• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1318-1321
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• 2006

We describe the 3D/2D convertible color display based on modified integral imaging. In the proposed method a color liquid crystal display panel is used as a transmission-type display panel and enables a color 3D/2D convertible display system. The principle of the proposed method will be explained and methods to overcome the color dispersion problem will be discussed also.

• Journal of KIBIM
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• v.5 no.2
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• pp.12-18
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• 2015

Bridge piers typically have circular or rectangular shapes without decorative design. Prefabrication for accelerated construction has been widely adopted in bridge structures. Cost for steel formwork is a main restriction of creative irregular shapes. 3D modelling techniques allow creative design of columns and 3D printing provides possibility to minimize the fabrication cost. In this paper, 3D design process of bridge piers was suggested by converting 2D picture into 3D decorative shape. Formwork design using 3D printed panels was also proposed and mock-up tests were conducted. Precast columns need accurate geometry control from fabrication to assembly. Laser scanning and geometry control devices were adopted. Through the digitalized process of design, fabrication and assembly, creative design of structures can be realized in reasonable cost range.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.253-261
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• 1997

In general, the transformation of coordinates in GPS is carried out by 3 dimensional transformation method with 3-10 parameter. In korea, the coordinates of transformation points ware determined are adjusted in-dependently by planimetry and the height, and also the weight of observations were not properly applied to the adjustment. In this study, two different transformation methods are tested and analysed by the field test, and it is finally found that 2 dimensional method is more efficient way than 3 dimensional classical transformation method.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.3
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• pp.225-231
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• 2019

Purpose: This study was undertaken to compare fracture and flexural strength of provisional restorative resins fabricated by additive manufacturing, subtractive manufacturing, and conventional direct technique. Materials and methods: Five types of provisional restorative resin made with different methods were investigated: Stereolithography apparatus (SLA) 3D printer (S3Z), two digital light processing (DLP) 3D printer (D3Z, D3P), milling method (MIL), conventional method (CON). For fracture strength test, premolar shaped specimens were prepared by each method and stored in distilled water at $37^{\circ}C$ for 24 hours. Compressive load was measured using a universal testing machine (UTM). For flexural strength test, rectangular bar specimens ($25{\times}2{\times}2mm$) were prepared by each method according to ISO 10477 and flexural strength was measured by UTM. Results: Fracture strengths of the S3Z, D3Z, and D3P groups fabricated by additive manufacturing were not significantly different from those of MIL and CON groups (P>.05/10=.005). On the other hand, the flexural strengths of S3Z, D3P, and MIL groups were significantly higher than that of CON group (P<.05), but the flexural strength of D3Z group was significantly lower than that of CON group (P<.05). Conclusion: Within the limitation of our study, provisional restorative resins made from additive manufacturing showed clinically comparable fracture and flexural strength as those made by subtractive manufacturing and conventional method.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.21-32
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• 2015

Since spatio-temporal local features for video representation have become an important issue of modeless bottom-up approaches in action recognition, various methods for feature extraction and description have been proposed in many papers. In particular, BoF(bag of features) has been promised coherent recognition results. The most important part for BoF is how to represent dynamic information of actions in videos. Most of existing BoF methods consider the video as a spatio-temporal volume and describe neighboring 3D interest points as complex volumetric patches. To simplify these complex 3D methods, this paper proposes a novel method that builds BoF representation as a way to learn 2D interest points directly from video data. The basic idea of proposed method is to gather feature points not only from 2D xy spatial planes of traditional frames, but from the 2D time axis called spatio-temporal frame as well. Such spatial-temporal features are able to capture dynamic information from the action videos and are well-suited to recognize human actions without need of 3D extensions for the feature descriptors. The spatio-temporal BoF approach using SIFT and SURF feature descriptors obtains good recognition rates on a well-known actions recognition dataset. Compared with more sophisticated scheme of 3D based HoG/HoF descriptors, proposed method is easier to compute and simpler to understand.

• Clinics in Shoulder and Elbow
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• v.23 no.3
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• pp.119-124
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• 2020

Background: This study was performed to compare glenoid version and inclination measured using two-dimensional (2D) images from computed tomography (CT) scans or three-dimensional (3D) reconstructed bone models. Methods: Thirty patients who had undergone conventional CT scans were included. Two orthopedic surgeons measured glenoid version and inclination three times on 2D images from CT scans (2D measurement), and two other orthopedic surgeons performed the same measurements using 3D reconstructed bone models (3D measurement). The 3D-reconstructed bone models were acquired and measured with Mimics and 3-Matics (Materialise). Results: Mean glenoid version and inclination in 2D measurements were -1.705° and 9.08°, respectively, while those in 3D measurements were 2.635° and 7.23°. The intra-observer reliability in 2D measurements was 0.605 and 0.698, respectively, while that in 3D measurements was 0.883 and 0.892. The inter-observer reliability in 2D measurements was 0.456 and 0.374, respectively, while that in 3D measurements was 0.853 and 0.845. Conclusions: The difference between 2D and 3D measurements is not due to differences in image data but to the use of different tools. However, more consistent results were obtained in 3D measurement. Therefore, 3D measurement can be a good alternative for measuring glenoid version and inclination.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.183-190
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• 2022

Image-based 3D object detection is one of the important and difficult problems in autonomous driving and robotics, and aims to find and represent the location, dimension and orientation of the object of interest. It generates three dimensional (3D) bounding boxes with only 2D images obtained from cameras, so there is no need for devices that provide accurate depth information such as LiDAR or Radar. Image-based methods can be divided into three main categories: monocular, stereo, and multi-view 3D object detection. In this paper, we investigate the recent state-of-the-art models of the above three categories. In the multi-view 3D object detection, which appeared together with the release of the new benchmark datasets, NuScenes and Waymo, we discuss the differences from the existing monocular and stereo methods. Also, we analyze their performance and discuss the advantages and disadvantages of them. Finally, we conclude the remaining challenges and a future direction in this field.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.71-76
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• 2022

In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.612-615
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• 2006

In this study, we compared and analyzed the floor impact noise insulation performance produced by the rating methods. The rating methods are using reversed A-weighting curve, A-weighted sound pressure levels(dB(A)). The results of this study are(1)dB(A) by the specified frequency is 0.5dB(A) at light weight and 2.5dB(A) at heavy weight upper than all pass dB(A)(2)the rating using reversed A-weighting curve is 5dB lower than dB(A)(3)the number of rating using reversed A-weighting curve mainly depends on impact noise pressure level of 63Hz in heavy weight but dB(A) does not.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.35-47
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• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.