• 제목/요약/키워드: feature reconstruction

검색결과 218건 처리시간 0.039초

등고선 지도의 특징점을 이용한 효율적인 3차원 지형 복원 (An Efficient 3D Terrain Reconstruction Method Using Feature Points in Contour Map)

  • 이동규;임원규;한경숙
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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    • pp.653-655
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    • 1998
  • 본 논문은 3차원 지형을 현실감 있고 효율적으로 구축하기 위하여, 등고선 데이터로부터 지형의 특징점을 추출하고 이를 이용하여 3차원 지형 데이터를 복원하는 방법을 제안한다. 래스터 기반의 거리변환기법 알고리즘을 사용하여 2차원의 등고선 데이터로부터 3차원 지형을 생성하며, 생성된 3차원 지형정보로부터 지형의 특징점을 추출한다. 복원된 3차원 지형을 격자망 형태로 시각화하는데, 이때 특징점의 높이정보를 이용함으로써 지형을 표시하는데 요구되는 정보의 크기를 감소시킨다. 제안한 방법은 사용자가 상호대화식으로 수행할 수 있는 프로그램으로 윈도우 환경의 PC상에서 구현되었다. 이 프로그램의 실험결과는, 기존의 방법보다 적은 데이터양으로 3차원 지형을 시각화할 수 있음을 보여준다.

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Domain Adaptation Image Classification Based on Multi-sparse Representation

  • Zhang, Xu;Wang, Xiaofeng;Du, Yue;Qin, Xiaoyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권5호
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    • pp.2590-2606
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    • 2017
  • Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

가상환경을 위한 파노라마 생성에 관한 연구 (Panoramic Image Generation for the Virtual Environment)

  • 김태은
    • 디지털콘텐츠학회 논문지
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    • 제8권3호
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    • pp.365-370
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    • 2007
  • 본 논문에서는 환경 탐색을 위한 영상 기반 환경을 자동으로 생성하기 위한 새로운 모자이크 기법을 제안 한다. 제안된 방법은 영상의 투영 변환 행렬을 이용하여 한 영상 위에 다른 영상을 합성 한다. 특징 모델을 기반한 정합을 이용하여 영상을 모자이크를 구현하고 구맵핑을 통해 시각에 따라 변형되어 몰입감을 주는 영상 기반 환경을 생성한다, 특히, 취득한 영상간의 카메라 회전 성분에 강건한 기준 특징 벡터 필터링 방법을 제안하며 실험을 통해 그 유용성을 검증한다.

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공정계획을 위한 분산객체의 응용 (Application of Distributed Objects for CAPP)

  • 김준국;이홍희
    • 대한안전경영과학회지
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    • 제4권2호
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    • pp.155-168
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    • 2002
  • As the market and the organizations of an enterprise expand globally, the rapid and accurate communication gets more important for product manufacturing. The manufacturing information flow among the designers, the process planners and the shop floors is characterized and modelled. Its methods are constructed using distributed objects. Their introduction to the network-based CAPP system offers speed and safety for the system and makes the reconstruction and distribution of the application programs easy. The manufacturing processes are generated based on the feature information of a designed part, then the manufacturing resources are selected using the process planning logic which is implemented by distributed objects. The databases and distributed objects are integrated under the recent internet environments. The developed system makes it possible to manipulate and to transfer the process planning and manufacturing data everywhere in the world.

Attenuated Phase Shift Mask에 광 근접 효과 보정을 적용한 고립 패턴의 해상 한계 분석 (Resolution Limit Analysis of Isolated Patterns Using Optical Proximity Correction Method with Attenuated Phase Shift Mask)

  • 김종선;오용호;임성우;고춘수;이재철
    • 한국전기전자재료학회논문지
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    • 제13권11호
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    • pp.901-907
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    • 2000
  • As the minimum feature size for making ULSI approaches the wavelength of light source in optical lithography, the aerial image is so hardly distorted because of the optical proximity effect that the accurate mask image reconstruction on wafer surface is almost impossible. We applied the Optical Proximity Correction(OPC) on isolated patterns assuming Attenuated Phase Shift Mask(APSM) as well as binary mask, to correct the widening of isolated patterns. In this study, we found that applying OPC to APSM shows much better improvement not only in enhancing the resolution and fidelity of t도 images but also in enhancing the process margin than applying OPC to the binary mask. Also, we propose the OPC method of APSM for isolated patterns, the size of which is less than the wavelength of the ArF excimer laser. Finally, we predicted the resolution limit of optical lithography through the aerial image simulation.

