• Title/Summary/Keyword: Feature modeling

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Curved Feature Modeling and Accuracy Analysis Using Point Cloud Data (점군집 데이터를 이용한 곡면객체 모델링 및 정확도 분석)

  • Lee, Dae Geon;Yoo, Eun Jin;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.3
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    • pp.243-251
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    • 2016
  • LiDAR data processing steps include noise removal, filtering, classification, segmentation, shape recognition, modeling, and quality assessment. This paper focuses on modeling and accuracy evaluation of 3D objects with curved surfaces. The appropriate modeling functions were determined by analyzing surface patch shape. Existing methods for modeling curved surface features require linearization, initial approximation, and iteration of the non-linear functions. However, proposed method could directly estimate the unknown parameters of the modeling functions. The results demonstrate feasibility of the proposed method. The proposed method was applied to the simulated and real building data of hemi-spherical and semi-cylindrical surfaces. The parameters and accuracy of the modeling functions were estimated. It is expected that the proposed method would contribute to automatic modeling of various objects.

Systematic Development of Mobile IoT Device Power Management: Feature-based Variability Modeling and Asset Development (모바일 IoT 디바이스 파워 관리의 체계적인 개발 방법: 휘처 기반 가변성 모델링 및 자산 개발)

  • Lee, Hyesun;Lee, Kang Bok;Bang, Hyo-Chan
    • Journal of KIISE
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    • v.43 no.4
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    • pp.460-469
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    • 2016
  • Internet of Things (IoT) is an environment where various devices are connected to each other via a wired/wireless network and where the devices gather, process, exchange, and share information. Some of the most important types of IoT devices are mobile IoT devices such as smartphones. These devices provide various high-performance services to users but cannot be supplied with power all the time; therefore, power management appropriate to a given IoT environment is necessary. Power management of mobile IoT devices involves complex relationships between various entities such as application processors (APs), HW modules inside/outside AP, Operating System (OS), platforms, and applications; a method is therefore needed to systematically analyze and manage these relationships. In addition, variabilities related to power management such as various policies, operational environments, and algorithms need to be analyzed and applied to power management development. In this paper, engineering principles and a method based on them are presented in order to address these challenges and support systematic development of IoT device power management. Power management of connected helmet systems was used to validate the feasibility of the proposed method.

Stereok Matching based on Intensity and Features for Images with Background Removed (배경을 제외한 영상에서 명암과 특징을 기반으로하는 스테레오 정합)

  • Choe, Tae-Eun;Gwon, Hyeok-Min;Park, Jong-Seung;Han, Jun-Hui
    • Journal of KIISE:Software and Applications
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    • v.26 no.12
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    • pp.1482-1496
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    • 1999
  • 기존의 스테레오 정합 알고리즘은 크게 명암기반기법과 특징기반기법의 두 가지로 나눌 수 있다. 그리고, 각 기법은 그들 나름대로의 장단점을 갖는다. 본 논문은 이 두 기법을 결합하는 새로운 알고리즘을 제안한다. 본 논문에서는 물체모델링을 목적으로 하기 때문에 배경을 제거하여 정합하는 방법을 사용한다. 이를 위해, 정합요소들과 정합유사함수가 정의되고, 정합유사함수는 두 기법사이의 장단점을 하나의 인수에 의해 조절한다. 그 외에도 거리차 지도의 오류를 제거하는 coarse-to-fine기법, 폐색문제를 해결하는 다중윈도우 기법을 사용하였고, 물체의 표면형태를 알아내기 위해 morphological closing 연산자를 이용하여 물체와 배경을 분리하는 방법을 제안하였다. 이러한 기법들을 기반으로 하여 여러가지 영상에 대해 실험을 수행하였으며, 그 결과들은 본 논문이 제안하는 기법의 효율성을 보여준다. 정합의 결과로 만들어지는 거리차 지도는 3차원 모델링을 통해 가상공간상에서 보여지도록 하였다.Abstract Classical stereo matching algorithms can be classified into two major areas; intensity-based and feature-based stereo matching. Each technique has advantages and disadvantages. This paper proposes a new algorithm which merges two main matching techniques. Since the goal of our stereo algorithm is in object modeling, we use images for which background is removed. Primitives and a similarity function are defined. The matching similarity function selectively controls the advantages and disadvantages of intensity-based and feature-based matching by a parameter.As an additional matching strategy, a coarse-to-fine method is used to remove a errorneous data on the disparity map. To handle occlusions, multiple windowing method is used. For finding the surface shape of an object, we propose a method that separates an object and the background by a morphological closing operator. All processes have been implemented and tested with various image pairs. The matching results showed the effectiveness of our method. From the disparity map computed by the matching process, 3D modeling is possible. 3D modeling is manipulated by VRML(Virtual Reality Manipulation Language). The results are summarized in a virtual reality space.

