• Title/Summary/Keyword: multi-time scale

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Multi-scale 3D Panor ama Content Augmented System using Depth-map

  • Kim, Cheeyong;Kim, Eung-Kon;Kim, Jong-Chan
    • Journal of Korea Multimedia Society
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    • v.17 no.6
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    • pp.733-740
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    • 2014
  • With the development and spread of 3D display, users can easily experience an augmented reality with 3D features. Therefore, the demand for content of an augmented reality is exponentially growing in various fields. A traditional augmented reality environment was generally created by CG(Computer Graphics) modelling production tools. However, this method takes too much time and efforts to create an augmented environment. To create an augmented environment similar to the real world, everything in the real world should be measured, gone through modeling, and located in an augmented environment. But the time and efforts spent in the creation don't produce the same environment as the real world, making it hard for users to feel the sense of reality. In this study, multi-scale 3D panorama content augmented system is suggested by using a depth-map. By finding matching features from images to add 3D features to an augmented environment, a depth-map is derived and embodied as panorama, producing high-quality augmented content system with a sense of reality. With this study, limits of 2D panorama technologies will be overcome and a sense of reality and immersion will be provided to users with a natural navigation.

A New Three-dimensional Integrated Multi-index Method for CBIR System

  • Zhang, Mingzhu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.993-1014
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    • 2021
  • This paper proposes a new image retrieval method called the 3D integrated multi-index to fuse SIFT (Scale Invariant Feature Transform) visual words with other features at the indexing level. The advantage of the 3D integrated multi-index is that it can produce finer subdivisions in the search space. Compared with the inverted indices of medium-sized codebook, the proposed method increases time slightly in preprocessing and querying. Particularly, the SIFT, contour and colour features are fused into the integrated multi-index, and the joint cooperation of complementary features significantly reduces the impact of false positive matches, so that effective image retrieval can be achieved. Extensive experiments on five benchmark datasets show that the 3D integrated multi-index significantly improves the retrieval accuracy. While compared with other methods, it requires an acceptable memory usage and query time. Importantly, we show that the 3D integrated multi-index is well complementary to many prior techniques, which make our method compared favorably with the state-of-the-arts.

Implementation Strategy for the Numerical Efficiency Improvement of the Multiscale Interpolation Wavelet-Galerkin Method

  • Seo Jeong Hun;Earmme Taemin;Jang Gang-Won;Kim Yoon Young
    • Journal of Mechanical Science and Technology
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    • v.20 no.1
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    • pp.110-124
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    • 2006
  • The multi scale wavelet-Galerkin method implemented in an adaptive manner has an advantage of obtaining accurate solutions with a substantially reduced number of interpolation points. The method is becoming popular, but its numerical efficiency still needs improvement. The objectives of this investigation are to present a new numerical scheme to improve the performance of the multi scale adaptive wavelet-Galerkin method and to give detailed implementation procedure. Specifically, the subdomain technique suitable for multiscale methods is developed and implemented. When the standard wavelet-Galerkin method is implemented without domain subdivision, the interaction between very long scale wavelets and very short scale wavelets leads to a poorly-sparse system matrix, which considerably worsens numerical efficiency for large-sized problems. The performance of the developed strategy is checked in terms of numerical costs such as the CPU time and memory size. Since the detailed implementation procedure including preprocessing and stiffness matrix construction is given, researchers having experiences in standard finite element implementation may be able to extend the multi scale method further or utilize some features of the multiscale method in their own applications.

Fast Random-Forest-Based Human Pose Estimation Using a Multi-scale and Cascade Approach

  • Chang, Ju Yong;Nam, Seung Woo
    • ETRI Journal
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    • v.35 no.6
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    • pp.949-959
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    • 2013
  • Since the recent launch of Microsoft Xbox Kinect, research on 3D human pose estimation has attracted a lot of attention in the computer vision community. Kinect shows impressive estimation accuracy and real-time performance on massive graphics processing unit hardware. In this paper, we focus on further reducing the computation complexity of the existing state-of-the-art method to make the real-time 3D human pose estimation functionality applicable to devices with lower computing power. As a result, we propose two simple approaches to speed up the random-forest-based human pose estimation method. In the original algorithm, the random forest classifier is applied to all pixels of the segmented human depth image. We first use a multi-scale approach to reduce the number of such calculations. Second, the complexity of the random forest classification itself is decreased by the proposed cascade approach. Experiment results for real data show that our method is effective and works in real time (30 fps) without any parallelization efforts.

A Terminal Ballistic Performance Prediction of Multi-Layer Armor with Neural Network (신경회로망을 이용한 다층장갑의 방호성능 예측)

  • 유요한;김태정;양동열
    • Journal of the Korea Institute of Military Science and Technology
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    • v.4 no.2
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    • pp.189-201
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    • 2001
  • For a design of multi-layer armor, the extensive full scale or sub-scale penetration test data are required. In generally, the collection of penetration data is in need of time-consuming and expensive processes. However, the application of numerical or analytical method is very limited due to poor understanding about penetration mechanics. In this paper, we have developed a neural network analyzer which can be used as a design tool for a new armor. Calculation results show that the developed neural network analyzer can predict relatively exact penetration depth of a new armor through the effective analysis of the pre-existing penetration database.

