• Title/Summary/Keyword: 전역 변이 벡터

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An Improved Motion/Disparity Vector Prediction for Multi-view Video Coding (다시점 비디오 부호화를 위한 개선된 움직임/변이 벡터 예측)

  • Lim, Sung-Chang;Lee, Yung-Lyul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.2
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    • pp.37-48
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    • 2008
  • Generally, a motion vector and a disparity vector represent the motion information of an object in a single-view of camera and the displacement of the same scene between two cameras that located spatially different from each other, respectively. Conventional H.264/AVC does not use the disparity vector in the motion vector prediction because H.264/AVC has been developed for the single-view video. But, multi-view video coding that uses the inter-view prediction structure based on H.264/AVC can make use of the disparity vector instead of the motion vector when the current frame refers to the frame of different view. Therefore, in this paper, we propose an improved motion/disparity vector prediction method that consists of global disparity vector replacement and extended neighboring block prediction. From the experimental results of the proposed method compared with the conventional motion vector prediction of H.264/AVC, we achieved average 1.07% and 1.32% of BD (Bjontegaard delta)-bitrate saving for ${\pm}32$ and ${\pm}64$ of global vector search range, respectively, when the search range of the motion vector prediction is set to ${\pm}16$.

Fast Disparity Vector Estimation using Motion vector in Stereo Image Coding (스테레오 영상에서 움직임 벡터를 이용한 고속 변이 벡터 추정)

  • Doh, Nam-Keum;Kim, Tae-Yong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.5
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    • pp.56-65
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    • 2009
  • Stereoscopic images consist of the left image and the right image. Thus, stereoscopic images have much amounts of data than single image. Then an efficient image compression technique is needed, the DPCM-based predicted coding compression technique is used in most video coding standards. Motion and disparity estimation are needed to realize the predicted coding compression technique. Their performing algorithm is block matching algorithm used in most video coding standards. Full search algorithm is a base algorithm of block matching algorithm which finds an optimal block to compare the base block with every other block in the search area. This algorithm presents the best efficiency for finding optimal blocks, but it has very large computational loads. In this paper, we have proposed fast disparity estimation algorithm using motion and disparity vector information of the prior frame in stereo image coding. We can realize fast disparity vector estimation in order to reduce search area by taking advantage of global disparity vector and to decrease computational loads by limiting search points using motion vectors and disparity vectors of prior frame. Experimental results show that the proposed algorithm has better performance in the simple image sequence than complex image sequence. We conclude that the fast disparity vector estimation is possible in simple image sequences by reducing computational complexities.

Fast Mode Decision using Global Disparity Vector for Multi-view Video Coding (다시점 영상 부호화에서 전역 변이 벡터를 이용한 고속 모드 결정)

  • Han, Dong-Hoon;Cho, Suk-Hee;Hur, Nam-Ho;Lee, Yung-Lyul
    • Journal of Broadcast Engineering
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    • v.13 no.3
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    • pp.328-338
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    • 2008
  • Multi-view video coding (MVC) based on H.264/AVC encodes multiple views efficiently by using a prediction scheme that exploits inter-view correlation among multiple views. However, with the increase of the number of views and use of inter-view prediction among views, total encoding time will be increased in multiview video coding. In this paper, we propose a fast mode decision using both MB(Macroblock)-based region segmentation information corresponding to each view in multiple views and global disparity vector among views in order to reduce encoding time. The proposed method achieves on average 40% reduction of total encoding time with the objective video quality degradation of about 0.04 dB peak signal-to-noise ratio (PSNR) by using joint multi-view video model (JMVM) 4.0 that is the reference software of the multiview video coding standard.

An efficient multi-view video coding using correlation between multi-view video and depth map (다시점 비디오와 깊이 정보의 상판도를 이용한 효율적인 다시점 비디오 부호화 기법)

  • Bae, Byung-Kyu;Yun, Jung-Hwan;Kim, Dong-Wook;Yoo, Ji-Sang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2008.11a
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    • pp.259-262
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    • 2008
  • 본 논문에서는 다시점 비디오와 깊이 정보의 상관도를 이용해서 현재 JVT(joint video team)에서 표준화 된 다시점 비디오 부호화 (multi-view video coding : MVC)의 참조 소프트웨어인 JMVM(joint multi-view video model)을 기반으로 하여 효율적인 다시점 비디오 압축 방법을 제안한다. 기존의 일반적인 비디오 부호화 방식은 단일 시점에 대한 비디오 부호화 기술이기 때문에 다시점 비디오 전송을 위해서는 시점 당 각각 전송 채널에 필요하다. 하지만 다시점 비디오 부호화 기법을 이용하게 되면, 단일 전송 채널을 이용하여 전송이 가능하다. 본 논문에서 제안된 방법은 입력된 다시점 입력 영상과 해당 하는 깊이 정보를 이용하여 시점 간의 예측 방법의 효율성을 높였다. 다시점 입력 영상과 깊이 정보의 전역 변이 벡터 (global disparity vector : GDV)의 상관도를 이용하였으며, 다시점 영상과 깊이 정보를 동시에 전송해야 할 경우 복잡도를 낮출 수 있고, 약 $0.01{\sim}0.1dB$의 PSNR 이득을 얻을 수 있다.

