• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2020.07a
• /
• pp.576-578
• /
• 2020

최근 사용자에게 더욱 몰입감 있는 콘텐츠를 제공하기 위한 기술에 대한 관심이 증가하고 있으며 기존의 2D 콘텐츠와는 다른 새로운 방식인 3D 콘텐츠에 대한 연구가 활발히 진행되고 있으며 그 중 가장 대표적인 것이 Point Cloud 영상이라고 할 수 있다. Point Cloud의 경우 수많은 3차원 좌표를 가진 점들로 구성되어 있으며 각 점들마다 Attribute 값을 이용하여 색상 등의 표현이 가능한 구조로 이루어져 있다. 이러한 특성 때문에 Point Cloud 데이터는 방대한 용량을 가지고 있으며 기존의 2D 방식과 데이터 구조가 상이하기 때문에 새로운 압축 표준이 요구되었다. 이에 미디어 표준화 단체인 MPEG(Moving Picture Experts Group)에서는 MPEG-I(Immersive) 차세대 프로젝트 그룹을 이용하여 이러한 움직임에 대응하고 있다. MPEG-I의 part 5(Video-based Point Cloud Compression, V-PCC)에서는 객체를 대상으로 하여 기존의 비디오 코덱을 활용한 Point Cloud 압축 표준화를 진행중이다. V-PCC 데이터의 경우 기존의 2D 영상 데이터와 같이 전송을 통해 소비될 가능성이 아주 높기 때문에 이에 대한 고려가 필요하다. 현재 MPEG에서 표준화를 완료한 MMT(MPEG Media Transport)라는 전송 표준이 존재하기 때문에 이 기술을 활용 가능할 것으로 보인다. 따라서 본 논문에서는 Point Cloud 데이터를 압축한 V-PCC 데이터를 전송 표준 방식인 MMT를 이용하여 전송하는 방안에 대하여 제안한다.

• Tunnel and Underground Space
• /
• v.33 no.6
• /
• pp.495-507
• /
• 2023

The roughness of discontinuity significantly influences the mechanical characteristics of rock masses and extensively affects thermal and hydraulic behaviors. In this study, we utilized photogrammetry to generate 3D point cloud data for discontinuity and applied this data to characterize the roughness of discontinuity. The discontinuity profiles, reconstructed from the 3D point cloud data, were compared with those manually measured using a profile gauge. This comparison served to validate the accuracy and reliability of the acquired point cloud data in replicating the actual configurations of rock surfaces. Subsequent to this validation, influence of the number of profiles for representative JRC assessment was further investigated followed by suggestion of roughness anisotropy evaluation method with application of it to actual rock discontinuity surfaces.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.12 no.1
• /
• pp.605-616
• /
• 2020

The construction quality control of hull blocks is of great significance for shipbuilding. The total station device is predominantly employed in traditional applications, but suffers from long measurement time, high labor intensity and scarcity of data points. In this paper, the Terrestrial Laser Scanning (TLS) device is utilized to obtain an efficient and accurate comprehensive construction information of hull blocks. To address the registration problem which is the most important issue in comparing the measurement point cloud and the design model, an automatic registration approach is presented. Furthermore, to compare the data acquired by TLS device and sparse point sets obtained by total station device, a method for key point extraction is introduced. Experimental results indicate that the proposed approach is fast and accurate, and that applying TLS to control the construction quality of hull blocks is reliable and feasible.

