• Title/Summary/Keyword: Background modeling

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3D/BIM Applications to Large-scale Complex Building Projects in Japan

  • Yamazaki, Yusuke;Tabuchi, Tou;Kataoka, Makoto;Shimazaki, Dai
    • International Journal of High-Rise Buildings
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    • v.3 no.4
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    • pp.311-323
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    • 2014
  • This paper introduces recent applications of three-dimensional building/construction data modeling (3D) and building information modeling (BIM) to large-scale complex building construction projects in Japan. Recently, BIM has been utilized as a tool in construction process innovation through planning, design, engineering, procurement and construction to establish a front-loading-type design building system. Firstly, the background and introduction processes of 3D and BIM are described to clarify their purposes and scopes of applications. Secondly, 3D and BIM applications for typical large-scale complex building construction projects to improve planning and management efficiency in building construction are presented. Finally, future directions and further research issues with 3D and BIM applications are proposed.

Using Hierarchical Performance Modeling to Determine Bottleneck in Pattern Recognition in a Radar System

  • Alsheikhy, Ahmed;Almutiry, Muhannad
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.292-302
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    • 2022
  • The radar tomographic imaging is based on the Radar Cross-Section "RCS" of the materials of a shape under examination and investigation. The RCS varies as the conductivity and permittivity of a target, where the target has a different material profile than other background objects in a scene. In this research paper, we use Hierarchical Performance Modeling "HPM" and a framework developed earlier to determine/spot bottleneck(s) for pattern recognition of materials using a combination of the Single Layer Perceptron (SLP) technique and tomographic images in radar systems. HPM provides mathematical equations which create Objective Functions "OFs" to find an average performance metric such as throughput or response time. Herein, response time is used as the performance metric and during the estimation of it, bottlenecks are found with the help of OFs. The obtained results indicate that processing images consumes around 90% of the execution time.

Analysis of Secondary Battery Trends Using Topic Modeling: Focusing on Solid-State Batteries

  • Chunghyun Do;Yong Jin Kim
    • Asian Journal of Innovation and Policy
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    • v.12 no.3
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    • pp.345-362
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    • 2023
  • As the widespread adoption and proliferation of electric vehicles continue, the secondary battery market is experiencing rapid growth. However, lithium-ion batteries, which constitute a majority of secondary batteries, present high risks of fire and explosion. Solid-state batteries are thus garnering attention as the next-generation batteries since they eliminate fire hazards and significantly reduce the risk of explosions. Against this background, the study aimed to analyze research trends and provide insights by examining 2,927 domestic papers related to solid-state batteries over the past decade (2013-2022). Specifically, we used topic modeling to extract major keywords associated with solid-state batteries research and to explore the network characteristics across major topics. The changes in research on solid-state batteries were analyzed in-depth by calculating topic dominance by year. The findings provide an overview of the emerging trends in domestic solid-state battery research, and might serve as a valuable reference in shaping long-term research directions.

Identifying Latent Groups in Married Working Women's Work-Family Spillover and Testing the Difference of Mental Health (기혼취업여성 일-가족 양립에 따른 전이유형과 정신건강에 관한 연구)

  • Ha, Yeojin
    • Human Ecology Research
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    • v.55 no.1
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    • pp.13-26
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    • 2017
  • This study investigated the latent groups depending on married working women's work-family spillover. The effects of factors that determine mental health subgroups and differences were also analyzed. Mixture modeling was applied to the Korean Longitudinal Survey of Women & Families to achieve the research objectives. The major findings of this study were as follows. First, there were four subgroups that could be defined according to the work-family spillover: mid-level spillover group (mid-positive and mid-negative spillover group), high-level spillover group (high-positive and high-negative spillover group), low-level spillover group (low-positive and low-negative spillover group), and high-negative and low-positive spillover group. Second, the results of mixture regression analysis to test the effect of eco-system variables showed that age, academic background, non-traditional family value, number of children, work hours, wage income, and availability of the maternity leave were significant determinants of the latent groups. The probability of classifying in the high-negative and low-positive spillover group increased when women showed a lower academic background and wage income, higher number of children and older age, and longer work hours than others. Third, the high-level spillover group, and the high-level spillover group showed the lowest stress and the lowest depression; however, the low-level spillover group reported the highest stress and the highest depression. Implications, limitations, and future directions were discussed based on the results.