Development of Digital Leaf Authoring Tool for Virtual Landscape Production (가상 조경 생성을위한 디지털 잎 저작도구 개발)

  • Kim, Jinmo
    • Journal of the Korea Computer Graphics Society
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    • v.21 no.5
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    • pp.1-10
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    • 2015
  • This study proposes a method of developing authoring tool that can easily and intuitively generate diverse digital leaves that compose virtual landscape. The main system of the proposed authoring tool consists of deformation method for the contour of leaf blade based on image warping, procedural modeling of leaf vein and visualization method based on mathematical model that expresses the color and brightness of leaves. First, the proposed authoring tool receives leaf input image and searches for contour information on the leaf blades. It then designs leaf blade deformation method that can generate diverse shapes of leaf blades in an intuitive structure using feature-based image warping. Based on the computed leaf blade contour, the system implements the generalized procedural modeling method suitable for the authoring tool that generates natural vein patterns appropriate for the leaf blade shape. Finally, the system applies visualization function that can express color and brightness of leaves and their changes over time using a mathematical model based on convolution sums of divisor functions. This paper provides texture support function so that the digital leaves that were generated using the proposed authoring tool can be used in a variety of three-dimensional digital contents field.

Deep Learning Based User Safety Profiling Using User Feature Information Modeling (딥러닝 기반 사용자 특징 정보 모델링을 통한 사용자 안전 프로파일링)

  • Kim, Kye-Kyung
    • Journal of Software Assessment and Valuation
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    • v.17 no.2
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    • pp.143-150
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    • 2021
  • There is a need for an artificial intelligent technology that can reduce various types of safety accidents by analyzing the risk factors that cause safety accidents in industrial site. In this paper, user safety profiling methods are proposed that can prevent safety accidents in advance by specifying and modeling user information data related to safety accidents. User information data is classified into normal and abnormal conditions through deep learning based artificial intelligence analysis. As a result of verifying user safety profiling technology using more than 10 types of industrial field data, 93.6% of user safety profiling accuracy was obtained.

Characterization of Groundwater Flow to Horizontal or Slanted Well Using Numerical Modeling (수치 모사를 활용한 수평 혹은 경사형 특수 정호 지하수 흐름 특성 평가)

  • Kim, Hyoung-Soo
    • Journal of Soil and Groundwater Environment
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    • v.13 no.2
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    • pp.54-61
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    • 2008
  • The drawdown distribution due to pumping by horizontal or slanted wells is analyzed by numerical modelling. In the numerical modelling uses 1-D discrete element feature included in commercial groundwater modeling program FEFLOW (version 5.1) and the results are compared with the semi analytic solution which uses superposition of successive point sources proposed by Zhan and Zlotnik (2002). Results of the numerical modeling agree well with the semi analytic solution except for very near field region of sink sources. The drawdown distribution due to pumping in riverbank filtration(RBF) plan site can be evaluated quantitatively by the numerical modeling in this study.