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The lambda network to build multi-domain intensive large-scale grid environment (람다네크워크를 통한 대규모 멀티도메인 그리드환경구현 연구)

  • Min-Ki Noh;Sung Jin Ahn
    • Annual Conference of KIPS
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    • 2008.11a
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    • pp.1383-1386
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    • 2008
  • 분산된 자원의 실시간 정보교환과 그리드를 통한 효율적인 자원 재구성을 위해서는 기존의 단일 도메인에서 구성되는 네트워크와는 다르게 대규모 가상도메인(Large-Scale Multi-domain)을 위한 네트워크의 성능과 기능 향상이 필요하다. 그리드네트워크를 기반으로 활발히 진행 중인 글로벌한 연구자원을 대상으로 공유된 자원의 성능 개선과 자원 간 데이터전달의 효율 개선을 위해 TDM(Time Division Multiplexing)기반의 Multi-Point Lambda-Path Ring 구현 기술을 제안하고 이를 Multi-Domain 간 Control Plane하에서 최적의 가상도메인으로 구성 할 수 있는 기법을 제안한다.

High-Temperature Oxidation Behavior of Commercial Pure Titanium in Mixed Gases (혼합가스 분위기 중에서 공업용 순 타이타늄의 고온산화 거동)

  • Park, S.H.;Ahn, Y.S.
    • Journal of Power System Engineering
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    • v.11 no.2
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    • pp.44-50
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    • 2007
  • The oxidation behavior of commercial pure titanium is investigated in the temperature range of $727^{\circ}C{\sim}950^{\circ}C$ in mixed gases. The weight change is measured by TGA during oxidation in mixed gases. The oxidation behavior indicated by weight gain or the growth of oxide layer is based on the linear rate law at high temperatures. The structure of the oxide scale formed during oxidation is analysed by optical microscopy, electron probe microanalyzer, scanning electron microscope and x-ray diffraction. Oxide scales have a $TiO_2$ structure, and are constituted with multi-layered or two layered porous external one and a dense internal one. Ti-O solid solution region is formed at the interface of metal and scale layer. The formation of oxide scale is influenced by the oxidation temperature, time, crystal structure and the condition of atmosphere.

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Review of Operational Multi-Scale Environment Model with Grid Adaptivity

  • Kang, Sung-Dae
    • Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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    • v.10 no.S_1
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    • pp.23-28
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    • 2001
  • A new numerical weather prediction and dispersion model, the Operational Multi-scale Environment model with Grid Adaptivity(OMEGA) including an embedded Atmospheric Dispersion Model(ADM), is introduced as a next generation atmospheric simulation system for real-time hazard predictions, such as severe weather or the transport of hazardous release. OMEGA is based on an unstructured grid that can facilitate a continuously varying horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from 20 -30 meters in the boundary layer to 1 km in the free atmosphere. OMEGA is also naturally scale spanning and time. In particular, the unstructured grid cells in the horizontal dimension can increase the local resolution to better capture the topography or important physical features of the atmospheric circulation and cloud dynamics. This means the OMEGA can readily adapt its grid to a stationary surface, terrain features, or dynamic features in an evolving weather pattern. While adaptive numerical techniques have yet to be extensively applied in atmospheric models, the OMEGA model is the first to exploit the adaptive nature of an unstructured gridding technique for atmospheric simulation and real-time hazard prediction. The purpose of this paper is to provide a detailed description of the OMEGA model, the OMEGA system, and a detailed comparison of OMEGA forecast results with observed data.

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Multi-resolution Representation of 2D Point Data (2차원 점 데이터의 다중해상도 표현)

  • Yun, Seong-Min;Lee, Mun-Bae;Park, Sang-Hun
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.7
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    • pp.768-774
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    • 2010
  • Reconstruction of implicit surfaces from scattered point data sets have been developed in various engineering and scientific studies. In this paper, we represent a method to construct functions of 2D point data using multi-scale kernels and show it can be applied to graphics applications needed to access data in real-time. Our approach is similar to previous work in that a set of coefficients of the functions are calculated and stored in the preprocessing stage and function values at arbitrary positions are evaluated for real-time applications, however, it is different from others in that users can choose detail levels freely in real-time processing stage. The reason why the functions implicitly supports multi-resolution results from the mathematical properties of multi-scale kernels, and proposed method can be expanded to represent multi-resolution functions of n-dimensional data.

Sound event detection based on multi-channel multi-scale neural networks for home monitoring system used by the hard-of-hearing (청각 장애인용 홈 모니터링 시스템을 위한 다채널 다중 스케일 신경망 기반의 사운드 이벤트 검출)

  • Lee, Gi Yong;Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.6
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    • pp.600-605
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    • 2020
  • In this paper, we propose a sound event detection method using a multi-channel multi-scale neural networks for sound sensing home monitoring for the hearing impaired. In the proposed system, two channels with high signal quality are selected from several wireless microphone sensors in home. The three features (time difference of arrival, pitch range, and outputs obtained by applying multi-scale convolutional neural network to log mel spectrogram) extracted from the sensor signals are applied to a classifier based on a bidirectional gated recurrent neural network to further improve the performance of sound event detection. The detected sound event result is converted into text along with the sensor position of the selected channel and provided to the hearing impaired. The experimental results show that the sound event detection method of the proposed system is superior to the existing method and can effectively deliver sound information to the hearing impaired.