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Multi-view Video Coding using the Constrained Inter-view Prediction (다시점 비디오 부호화에서 시점 간 예측 제한 방법)

  • Chun, Sung-Hwan;Shin, Kwang-Mu;Kim, Ki-Wan;Chung, Ki-Dong
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.8
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    • pp.788-792
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    • 2008
  • In this paper, we propose a method that uses the constrained inter-view prediction for multi-view video coding. In the multi-view video, there exists occluded area because of the locations and angles of cameras. This increases the computational complexity, as it still uses both reference pictures for predicting the area which is not shown in the current frame. In this paper, we propose a method that does not use the inter-view prediction in cases of the occluded macroblocks. Experimental results show that benefits about 4% can be achieved compared with the conventional approaches.

Genetic lesion matching algorithm using medical image (의료영상 이미지를 이용한 유전병변 정합 알고리즘)

  • Cho, Young-bok;Woo, Sung-Hee;Lee, Sang-Ho;Han, Chang-Su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.5
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    • pp.960-966
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    • 2017
  • In this paper, we proposed an algorithm that can extract lesion by inputting a medical image. Feature points are extracted using SIFT algorithm to extract genetic training of medical image. To increase the intensity of the feature points, the input image and that raining image are matched using vector similarity and the lesion is extracted. The vector similarity match can quickly lead to lesions. Since the direction vector is generated from the local feature point pair, the direction itself only shows the local feature, but it has the advantage of comparing the similarity between the other vectors existing between the two images and expanding to the global feature. The experimental results show that the lesion matching error rate is 1.02% and the processing speed is improved by about 40% compared to the case of not using the feature point intensity information.

Fast Motion Estimation Algorithm for Efficient MPEG-2 Video Transcoding with Scan Format Conversion (스캔 포맷 변환이 있는 효율적인 MPEG-2 동영상 트랜스코딩을 위한 고속 움직임 추정 기법)

  • 송병철;천강욱
    • Journal of Broadcast Engineering
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    • v.8 no.3
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    • pp.288-296
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    • 2003
  • ATSC (Advanced Television System Committee) has specified 18 video formats for DTV (Digital Television), e.g., scan format, size format, and frame rate format conversion. Effective MPEG-2 video transcoders should support any conversion between the above-mentioned formats. Scan format conversion Is hard to Implement because it may often induce frame rate and size format conversion together. Especially. because of picture type conversion caused by scan format conversion, the computational burden of motion estimation (ME) in transcoding becomes serious. This paper proposes a fast ME algorithm for MPEG-2 video transcoding supporting scan format conversion. Firstly, we extract and compose a set of candidate motion vectors (MVs) from the input bit-stream to comply with the re-encoding format. Secondly, the best MV is chosen among several candidate MVs by using a weighted median selector. Simulation results show that the proposed ME algorithm provides outstanding PSNR performance close to full search ME, while reducing the transcoding complexity significantly.

A Study on Electromyogram Signals Recognition Technique using Neural Network and Genetic Algorithms (신경회로망과 유전알고리즘을 이용한 근전신호 인식기법)

  • Shin, Chul-Kyu;Lee, Sang-Min;Lee, Eun-Sil;Kwon, Jang-Woo;Jang, Young-Gun;Hong, Seung-Hong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.11
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    • pp.176-183
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    • 1998
  • A new recognition technique using neural network coupled with Genetic Algorithms (GAs) was proposed. This technique concentrate on efficient Electromyography signal recognition through out improving neural network's several demerits. GAs paly a role of selecting Multilayer Perceptron's optimized initial connection weights by its typical global search. Electro Myography signal was pre-processed with Hidden Markov Model (HMM) in order to refect its time-varying property into input pattern except other features such as Zero Crossing Number(ZCN) and Integral Absolute Value (IAV). Results for 6 primitive motions show that the suggested technique has better performance in learning time and recognition rates than already established ordinary methods. Moreover, it performed stable recognition without convergence into a local minimum.

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