• Title/Summary/Keyword: Background Generation

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Background Generation using Temporal and Spatial Information of Pixels (시간축과 공간축 화소 정보를 이용한 배경 생성)

  • Cho, Sang-Hyun;Kang, Hang-Bong
    • The KIPS Transactions:PartB
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    • v.17B no.1
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    • pp.15-22
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    • 2010
  • Background generation is very important for accurate object tracking in video surveillance systems. Traditional background generation techniques have some problems with non-moving objects for longer periods. To overcome this problem, we propose a newbackground generation method using mean-shift and Fast Marching Method (FMM) to use pixel information along temporal and spatial dimensions. The mode of pixel value density along time axis is estimated by mean-shift algorithm and spatial information is evaluated by FMM, and then they are used together to generate a desirable background in the existence of non-moving objects during longer period. Experimental results show that our proposed method is more efficient than the traditional method.

A Study of Background Edge Generation for Moving Object Detection under Moving Camera (이동카메라에서 이동물체 감지를 위한 배경에지 생성에 관한 연구)

  • Lee, June-Hyung;Chae, Ok-Sam
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.6 s.44
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    • pp.151-156
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    • 2006
  • This paper presents an background edge generation based automatic algorithm for detection of moving objects under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally, aligning and reorganizing this images. We develop an efficient approach for robust panoramic background edge generation as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The proposed method can be successfully realized in various monitoring systems like intrusion detection as well as video surveillance.

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Adaptive Background Generation for Vehicle Tracking System (차량 추적 시스템을 위한 적응적 배경 영상 생성)

  • 장승호;정정훈;신정호;박주용;백준기
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.413-416
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    • 2003
  • This paper proposes an adaptive background image generation method based on the frame difference for traffic monitoring. The performance of the conventional method is limited when there are more vehicles due to traffic Jam. To improve on this, we use frame differencing to separate vehicles from background in frame differencing, we adopt selective approach by using part of the image not considered as vehicle fer extraction of background. The proposed method generates background more efficiently than conventional methods even in the presence of heavy traffic.

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Music Generation Method by DNA as a Game Background Music (DNA염기배열에 의한 게임 배경 음악 생성방법)

  • Park, Young-B.;Hwang, Cheol-Ho
    • Journal of Korea Game Society
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    • v.1 no.1
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    • pp.88-93
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    • 2001
  • It is getting easier to make copy of Digital Media. And, illegal copy of digital media causes an infringement of copyright. As a result, it is getting hard to find good game background music. In this study, Auto music generation method by DNA is proposed. Through this method, the game background music can be provided very easily. Since thousands forms of DNA have been found already, we can have thousands of game background music through this method.

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Depth-based Mesh Modeling for Virtual Environment Generation (가상 환경 생성을 위한 깊이 기반 메쉬 모델링)

  • 이원우;우운택
    • Proceedings of the IEEK Conference
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    • 2003.11b
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    • pp.111-114
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    • 2003
  • In this paper, we propose a depth-based mesh modeling method to generate virtual environment. The proposed algorithm constructs mesh model from unorganized point cloud obtained from a multi-view camera. We separate the point cloud consisting objects from the background. Then, we apply triangulation to each object and background. Since the objects and the background are modeled independently, it is possible to construct effective virtual environment. The application of proposed modeling method is applicable to entertainment, such as movie and video game and effective virtual environment generation.

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Non-parametric Background Generation based on MRF Framework (MRF 프레임워크 기반 비모수적 배경 생성)

  • Cho, Sang-Hyun;Kang, Hang-Bong
    • The KIPS Transactions:PartB
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    • v.17B no.6
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    • pp.405-412
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    • 2010
  • Previous background generation techniques showed bad performance in complex environments since they used only temporal contexts. To overcome this problem, in this paper, we propose a new background generation method which incorporates spatial as well as temporal contexts of the image. This enabled us to obtain 'clean' background image with no moving objects. In our proposed method, first we divided the sampled frame into m*n blocks in the video sequence and classified each block as either static or non-static. For blocks which are classified as non-static, we used MRF framework to model them in temporal and spatial contexts. MRF framework provides a convenient and consistent way of modeling context-dependent entities such as image pixels and correlated features. Experimental results show that our proposed method is more efficient than the traditional one.

A Background Image Generation Method for Image Detector Using Detected Vehicle Information (차량 탐지 정보를 이용한 영상 검지기의 배경 영상 생성 방법)

  • Kwon, Young Tak;Kim, Yoon Jin;Park, Chul Hong;Kim, Hee Jeong;Soh, Young Sung
    • Journal of Advanced Navigation Technology
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    • v.3 no.1
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    • pp.60-68
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    • 1999
  • In this paper, we propose a new background generation method for image detector for traffic information collection. Conventional methods result in bad performance when there are frequent traffic jams due to heavy traffic. To improve on this, we use high level information from vehicle detection. Only part of the image that is not considered as vehicle is used in background generation. The proposed method finds background more robustly than that of the conventional methods even in the presence of heavy traffic.

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Stereoscopic Conversion of Object-based MPEG-4 Video (객체 기반 MPEG-4 동영상의 입체 변환)

  • 박상훈;김만배;손현식
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2407-2410
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    • 2003
  • In this paper, we propose a new stereoscopic video conversion methodology that converts two-dimensional (2-D) MPEG-4 video to stereoscopic video. In MPEG-4, each Image is composed of background object and primary object. In the first step of the conversion methodology, the camera motion type is determined for stereo Image generation. In the second step, the object-based stereo image generation is carried out. The background object makes use of a current image and a delayed image for its stereo image generation. On the other hand, the primary object uses a current image and its horizontally-shifted version to avoid the possible vertical parallax that could happen. Furthermore, URFA(Uncovered Region Filling Algorithm) is applied in the uncovered region which might be created after the stereo image generation of a primary object. In our experiment, show MPEG-4 test video and its stereoscopic video based upon out proposed methodology and analyze Its results.

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A NEW CELL SIZING METHOD FOR AUTOMATIC UNSTRUCTURED GRID GENERATION USING CAD SURFACE DATA (CAD 형상 데이터를 이용한 비정렬 격자 자동 생성을 위한 격자셀 크기 지정 기법)

  • Lee, B.J.;Kim, B.S.
    • 한국전산유체공학회:학술대회논문집
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    • 2007.10a
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    • pp.120-125
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    • 2007
  • In this paper a new cell sizing method is proposed. The new method calculates cell size at a point using given size control elements directly without the aid of background grid as other cell sizing algorithms do. The calculation method and related definitions are described in detail, and typical cell sizing results are given.

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Feature-Based Panoramic Background Generation for Object Tracking in Dynamic Video (가변시점 비디오 객체추적을 위한 특징점 기반 파노라마 배경 생성)

  • Im, Jae-Hyun;Paik, Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.6
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    • pp.108-116
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    • 2008
  • In this paper, we propose the algorithm for making panoramic background and object tacking using pan-tilt-zoom camera. We draw an analogy relation between images for cylinder projection, rearrange of images, stitching, and blending. We can then make the panoramic background, and can track the object use the panoramic background. After generated the background, the proposed algorithm tracks the moving object. Therefore it can detect the wide area, and it tracks the object continuously. So the proposed algorithm is able to use at wide area to detect and track the object.