• 제목/요약/키워드: 3D Based

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스케치를 이용한 웹 환경에서의 3차원 모델 검색 (Web-based 3D Object Retrieval from User-drawn Sketch Query)

  • 송종헌;주재호;윤상민
    • 정보과학회 논문지
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    • 제41권10호
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    • pp.838-846
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    • 2014
  • 터치기반 스마트 기기의 발달에 따라, 사용자가 펜/손가락을 이용하여 그린 스케치를 기반으로 다양한 멀티미디어 검색 기술은 컴퓨터 비전, 컴퓨터 그래픽스, 패턴인식, HCI 분야에서 많은 각광을 받고 있다. 하지만, 기존의 텍스트 정보를 기반으로 한 검색 시스템은 사용자가 원하는 멀티미디어 데이터를 정확히 검색하는데 한계가 있다. 따라서, 멀티미디어 자체가 가지고 있는 정보를 이용하여 검색할 수 있는 내용 기반 멀티미디어 검색에 관한 연구가 필요하게 되었다. 본 논문에서는 Hybrid Edge Descriptor(HED)를 사용한 웹 환경에서의 사용자가 스케치로부터 3차원 모델을 검색할 수 있는 시스템을 제안한다. 3차원 모델로부터 다양한 방향으로 투영된 suggestive contour 영상 및 사용자가 그린 스케치 영상으로부터 전역/지역 히스토그램 분석을 이용한 HED 검색자를 통해 회전 및 이동에 강인한 3차원 모델 검색 시스템을 제안한다.

중소규모 교량의 점검·진단 데이터 효율적 관리 및 활용을 위한 3D 모델 기반 실증 DB시스템 개발 (Development of a 3D Model-Based Demonstration DB System for Efficient Management and Utilization of Inspection and Diagnosis Data of Small and Medium-Sized Bridges)

  • 박세현;정대성;서진숙;김태형
    • 한국구조물진단유지관리공학회 논문집
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    • 제25권6호
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    • pp.1-11
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    • 2021
  • 국내 대형 SOC 시설물의 노후화가 가속화됨에 따라 시설물 유지관리도 현재 상태 기준의 안전성 평가에서 미래 노후도 수준 예측을 기반으로 한 성능 중심의 예방적·선제적 유지 관리로 전환되고 있다. 특히, 교량의 경우 1·2종 교량은 많은 연구와 함께체계적으로 관리되고 있으나, 중소형 3종 교량은 사용 연한 동안 성능저하를 대변하는 이력 데이터 수집과 활용은 전무한 실정이다. 따라서 본 연구에서는 부재별 외관 손상에 대해 생애주기별 유지관리 이력을 3차원 교량 객체에 등록함으로써 손상 위치의 손상변화율 등을 직관적으로 확인 할 수 있고, API 기반 종합성능평가가 가능하도록 3D 교량모델 기반의 실증 DB시스템을 설계하여 개발하였다.

Effects of Extracellular Stimulation of Different Niche Condition on the Transcriptional Regulation of Matrix Metalloproteinase Genes in the Mouse Embryonic Stem Cells

  • Yun, Jung Im;Kim, Min Seong;Lee, Seung Tae
    • Reproductive and Developmental Biology
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    • 제37권2호
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    • pp.79-83
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    • 2013
  • Matrix metalloproteinases (MMPs) have been known to affect to cell migration, proliferation, morphogenesis and apoptosis by degrading the extracellular matrix. In the previous studies, undifferentiated mouse embryonic stem cells (ESCs) were successfully proliferated inside the extracellular matrix (ECM) analog-conjugated three-dimensional (3D) poly ethylene glycol (PEG)-based hydrogel. However, there is no report about MMP secretion in ESCs, which makes it difficult to understand and explain how ESCs enlarge space and proliferate inside 3D PEG-based hydrogel constructed by crosslinkers containing MMP-specific cleavage peptide sequence. Therefore, we investigated what types of MMPs are released from undifferentiated ESCs and how extracellular signals derived from various niche conditions affect MMP expression of ESCs at the transcriptional level. Results showed that undifferentiated ESCs expressed specifically MMP2 and MMP3 mRNAs. Transcriptional up-regulation of MMP2 was caused by the 3D scaffold, and activation of integrin inside the 3D scaffold upregulated MMP2 mRNAs synergistically. Moreover, mouse embryonic fibroblasts (MEFs) on 2D matrix and 3D scaffold induced upregulation of MMP3 mRNAs, and activation of integrins through conjugation of extracellular matrix (ECM) analogs with 3D scaffold upregulated MMP3 mRNAs synergistically. These results suggest that successful proliferation of ESCs inside the 3D PEG-based hydrogel may be caused by increase of MMP2 and MMP3 expression resulting from 3D scaffold itself as well as activation of integrins inside the 3D PEG-based scaffold.

