• Title/Summary/Keyword: Moving Image(Video)

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An Improved Method for Detection of Moving Objects in Image Sequences Using Statistical Hypothesis Tests

  • Park, Jae-Gark;Kim, Munchurl;Lee, Myoung-Ho;Ahn, Chei-Teuk
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1998.06b
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    • pp.171-176
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    • 1998
  • This paper resents a spatio-temporal video segmentation method. The algorithm segments each frame of video sequences captured by a static or moving camera into moving objects (foreground) and background using a statistical hypothesis test. In the proposed method, three consecutive image frames are exploited and a hypothesis testing is performed by comparing two means from two consecutive difference images, which results in a T-test. This hypothesis test yields change detection mask that indicates moving areas (foreground) and non-moving areas (background). Moreover, an effective method for extracting object mask form change detection mask is proposed.

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A Segmentation Method for a Moving Object on A Static Complex Background Scene. (복잡한 배경에서 움직이는 물체의 영역분할에 관한 연구)

  • Park, Sang-Min;Kwon, Hui-Ung;Kim, Dong-Sung;Jeong, Kyu-Sik
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.3
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    • pp.321-329
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    • 1999
  • Moving Object segmentation extracts an interested moving object on a consecutive image frames, and has been used for factory automation, autonomous navigation, video surveillance, and VOP(Video Object Plane) detection in a MPEG-4 method. This paper proposes new segmentation method using difference images are calculated with three consecutive input image frames, and used to calculate both coarse object area(AI) and it's movement area(OI). An AI is extracted by removing background using background area projection(BAP). Missing parts in the AI is recovered with help of the OI. Boundary information of the OI confines missing parts of the object and gives inital curves for active contour optimization. The optimized contours in addition to the AI make the boundaries of the moving object. Experimental results of a fast moving object on a complex background scene are included.

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Establishment Threshold Value of Image Realization & Reconstruction of Stoppage Image using Picture Resemblance (닮은꼴을 이용한 영상구현 임계값설정과 정지영상 복원법)

  • Jin, Hyun-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.4
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    • pp.187-194
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    • 2011
  • In this paper, JPEG(Joint Photographic Experts Group) image data video decoding technique is presented, it is Huffman decoding method and fractal image method which is very complexive algorithm and the time required much it to implement this method and the first image is decoded to video frame image. This have defect of overlap decoding and transport work because of impossible to represent objective value of resemblance. The proposed method was calculated the mathematical absolute image resemblance and simplify the moving picture process to reducing the step of moving picture codefying. The results show that smoothed moving picture compared recent methods.

Motion Compensated Subband Video Coding with Arbitrarily Shaped Region Adaptivity

  • Kwon, Oh-Jin;Choi, Seok-Rim
    • ETRI Journal
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    • v.23 no.4
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    • pp.190-198
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    • 2001
  • The performance of Motion Compensated Discrete Cosine Transform (MC-DCT) video coding is improved by using the region adaptive subband image coding [18]. On the assumption that the video is acquired from the camera on a moving platform and the distance between the camera and the scene is large enough, both the motion of camera and the motion of moving objects in a frame are compensated. For the compensation of camera motion, a feature matching algorithm is employed. Several feature points extracted using a Sobel operator are used to compensate the camera motion of translation, rotation, and zoom. The illumination change between frames is also compensated. Motion compensated frame differences are divided into three regions called stationary background, moving objects, and newly emerging areas each of which is arbitrarily shaped. Different quantizers are used for different regions. Compared to the conventional MC-DCT video coding using block matching algorithm, our video coding scheme shows about 1.0-dB improvements on average for the experimental video samples.

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The Walkers Tracking Algorithm using Color Informations on Multi-Video Camera (다중 비디오카메라에서 색 정보를 이용한 보행자 추적)

  • 신창훈;이주신
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.5
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    • pp.1080-1088
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    • 2004
  • In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

Segmentation and Tracking Algorithm for Moving Speaker in the Video Conference Image (화상회의 영상에서 움직이는 화자의 분할 및 추적 알고리즘)

  • Choi Woo-Young;Kim Han-Me
    • Journal of IKEEE
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    • v.6 no.1 s.10
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    • pp.54-64
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    • 2002
  • In this paper, we propose the algorithm for segmenting the moving speaker and tracking its movement in the video conference image. For real time processing, we simplify the algorithm which is processed in the order of the segmenting and the tracking step. In the segmenting step, the speaker object is segmented from the image by using both the motion information obtained from the difference method and the illuminance information of image. The reference mask image is created from segmented speaker object. In the tracking step, the moving speaker is tracked by using simple block matching algorithm of which computation time is reduced by discarding the blocks which are classified into the unuseful blocks. In the simulation, we can get the good result of segmenting and tracking the moving speaker by applying the proposed algorithm to several test images.