An Accurate Modeling Approach to Compute Noise Transfer Gain in Complex Low Power Plane Geometries of Power Converters

  • Nguyen, Tung Ngoc;Blanchette, Handy Fortin;Wang, Ruxi
    • Journal of Power Electronics
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    • v.17 no.2
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    • pp.411-421
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    • 2017
  • An approach based on a 2D lumped model is presented to quantify the voltage transfer gain (VTG) in power converter low power planes. The advantage of the modeling approach is the ease with which typical noise reduction devices such as decoupling capacitors or ferrite beads can be integrated into the model. This feature is enforced by a new modular approach based on effective matrix partitioning, which is presented in the paper. This partitioning is used to decouple power plane equations from external device impedance, which avoids the need for rewriting of a whole set of equation at every change. The model is quickly solved in the frequency domain, which is well suited for an automated layout optimization algorithm. Using frequency domain modeling also allows the integration of frequency-dependent devices such inductors and capacitors, which are required for realistic computation results. In order to check the precision of the modeling approach, VTGs for several layout configurations are computed and compared with experimental measurements based on scattering parameters.

Improvement and Evaluation of the Korean Large Vocabulary Continuous Speech Recognition Platform (ECHOS) (한국어 음성인식 플랫폼(ECHOS)의 개선 및 평가)

  • Kwon, Suk-Bong;Yun, Sung-Rack;Jang, Gyu-Cheol;Kim, Yong-Rae;Kim, Bong-Wan;Kim, Hoi-Rin;Yoo, Chang-Dong;Lee, Yong-Ju;Kwon, Oh-Wook
    • MALSORI
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    • no.59
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    • pp.53-68
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    • 2006
  • We report the evaluation results of the Korean speech recognition platform called ECHOS. The platform has an object-oriented and reusable architecture so that researchers can easily evaluate their own algorithms. The platform has all intrinsic modules to build a large vocabulary speech recognizer: Noise reduction, end-point detection, feature extraction, hidden Markov model (HMM)-based acoustic modeling, cross-word modeling, n-gram language modeling, n-best search, word graph generation, and Korean-specific language processing. The platform supports both lexical search trees and finite-state networks. It performs word-dependent n-best search with bigram in the forward search stage, and rescores the lattice with trigram in the backward stage. In an 8000-word continuous speech recognition task, the platform with a lexical tree increases 40% of word errors but decreases 50% of recognition time compared to the HTK platform with flat lexicon. ECHOS reduces 40% of recognition errors through incorporation of cross-word modeling. With the number of Gaussian mixtures increasing to 16, it yields word accuracy comparable to the previous lexical tree-based platform, Julius.

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Human Action Recognition Based on 3D Human Modeling and Cyclic HMMs

  • Ke, Shian-Ru;Thuc, Hoang Le Uyen;Hwang, Jenq-Neng;Yoo, Jang-Hee;Choi, Kyoung-Ho
    • ETRI Journal
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    • v.36 no.4
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    • pp.662-672
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    • 2014
  • Human action recognition is used in areas such as surveillance, entertainment, and healthcare. This paper proposes a system to recognize both single and continuous human actions from monocular video sequences, based on 3D human modeling and cyclic hidden Markov models (CHMMs). First, for each frame in a monocular video sequence, the 3D coordinates of joints belonging to a human object, through actions of multiple cycles, are extracted using 3D human modeling techniques. The 3D coordinates are then converted into a set of geometrical relational features (GRFs) for dimensionality reduction and discrimination increase. For further dimensionality reduction, k-means clustering is applied to the GRFs to generate clustered feature vectors. These vectors are used to train CHMMs separately for different types of actions, based on the Baum-Welch re-estimation algorithm. For recognition of continuous actions that are concatenated from several distinct types of actions, a designed graphical model is used to systematically concatenate different separately trained CHMMs. The experimental results show the effective performance of our proposed system in both single and continuous action recognition problems.

Moving Objects Modeling for Supporting Content and Similarity Searches (내용 및 유사도 검색을 위한 움직임 객체 모델링)

  • 복경수;김미희;신재룡;유재수;조기형
    • Journal of Korea Multimedia Society
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    • v.7 no.5
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    • pp.617-632
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    • 2004
  • Video Data includes moving objects which change spatial positions as time goes by. In this paper, we propose a new modeling method for a moving object contained in the video data. In order to effectively retrieve moving objects, the proposed modeling method represents the spatial position and the size of a moving object. It also represents the visual features and the trajectory by considering direction, distance and speed or moving objects as time goes by. Therefore, It allows various types of retrieval such as visual feature based similarity retrieval, distance based similarity retrieval and trajectory based similarity retrieval and their mixed type of weighted retrieval.

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