3D 프린터를 이용한 마이크로 리액터 가공에 관한 연구 (Fabrication of Micro-reactor by 3D Printing Machine)

  • 최해운;윤성철;마재권;방대욱
    • 한국생산제조학회지
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    • 제23권3호
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    • pp.218-222
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    • 2014
  • A 3D printer was used to fabricate a micro-TAS system for biomedical applications. A polymeric medical device fabrication based on a 3D printer can be performed at atmospheric conditions. A CAD- and CAM-based system is a flexible method to design medical components, and a 3D printer is a suitable device to perform this task. In this research, a 100-micron-wide fluidic channel was fabricated with a high-aspect ratio. A cross-sectional SEM image confirmed its possible usage in a micro-reactor using 3D printers. CNC-machined samples were compared to 3D printer-fabricated samples, and the advantages and disadvantages were discussed. Based on the SEM images, the surface roughness of the 3D printed reactor was not affected by wet or dry conditions due to its manufacturing principle. An aspect ratio of 5 to 1 was achievable with 100-${\mu}$ m-wide fluid channels. No melting was found, and the shape of channels was straight enough to be used for micro reactors.

정규화를 통한 3차원 데이터 모델 구축 및 활용성 향상 방안 연구 -건축 마감 공사 중심으로 - (A Study on 3D Data Model Development by Normalizing and Method of its Effective Use - Focused on Building Interior Construction -)

  • 이명훈;함남혁;김주형;김재준
    • 한국디지털건축인테리어학회논문집
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    • 제10권3호
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    • pp.11-18
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    • 2010
  • Cost estimation through fast and correct quantity take offs are crucial in the process of construction project. The existing methods for cost estimation are mainly based on 2D-based drawings and the estimation result tends to be different according to the estimator's experience, the quality and quantity of used information and estimation time. To solve these problems, the domestic construction industry have recently tried to use the data extracted from 3D data modeling based on BIM(Building Information Modeling) in order to achieve more accurate and objective cost estimation. However it tends to increase dramatically the quantity of information that can be used in cost estimation by estimators. Therefore in order to achieve quality information data from 3D data modeling, the characteristics of the project should be reflected on the 3D model and it is most important to extract information only for cost estimation from the whole 3D model fast and accurately. Thus this study aims to propose the 3D modeling method through Data Normalization which maximizes the usability of 3D Data modeling in cost estimation process.

3D 오토인코더 기반의 뇌 자기공명영상에서 다발성 경화증 병변 검출 (Multiple Sclerosis Lesion Detection using 3D Autoencoder in Brain Magnetic Resonance Images)

  • 최원준;박성수;김윤수;감진규
    • 한국멀티미디어학회논문지
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    • 제24권8호
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    • pp.979-987
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    • 2021
  • Multiple Sclerosis (MS) can be early diagnosed by detecting lesions in brain magnetic resonance images (MRI). Unsupervised anomaly detection methods based on autoencoder have been recently proposed for automated detection of MS lesions. However, these autoencoder-based methods were developed only for 2D images (e.g. 2D cross-sectional slices) of MRI, so do not utilize the full 3D information of MRI. In this paper, therefore, we propose a novel 3D autoencoder-based framework for detection of the lesion volume of MS in MRI. We first define a 3D convolutional neural network (CNN) for full MRI volumes, and build each encoder and decoder layer of the 3D autoencoder based on 3D CNN. We also add a skip connection between the encoder and decoder layer for effective data reconstruction. In the experimental results, we compare the 3D autoencoder-based method with the 2D autoencoder models using the training datasets of 80 healthy subjects from the Human Connectome Project (HCP) and the testing datasets of 25 MS patients from the Longitudinal multiple sclerosis lesion segmentation challenge, and show that the proposed method achieves superior performance in prediction of MS lesion by up to 15%.

