. In this study, coastline changes of Yangyang and Gangneung in Gangwon-do were tracked and analyzed over a long period of time. In order to build time series image data, aerial photos from the 1940s to the present were mainly used, and data from CORONA satellite, which operated from the 1960s to the early 1970s, were collected and used together. Using 51cm resolution ortho image and 2m resolution Digital Elevation Model(DEM) as reference, ground control points were selected to perform geometric correction on the aerial photos and CORONA images. Subsequently, Canny edge detector applied to these images to extract the coastlines. As a result of analyzing the extracted and vectorized coastlines by overlaying them in chronological order, erosion and deposition occurring around the artificial structures and on the nearby beaches were observed. In this study, the effect of seasonal variation, tide, and various coastal management including the beach filling were not considered. Because coastal erosion is greatly affected by geographic factors, each local government must find its own solution. Continuous research and local data accumulation are required.
The possibility of metaverse system to be a catalyst for hyper-connected society will be dependent on the speed of connected technological development and its social utilization in the same manner as AI technology. Putting these technical realization processes in brackets, this paper focus on some philosophical-political issues in connection with cognitive-ecological changes in the future cinema which will be influenced by the complexive techno-socio couples of accelerated development of metaverse system. Generally speaking, essence of metaverse system seems to be the degree of immersion by technical accuracy, but is not true. In perspective of cognitive-ecology, flow degree of a picture or photograph is relied not on 'accuracy of representation' but on its message's contextual link-up. In this aspect, real potentiality of metaverse system shall be understood in the context of cognitive-ecological changes of human brain's multi-intelligence networking abilities(intersection of augmentation-simulation and outside-inside) which will be activated in the new structure of natural-social-technological coupling of metaverse system. These cognitive-ecological potentialities have been partially actualized in the cinematic process of tripod mimesis for the longest time, [real contradiction/conflicts (Mimesis-1) -->fictional solutions of cinema (Mimesis-2) --> selective interpretation of spectator's wish fulfillment (Mimesis-3) --> real change (Mimesis-1')]. Therefore metaverse's real potentiality must be considered to be dependent on the possibility of deepening and extending of cinematic circulation between real seperation/problems and ideal connection/solutions. In this context, advanced metaverse system can be compared as a modern technical version of ideal circulation of physics and metaphysics
An, Phil-Gyun;Eom, Seong-Jun;Kim, Yong-Gyun;Cho, Han-Sol;Kim, Sang-Bum
Journal of Korean Society of Rural Planning
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v.27
no.4
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pp.55-70
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2021
In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.
Kim, Kook-jin;Youn, Jae-pil;Yoon, Suk-joon;Kang, Ji-won;Kim, Kyung-shin;Shin, Dong-kyoo
Journal of Internet Computing and Services
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v.23
no.5
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pp.87-101
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2022
Cyber-attacks occur in the blink of an eye in cyberspace, and the damage is increasing all over the world. Therefore, it is necessary to develop a cyber common operational picture that can grasp the various assets belonging to the 3rd layer of cyberspace from various perspectives. By applying the method for grasping battlefield information used by the military, it is possible to achieve optimal cyberspace situational awareness. Therefore, in this study, the visualization screens necessary for the cyber common operational picture are identified and the criteria (response speed, user interface, object symbol, object size) are investigated. After that, the framework is designed by applying the identified and investigated items, and the visualization screens are implemented accordingly. Finally, among the criteria investigated by the visualization screen, an experiment is conducted on the response speed that cannot be recognized by a photograph. As a result, all the implemented visualization screens met the standard for response speed. Such research helps commanders and security officers to build a cyber common operational picture to prepare for cyber-attacks.
The study aims to provide an academic basis for the preservation and restoration of abandoned paddy wetland and the enhancement of its carbon accumulation function. First, the temporal change of the wetlands was analysed, and a typological classification system for wetlands was attempted with the goal of carbon reduction. The types of wetland were classified based on three variables: hydrological environment, vegetation, and carbon accumulation, with a special attention on the function of carbon accumulation. The types of abandoned paddy wetlands were classified into 12 categories based on hydrologic variables- either high or low levels of water inflow potential-, vegetation variables with either dominance of aquatic plants or terrestrial plants, and three carbon accumulation variables including organic matter production, soil organic carbon accumulation, and decomposition. It was found that the development period of abandoned paddy analyzed with aerial photographs provided by the National Geographic Information Institute happened between 2010 and 2015. In the case of the wetland in Daejeon 1 (DJMN01) farming stopped by 1990 and it appeared to be a similar structure to natural wetlands after 2010 . Over the past 40 years the abandoned paddy wetland changed to a high proportion of forests and agricultural lands. As time went by, such forests and agricultural lands tended to decrease rapidly and the lands were covered by artificial grass and other types of forests.
The dry unit weight of the soil can be obtained by measuring the weight of the oven dried soil. According to the Korean Industrial Standards (KS F), oven dried soil at 110±5℃ continuously increases in weight when exposed to air. However, there is no regulation on the weight measurement time of oven dried soil, making it difficult to accurately measure the dry weight. In this study, a method to easily determine the dry weight was presented through the analysis of the weight singularity that appears during weight measurement. The weight singularity represents the smallest value among the measured weights, and is the weight at which the effect of moisture absorption in the air of the sample is minimized. In the course of the experiment, a container was selected using a statistical analysis method, and a photograph of the soil samples were presented using an optical microscope. In addition, the temperature of the weight singularity was measured using a non-contact infrared thermometer. As a result of analyzing the weight singularity of six types of soil, including Jumunjin sand, Naeseong stream sand, Yecheon weathered granite soil, Jeju sand, Sabkha sand, and Ulleung sand, the weight singularity of oven dried sample appeared between 8 and 27 seconds after weight measurement, and the temperature ranged from 103.4 to 108.13℃. The weight decrease rate of the singularity was 0.0066 to 0.0085% depending on the soil samples.
International conference on construction engineering and project management
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2009.05a
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pp.30-31
/
2009
Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.
Journal of The Geomorphological Association of Korea
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v.17
no.4
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pp.71-83
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2010
In this study, the volume of shoreline retreat at sea-cliffs in the Taean peninsula(West Coast of Korea) was estimated and their erosion and seasonal landforms characteristics changes were investigated through multi-temporal aerial photographs and field survey. Based on the analysis of aerial photographs through ortho-correction, the results show that the length of shoreline and erosion area increase as erosion at sea-cliffs occurs in Pado-li and Dundu-li. To obtain the seasonal quantitative landforms changes and retreat of sea-cliffs, we marked top, middle, and bottom datum-points, from which the distance to the nearest bedrock was repeatedly measured. In these regions, the retreat of sea-cliffs gradually increases in spring to summer, but gradually decreases in autumn. In particular, the typhoon that has a great influence on the Korean peninsula in July to September in summer would drastically increase the retreat of sea-cliffs in comparison with other seasons. As the outcrop of sea-cliffs repeats freezing and thawing in winter, the retreat of sea-cliffs increases a little due to active mechanical weathering. To know the erosion and seasonal landforms changes of sea-cliffs, we took pictures of them in every month and then analyze their condition. The retreat of sea-cliffs was repeatedly occurred by the circulation of the erosion of sea-cliff base, landslides, the formation of slope sediment debris and their erosion, in that order.
Journal of the Institute of Convergence Signal Processing
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v.23
no.3
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pp.166-172
/
2022
In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.
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