A Study on Window Based Real-Time Static Background Modeling and Object Extraction (윈도우 기반의 실시간 정지 백그라운드 모델링과 오브젝트 추출에 관한 연구)

  • Park, Jun-Hun;Choi, Chang-Gyu;Cho, Jeong-Hyun;Kim, Sung-Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.11a
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    • pp.49-52
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    • 2003
  • 본 논문에서는 실시간 감시 시스템의 응용분야를 위한 백그라운드 모델링과 업데이트 그리고 오브젝트 추출 시스템을 설계 구현한다. 일반적인 감시 시스템은 백그라운드의 모델링(background modeling)과 오브젝트의 검출(object detection), 오브젝트의 추적(tracking)으로 구성된다. 실시간 감시시스템을 가능하게 하기 위해서는 작은 시간 복잡도(low time complexity)로 백그라운드와 오브젝트를 검출할 수 있어야 하고 실외환경(outdoor)의 노이즈(noise)를 반영할 수 있어야 한다. 기존에는 빠른 백그라운드 모델링을 위해 분산, 평균, 최빈값 등을 사용한 연구들이 있었다. 이러한 방법들은 빠른 수행 속도를 보장하지만 노이즈를 오브젝트로 검출하는 문제점이 있다. 또 다른 연구 분야인 메디안(median) 검출 방법은 실외환경에 존재하는 노이즈 반영에 적합한 반면, 정렬(sorting) 연산에 많은 시간이 소요된다. 본 논문은 윈도우(Window) 기반의 러닝 윈도우 리스트(Running Window List)를 이용하여 메디안 정렬 시간을 최소화하고 실시간으로 백그라운드 모델링, 오브젝트 검출, 백그라운드 업데이트를 할 수 있는 방법을 제안한다.

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Parametric Video Compression Based on Panoramic Image Modeling (파노라믹 영상 모델에 근거한 파라메트릭 비디오 압축)

  • Sim Dong-Gyu
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.4 s.310
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    • pp.96-107
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    • 2006
  • In this paper, a low bitrate video coding method based on new panoramic modeling is proposed for panning cameras. An input video frame from a panning camera is decomposed into a background image, rectangular moving object regions, and a residual image. In coding the background, we employ a panoramic model that can account for several image formation processes, such as perspective projection, lens distortion, vignetting and illumination effects. Moving objects aredetected, and their minimum bounding rectangular regions are coded with a JPEG-2000 coder. We have evaluated the effectiveness of the proposed algorithm with several indoor and outdoor sequences and found that the PSNR is improved by $1.3{\sim}4.4dB$ compared to that of JPEG-2000.

Real-Time Object Segmentation in Image Sequences (연속 영상 기반 실시간 객체 분할)

  • Kang, Eui-Seon;Yoo, Seung-Hun
    • The KIPS Transactions:PartB
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    • v.18B no.4
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    • pp.173-180
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    • 2011
  • This paper shows an approach for real-time object segmentation on GPU (Graphics Processing Unit) using CUDA (Compute Unified Device Architecture). Recently, many applications that is monitoring system, motion analysis, object tracking or etc require real-time processing. It is not suitable for object segmentation to procedure real-time in CPU. NVIDIA provide CUDA platform for Parallel Processing for General Computation to upgrade limit of Hardware Graphic. In this paper, we use adaptive Gaussian Mixture Background Modeling in the step of object extraction and CCL(Connected Component Labeling) for classification. The speed of GPU and CPU is compared and evaluated with implementation in Core2 Quad processor with 2.4GHz.The GPU version achieved a speedup of 3x-4x over the CPU version.

The Effective Background Modeling Method by User Intervention (사용자 개입을 통한 효과적 배경 모델 생성 기법)

  • Kim, Hyungmin;Lee, Jae Hoon;Park, Jong-Il;Kim, Yookyung;Kim, Kwang-yong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.11a
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    • pp.47-50
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    • 2016
  • 객체를 추적하는 기술은 컴퓨터 비전 분야에서 활발히 연구되고 있는 분야 중 하나이다. 그 중 고정된 단일 카메라를 이용한 객체 추적 기술은 비디오 감시(Surveillance) 등에서 활용되고 있다. 고정된 카메라 환경에서 객체를 추적하는 방법 중 배경 모델링(Background Modeling)을 이용한 방법은 간단하면서도 널리 사용되는 방법 중 하나이다. 객체의 움직임이나 특징을 분석하여 배경 모델을 생성한 후 배경 정보를 이용하여 전경을 분리하면 쉽게 객체를 추출할 수 있다. 그러나 객체의 움직임이 적은 경우 해당 영역에서의 배경 모델은 정확하게 생성될 수 없다. 배경 모델을 학습하는 동안 객체가 충분이 움직이면 이런 문제를 해결할 수 있으나 객체가 움직이기 전까지는 오류가 지속된다. 이런 문제를 해결하기 위해 본 논문에서는 인페인팅(Inpainting)을 이용하여 움직임이 적은 영역을 보정하여 정확한 배경 모델을 생성하는 방법을 제안한다. 배경 모델을 생성한 후 객체로 식별할 수 있는 후보 영역을 식별한다. 선정된 영역들 중 사용자가 객체로 판단되는 영역을 선택하여 해당 영역에 대해 인페인팅으로 화소값 및 가중치들을 보정한다. 보정된 영상으로 배경 모델링을 수행하면 움직임이 적은 영역에 대해서도 효과적으로 배경 모델을 생성 할 수 있다.

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Adaptive Background Modeling Considering Stationary Object and Object Detection Technique based on Multiple Gaussian Distribution

  • Jeong, Jongmyeon;Choi, Jiyun
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.11
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    • pp.51-57
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    • 2018
  • In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.