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Tracing of Moving Objects by Stereo Video Cameras (스테레오 비디오 카메라에 의한 운동물체의 위치추적)

  • Lee, Chang-Kyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.15 no.2
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    • pp.185-193
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    • 1997
  • While close range photogrammetry has been widely applied for static deformation analysis, video cameras have many characteristics that make them the sensors of choice for dynamic analysis of rapidly changing situations. They also have limitations. The aim of this research is to explore the potential of a video system for monitoring dynamic objects. A pilot system consists of two camcorders, VCR, and PC with frame grabber. To estimte the performance of this system for moving objects, a car was imaged covering several phases when starting to drive. The sequential images of a moving car were recorded on VCR. 15 images per second were digitized in an off-line mode by frame grabber. The image coordinates of targets attached to the rear bumper of a car were acquired by IDRISI, and the object coordinates were derived based on DLT. This research suggests that home video cameras, PC, and photogrammetric principles are promising tools for monitoring of the moving objects and vibrations as well as other time dependent situations.

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A Study on Parallel Processing System for Automatic Segmentation of Moving Object in Image Sequences

  • Lee, Hyung;Park, Jong-Won
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.429-432
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    • 2000
  • The new MPEG-4 video coding standard enables content-based functionalities. In order to support the philosophy of the MPEG-4 visual standard, each frame of video sequences should be represented in terms of video object planes (VOP’s). In other words, video objects to be encoded in still pictures or video sequences should be prepared before the encoding process starts. Therefore, it requires a prior decomposition of sequences into VOP’s so that each VOP represents a moving object. A parallel processing system is required an automatic segmentation to be processed in real-time, because an automatic segmentation is time consuming. This paper addresses the parallel processing: system for an automatic segmentation for separating moving object from the background in image sequences. The proposed parallel processing system comprises of processing elements (PE’s) and a multi-access memory system (MAMS). Multi-access memory system is a memory controller to perform parallel memory access with the variety of types: horizontal, vertical, and block access way. In order to realize these ways, a multi-access memory system consists of a memory module selection module, data routing modules, and an address calculation and routing module. The proposed system is simulated and evaluated by the CADENCE Verilog-XL hardware simulation package.

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An Automatic Segmentation Method for Video Object Plane Generation (비디오 객체 생성을 위한 자동 영상 분할 방법)

  • 최재각;김문철;이명호;안치득;김성대
    • Journal of Broadcast Engineering
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    • v.2 no.2
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    • pp.146-155
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    • 1997
  • The new video coding standard Iv1PEG-4 is enabling content-based functionalities. It requires a prior decomposition of sequences into video object planes (VOP's) so that each VOP represents moving objets. This paper addresses an image segmentation method for separating moving objects from still background (non-moving area) in video sequences using a statistical hypothesis test. In the proposed method. three consecutive image frames are exploited and a hypothesis testing is performed by comparing two means from two consecutive difference images. which results in a T-test. This hypothesis test yields a change detection mask that indicates moving areas (foreground) and non-moving areas (background), Moreover. an effective method for extracting

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Removing Shadows for the Surveillance System Using a Video Camera (비디오 카메라를 이용한 감시 장치에서 그림자의 제거)

  • Kim, Jung-Dae;Do, Yong-Tae
    • Proceedings of the KIEE Conference
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    • 2005.05a
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    • pp.176-178
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    • 2005
  • In the images of a video camera employed for surveillance, detecting targets by extracting foreground image is of great importance. The foreground regions detected, however, include not only moving targets but also their shadows. This paper presents a novel technique to detect shadow pixels in the foreground image of a video camera. The image characteristics of video cameras employed, a web-cam and a CCD, are first analysed in the HSV color space and a pixel-level shadow detection technique is proposed based on the analysis. Compared with existing techniques where unified criteria are used to all pixels, the proposed technique determines shadow pixels utilizing a fact that the effect of shadowing to each pixel is different depending on its brightness in background image. Such an approach can accommodate local features in an image and hold consistent performance even in changing environment. In experiments targeting pedestrians, the proposed technique showed better results compared with an existing technique.

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