• Journal of KIISE
• /
• v.44 no.4
• /
• pp.392-398
• /
• 2017

The point-cloud representation of an object is performed by scanning a space through a laser scanner that is extracting a set of points, and the points are then integrated into the same coordinate system through a registration. The set of the completed registration-integrated point clouds is classified into meaningful regions, shapes, and noises through a mathematical analysis. In this paper, the aim is the matching of a curved area like a cylinder shape in 3D point-cloud data. The matching procedure is the attainment of the center and radius data through the extraction of the cylinder-shape candidates from the sphere that is fitted through the RANdom Sample Consensus (RANSAC) in the point cloud, and completion requires the matching of the curved region with the Catmull-Rom spline from the extracted center-point data using the Principal Component Analysis (PCA). Not only is the proposed method expected to derive a fast estimation result via linear and curved cylinder estimations after a center-axis estimation without constraint and segmentation, but it should also increase the work efficiency of reverse engineering.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.6_3
• /
• pp.1233-1241
• /
• 2023

This paper investigates the efficient application of drone LiDAR technology for acquiring precise point cloud data in construction and civil engineering. A structured workflow encompassing data acquisition, processing, and accuracy verification is introduced. Practical testing on a construction site affirms that drone LiDAR surveying yields accurate and reliable data across various applications. With a focus on accuracy and verification, the results contribute to the progression of surveying methodologies in construction and civil engineering. The findings provide valuable insights into the dynamic technological landscape of these fields, establishing a foundation for more effective and precise surveying techniques. This study underscores the transformative potential of drone LiDAR technology in shaping the future of construction and civil engineering survey practices.

• Korean Journal of Computational Design and Engineering
• /
• v.11 no.5
• /
• pp.335-343
• /
• 2006

Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.6_2
• /
• pp.643-651
• /
• 2012

Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

• Journal of the Korea Institute of Military Science and Technology
• /
• v.23 no.6
• /
• pp.542-553
• /
• 2020

Virtual world and simulation need large scale map rendering. However, rendering too many vertices is a computationally complex and time-consuming process. Some game development companies have developed 3D LOD objects for high-speed rendering based on distance between camera and 3D object. Terrain physics simulation researchers need a way to recognize the original object shape from 3D LOD objects. In this paper, we proposed simply automatic LOD framework using point cloud data (PCD). This PCD was created using a 6-direct orthographic ray. Various experiments are performed to validate the effectiveness of the proposed method. We hope the proposed automatic LOD generation framework can play an important role in game development and terrain physic simulation.

• The Journal of Korea Robotics Society
• /
• v.17 no.3
• /
• pp.373-380
• /
• 2022

This paper considers a method of fast correspondence matching for iterative closest point (ICP) algorithm. In robotics, the ICP algorithm and its variants have been widely used for pose estimation by finding the translation and rotation that best align two point clouds. In computational perspectives, the main difficulty is to find the correspondence point on the reference point cloud to each observed point. Jump-table-based correspondence matching is one of the methods for reducing computation time. This paper proposes a method that corrects errors in an existing jump-table-based correspondence matching algorithm. The criterion activating the use of jump-table is modified so that the correspondence matching can be applied to the situations, such as point-cloud registration problems with highly curved surfaces, for which the existing correspondence-matching method is non-applicable. For demonstration, both hardware and simulation experiments are performed. In a hardware experiment using Hokuyo-10LX LiDAR sensor, our new algorithm shows 100% correspondence matching accuracy and 88% decrease in computation time. Using the F1TENTH simulator, the proposed algorithm is tested for an autonomous driving scenario with 2D range-bearing point cloud data and also shows 100% correspondence matching accuracy.

• Journal of Broadcast Engineering
• /
• v.25 no.5
• /
• pp.709-722
• /
• 2020

Point Cloud which is a cluster of numerous points can express 3D object beyond the 2D plane. Each point contains 3D coordinate and color data basically, reflectance or etc. additionally. Point Cloud demand research and development much higher effective compression technology. Video-based Point Cloud Compression (V-PCC) technology in development and standardization based on the established video codec. Despite its high effective compression technology, point cloud service will be limited by terminal spec and network conditions. 2D video had the same problems. To remedy this kind of problem, 2D video is using Scalable High efficiency Video Coding (SHVC), Dynamic Adaptive Streaming over HTTP (DASH) or diverse technology. This paper proposed a density scalability method using SHVC codec in V-PCC.