3D-Distortion Based Rate Distortion Optimization for Video-Based Point Cloud Compression

  • Yihao Fu;Liquan Shen;Tianyi Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권2호
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    • pp.435-449
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    • 2023
  • The state-of-the-art video-based point cloud compression(V-PCC) has a high efficiency of compressing 3D point cloud by projecting points onto 2D images. These images are then padded and compressed by High-Efficiency Video Coding(HEVC). Pixels in padded 2D images are classified into three groups including origin pixels, padded pixels and unoccupied pixels. Origin pixels are generated from projection of 3D point cloud. Padded pixels and unoccupied pixels are generated by copying values from origin pixels during image padding. For padded pixels, they are reconstructed to 3D space during geometry reconstruction as well as origin pixels. For unoccupied pixels, they are not reconstructed. The rate distortion optimization(RDO) used in HEVC is mainly aimed at keeping the balance between video distortion and video bitrates. However, traditional RDO is unreliable for padded pixels and unoccupied pixels, which leads to significant waste of bits in geometry reconstruction. In this paper, we propose a new RDO scheme which takes 3D-Distortion into account instead of traditional video distortion for padded pixels and unoccupied pixels. Firstly, these pixels are classified based on the occupancy map. Secondly, different strategies are applied to these pixels to calculate their 3D-Distortions. Finally, the obtained 3D-Distortions replace the sum square error(SSE) during the full RDO process in intra prediction and inter prediction. The proposed method is applied to geometry frames. Experimental results show that the proposed algorithm achieves an average of 31.41% and 6.14% bitrate saving for D1 metric in Random Access setting and All Intra setting on geometry videos compared with V-PCC anchor.

3차원 모델링을 이용한 템플릿 정합 (3D-Modeling-Based Template Matching)

  • 한영모
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제5권12호
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    • pp.663-670
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    • 2016
  • 본 논문은 3차원 모델링을 이용한 템플릿 정합 방법을 제안한다. 본 방법은 각도와 크기 별로 매칭 중에 여러 개의 2차원 템플릿을 사용하는 기존의 불편한 영상 템플릿 정합 방법보다 사용 편리성을 증대시킨다.

웹 기반의 가상현실 3D 국악 박물관 제작 (A Web-based 3D Virtual Reality Pavilion of Korean Traditional Music)

  • 최지애;심재선;김윤상
    • 디지털산업정보학회논문지
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    • 제4권1호
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    • pp.65-68
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    • 2008
  • In this paper, a web-based 3D virtual reality (VR) pavillion of Korean Traditional Music was implemented. The VR pavillion is used for the virtual demonstration and experience of Korean Traditional Music, which provides the information as well as multimedia experience on eight instruments to users through internet. It provides eight web-pages and one an audio-visual classroom on the instruments.

학습기반의 객체분할과 Optical Flow를 활용한 2D 동영상의 3D 변환 (2D to 3D Conversion Using The Machine Learning-Based Segmentation And Optical Flow)

  • 이상학
    • 한국인터넷방송통신학회논문지
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    • 제11권3호
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    • pp.129-135
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    • 2011
  • 본 논문에서는 2D 동영상을 3D 입체영상으로 변환하기 위해서 머신러닝에 의한 학습기반의 객체분할과 객체의 optical flow를 활용하는 방법을 제안한다. 성공적인 3D 변환을 가능하게 하는 객체분할을 위해서, 객체의 칼라 및 텍스쳐 정보는 학습을 통해 반영하고 움직임이 있는 영역 위주로 객체분할을 수행할 수 있도록 optical flow를 도입한 새로운 에너지함수를 설계하도록 한다. 분할된 객체들에 대해 optical flow 크기에 따른 깊이맵을 추출하여 입체영상에 필요한 좌우 영상을 합성하여 생성하도록 한다. 제안한 기법으로 인해 효과적인 객체분할과 깊이맵을 생성하여 2D 동영상에서 3D 입체동영상으로 변환됨을 실험결과들이 보여준다.