• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.621-629
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• 2011

According to the development of technologies for generating the 3D spatial information, the needs for producing and updating the precise 3D objects with LoD 4 level are increased. On the other hand, the needs for real-time updating of 2D digital maps are expanded, based on the execution of various GIS projects. These 2D informations can be extracted from precisely constructed 3D spatial information, to do this the feasibility studies on extraction of the 2D information from the 3D spatial information is needed. In this study, 3D objects are modeled using multi-oblique images, and the objects are stereo-plotted using digital airborne images, as well. Then the two data sets are compared and analyzed. The results show that the accuracy assessments fulfill the 1/1,000 digital map accuracy standard of regulations for photogrametric surveying of National Geographic Information Institute, but the shapes and the areas of building objects are different between two data sets because of the portrayal standards. Consequently, researchers can conclude that it is possible to generate the building layer of large scale topographic map using multi-oblique images, but additional researches is needed to resolve the problems on differences of the portrayal standards.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.613-616
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• 2004

Recently, in a field of cadastre, a computerization of cadastral map is in progress with great growth of GSIS field. Also, the needs for the integration of land and building information are widely increasing for integral-management and its application of various land related information. Through a revision of cadastral laws to replace the existing 2D-Cadastre with the 3D-Cadastre, a legal basis to register the position of buildings and facilities is prepared in the governmental or civil fields. This paper presented 3D-Cadastre theory that has been studied on Europe and surveyed building position directly with Totalstation at cadastral control point after choosing pilot test area, Also, the most efficient surveying method of registering building in a cadastral map is presented with comparing and analyzing building position after surveying digital orthophoto and digital map.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.35-49
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• 2021

In order to manage the underground spatial information in systematic and effective way, production of an integration underground spatial information map is essential process. The government has been making efforts to expand manage the production of 3D underground spatial integrated map. In recent the GPR is actively used for exploring underground facilities in non-exploring area and sinkhole. For achieving the research objectives presenting the accuracy of verification standard in underground spatial information surveying using GPR, the related legislation standard, the experiment resutls and international criteria have been analyzed. From this research it is found that the accuracy standard has been made by the related academic society(USA) and association(UK) in foreign counties. It is recommended that indicate the verification standard with number and percent together considering the characteristics of GPR.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.447-454
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• 2018

This paper proposes a depth image generation algorithm of stereo images using a deep learning model composed of a CNN (convolutional neural network). The proposed algorithm consists of a feature extraction unit which extracts the main features of each parallax image and a depth learning unit which learns the parallax information using extracted features. First, the feature extraction unit extracts a feature map for each parallax image through the Xception module and the ASPP(Atrous spatial pyramid pooling) module, which are composed of 2D CNN layers. Then, the feature map for each parallax is accumulated in 3D form according to the time difference and the depth image is estimated after passing through the depth learning unit for learning the depth estimation weight through 3D CNN. The proposed algorithm estimates the depth of object region more accurately than other algorithms.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.207-213
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• 2018

This paper investigates applicability of Microsoft $Kinect^{(R)}$, RGB-depth camera, to implement a 3D image and spatial information for sensing a target. The relationship between the image of the Kinect camera and the pixel coordinate system is formulated. The calibration of the camera provides the depth and RGB information of the target. The intrinsic parameters are calculated through a checker board experiment and focal length, principal point, and distortion coefficient are obtained. The extrinsic parameters regarding the relationship between the two Kinect cameras consist of rotational matrix and translational vector. The spatial images of 2D projection space are converted to a 3D images, resulting on spatial information on the basis of the depth and RGB information. The measurement is verified through comparison with the length and location of the 2D images of the target structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.364-380
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• 2016

The most popular approach in object classification is based on the bag of visual-words model, which has several fundamental problems that restricting the performance of this method, such as low time efficiency, the synonym and polysemy of visual words, and the lack of spatial information between visual words. In view of this, an object classification based on weakly supervised E2LSH and saliency map weighting is proposed. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is employed to generate a group of weakly randomized visual dictionary by clustering SIFT features of the training dataset, and the selecting process of hash functions is effectively supervised inspired by the random forest ideas to reduce the randomcity of E2LSH. Secondly, graph-based visual saliency (GBVS) algorithm is applied to detect the saliency map of different images and weight the visual words according to the saliency prior. Finally, saliency map weighted visual language model is carried out to accomplish object classification. Experimental results datasets of Pascal 2007 and Caltech-256 indicate that the distinguishability of objects is effectively improved and our method is superior to the state-of-the-art object classification methods.

• Korean Journal of Cognitive Science
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• v.22 no.2
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• pp.103-121
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• 2011

This study investigated how spatial dimension information and dimensional consistency between learning and testing phase would influence the target search performance. The participants learned spatial layouts of Lego blocks shown in either two- (2D) or three-dimension (3D) and were tested with the rotated stimuli ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, or $270^{\circ}$ from the initial view) in consistent or inconsistent dimension. Significantly better performance was observed when initial learning display appeared in 2D than in 3D. Particularly, the participants showed difficulties in flexible usage of spatial information presented in 3D especially if the dimensional information in the testing phase also was 3D and required mental rotation. The present study indicates that spatial map presented in 2D may be more useful than 3D in driving situations in which acquired spatial information from navigating device, such as GPS, and location of driver continuously changes.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.237-251
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• 2016

The conventional 3D-HEVC uses the depth data of the other view instead of that of the current view because the texture data has to be encoded before the corresponding depth data of the current view has been encoded, where the depth data of the other view is used as the predicted depth for the current view. Whereas the conventional 3D-HEVC has no other candidate for the predicted depth information except for that of the other view, the scalable 3D-HEVC utilizes the depth data of the lower spatial layer whose view ID is equal to that of the current picture. The depth data of the lower spatial layer is up-scaled to the resolution of the current picture, and then the enlarged depth data is used as the predicted depth information. Because the quality of the enlarged depth is much higher than that of the depth of the other view, the proposed scheme increases the coding efficiency of the scalable 3D-HEVC codec. Computer simulation results show that the scalable 3D-HEVC is useful and the proposed scheme to use the enlarged depth data for the current picture provides the significant coding gain.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.113-120
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• 2018

To fly a drone or unmanned aerial vechicle(UAV) safely, its pilot needs to maintain high situation awareness of its flight space. One of the important ways to improve the flight space awareness is to integrate both the global and the local navigation map a drone provides. However, the drone pilot often has to use the inconsistent reference frames or perspectives between the two maps. In specific, the global navigation map tends to display space information in the third-person perspective, whereas the local map tends to use the first-person perspective through the drone camera. This inconsistent perspective problem makes the pilot use mental rotation to align the different perspectives. In addition, integrating different dimensionalities (2D vs. 3D) of the two maps may aggravate the pilot's cognitive load of mental rotation. Therefore, this study aims to investigate the relation between perspective difference ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$) and the map dimensionality matches (3D-3D vs. 3D-2D) to improve the way of integrating the two maps. The results show that the pilot's flight space awareness improves when the perspective differences are smaller and also when the dimensionalities between the two maps are matched.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.109-116
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• 2005

3D Spatial Data, namely 3D Urban CG model express the building, road, river in virtual world and accumulate, manage the data in the GIS system. It is important infrastructure which expected in many usages. Recently 3D CG urban model needs much manual effort, time and costs to build them. In this paper, we introduce the integration of GIS, CG and automatic production of the $\lceil$3D Spatial Data Infrastructure$\rfloor$. This system make filtering, divide the polygon, generate the outlines of the GIS building map, design the graphic and property information and finally make automatic 3D CG models.