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Organizing Lidar Data Based on Octree Structure

  • Wang, Miao;Tseng, Yi-Hsing
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.150-152
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    • 2003
  • Laser scanned lidar data record 3D surface information in detail. Exploring valuable spatial information from lidar data is a prerequisite task for its applications, such as DEM generation and 3D building model reconstruction. However, the inherent spatial information is implicit in the abundant, densely and randomly distributed point cloud. This paper proposes a novel method to organize point cloud data, so that further analysis or feature extraction can proceed based on a well organized data model. The principle of the proposed algorithm is to segment point cloud into 3D planes. A split and merge segmentation based on the octree structure is developed for the implementation. Some practical airborne and ground lidar data are tested for demonstration and discussion. We expect this data organization could provide a stepping stone for extracting spatial information from lidar data.

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스테레오 영상을 이용한 Surface Rendering (Surface Rendering using Stereo Images)

  • 이성재;윤성원;조영빈;이명호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 D
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    • pp.2818-2820
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    • 2001
  • This paper presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we performed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) algorithm. The final result image is helpful for the understanding of depth information visually.

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보조영상 재구성을 이용한 장문 검증 (Palm Print Verification Using Subimage Reconstruction)

  • 송영기;강환일;장우석;이병희
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2006년도 가을 학술발표논문집 Vol.33 No.2 (A)
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    • pp.48-52
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    • 2006
  • The palm print recognition is the most reliable authentication method in the biometrics. In this paper, using the efficient segmentation of the palm print region we propose the method of enabling the palm print recognition as the same method applicable to the finger print recognition. To achieve this, we propose the image processing procedures of the palm print segmentation and the feature extraction. We compare the matching result after extracting the features for the finger print and the palm print.

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Tucker Modeling based Kronecker Constrained Block Sparse Algorithm

  • Zhang, Tingping;Fan, Shangang;Li, Yunyi;Gui, Guan;Ji, Yimu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권2호
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    • pp.657-667
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    • 2019
  • This paper studies synthetic aperture radar (SAR) imaging problem which the scatterers are often distributed in block sparse pattern. To exploiting the sparse geometrical feature, a Kronecker constrained SAR imaging algorithm is proposed by combining the block sparse characteristics with the multiway sparse reconstruction framework with Tucker modeling. We validate the proposed algorithm via real data and it shows that the our algorithm can achieve better accuracy and convergence than the reference methods even in the demanding environment. Meanwhile, the complexity is smaller than that of the existing methods. The simulation experiments confirmed the effectiveness of the algorithm as well.

희소 클래스 분류 문제 해결을 위한 전처리 연구 (A Study on Pre-processing for the Classification of Rare Classes)

  • 류경준;신동규;신동일
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2020년도 춘계학술발표대회
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    • pp.472-475
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    • 2020
  • 실생활의 사례를 바탕으로 생성된 여러 분야의 데이터셋을 기계학습 (Machine Learning) 문제에 적용하고 있다. 정보보안 분야에서도 사이버 공간에서의 공격 트래픽 데이터를 기계학습으로 분석하는 많은 연구들이 진행 되어 왔다. 본 논문에서는 공격 데이터를 유형별로 정확히 분류할 때, 실생활 데이터에서 흔하게 발생하는 데이터 불균형 문제로 인한 분류 성능 저하에 대한 해결방안을 연구했다. 희소 클래스 관점에서 데이터를 재구성하고 기계학습에 악영향을 끼치는 특징들을 제거하고 DNN(Deep Neural Network) 모델을 사용해 분류 성능을 평가했다.