• Title/Summary/Keyword: 움직임 보간

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Error-Resilience Enhancement based on Polyphase Down Sampling for the H.264 Video Coding Technology (에러 강인성 향상을 위한 다상 다운 샘플링 적용 H.264 동영상 부호화 기술)

  • Jung, Eun Ku;Jia, Jie;Kim, Hae Kwang;Choi, Hae Chul;Kim, Jae Gon
    • Journal of Broadcast Engineering
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    • v.10 no.3
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    • pp.340-347
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    • 2005
  • This paper presents a polyphase down sampling based multiple description coding applied to H.264 video coding standard. For a given macroblock, a residual macroblock is calculated by motion estimation, and before applying DCT, quantization and entrophy coding of the H.264 coding process, the polyphase down sampling is applied to the residual macroblock to code in four separate descriptions. Experiments were performed for all the 9 test sequences of JVT SVC standardization in various packet loss patterns. Experimental results show that the proposed one gives 0.5 to 5 dB enhancement over an error-concealment based on the slice group map technolgoy.

Gaze Detection Based on Facial Features and Linear Interpolation on Mobile Devices (모바일 기기에서의 얼굴 특징점 및 선형 보간법 기반 시선 추적)

  • Ko, You-Jin;Park, Kang-Ryoung
    • Journal of Korea Multimedia Society
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    • v.12 no.8
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    • pp.1089-1098
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    • 2009
  • Recently, many researches of making more comfortable input device based on gaze detection technology have been performed in human computer interface. Previous researches were performed on the computer environment with a large sized monitor. With recent increase of using mobile device, the necessities of interfacing by gaze detection on mobile environment were also increased. In this paper, we research about the gaze detection method by using UMPC (Ultra-Mobile PC) and an embedded camera of UMPC based on face and facial feature detection by AAM (Active Appearance Model). This paper has following three originalities. First, different from previous research, we propose a method for tracking user's gaze position in mobile device which has a small sized screen. Second, in order to detect facial feature points, we use AAM. Third, gaze detection accuracy is not degraded according to Z distance based on the normalization of input features by using the features which are obtained in an initial user calibration stage. Experimental results showed that gaze detection error was 1.77 degrees and it was reduced by mouse dragging based on the additional facial movement.

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Correction of Rotated Frames in Video Sequences Using Modified Mojette Transform (변형된 모젯 변환을 이용한 동영상에서의 회전 프레임 보정)

  • Kim, Ji-Hong
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.42-49
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    • 2013
  • The camera motion is accompanied with the translation and/or the rotation of objects in frames of a video sequence. An unnecessary rotation of objects declines the quality of the moving pictures and in addition is a primary cause of the viewers' fatigue. In this paper, a novel method for correcting rotated frames in video sequences is presented, where the modified Mojette transform is applied to the motion-compensated area in each frame. The Mojette transform is one of discrete Radon transforms, and is modified for correcting the rotated frames as follows. First, the bin values in the Mojette transform are determined by using pixels on the projection line and the interpolation of pixels adjacent to the line. Second, the bin values are calculated only at some area determined by the motion estimation between current and reference frames. Finally, only one bin at each projection is computed for reducing the amount of the calculation in the Mojette transform. Through the simulation carried out on various test video sequences, it is shown that the proposed scheme has good performance for correcting the rotation of frames in moving pictures.

Advanced Abdominal MRI Techniques and Problem-Solving Strategies (복부 자기공명영상 고급 기법과 문제 해결 전략)

  • Yoonhee Lee;Sungjin Yoon;So Hyun Park;Marcel Dominik Nickel
    • Journal of the Korean Society of Radiology
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    • v.85 no.2
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    • pp.345-362
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    • 2024
  • MRI plays an important role in abdominal imaging because of its ability to detect and characterize focal lesions. However, MRI examinations have several challenges, such as comparatively long scan times and motion management through breath-holding maneuvers. Techniques for reducing scan time with acceptable image quality, such as parallel imaging, compressed sensing, and cutting-edge deep learning techniques, have been developed to enable problem-solving strategies. Additionally, free-breathing techniques for dynamic contrast-enhanced imaging, such as extra-dimensional-volumetric interpolated breath-hold examination, golden-angle radial sparse parallel, and liver acceleration volume acquisition Star, can help patients with severe dyspnea or those under sedation to undergo abdominal MRI. We aimed to present various advanced abdominal MRI techniques for reducing the scan time while maintaining image quality and free-breathing techniques for dynamic imaging and illustrate cases using the techniques mentioned above. A review of these advanced techniques can assist in the appropriate interpretation of sequences.

An Improved Input Image Selection Algorithm for Super Resolution Still Image Reconstruction from Video Sequence (비디오 시퀀스로부터 고해상도 정지영상 복원을 위한 입력영상 선택 알고리즘)

  • Lee, Si-Kyoung;Cho, Hyo-Moon;Cho, Sang-Bok
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.1
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    • pp.18-23
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    • 2008
  • In this paper, we propose the input image selection-method to improve the reconstructed high-resolution (HR) image quality. To obtain ideal super-resolution (SR) reconstruction image, all input images are well-registered. However, the registration is not ideal in practice. Due to this reason, the selection of input images with low registration error (RE) is more important than the number of input images in order to obtain good quality of a HR image. The suitability of a candidate input image can be determined by using statistical and restricted registration properties. Therefore, we propose the proper candidate input Low Resolution(LR) image selection-method as a pre-processing for the SR reconstruction in automatic manner. In video sequences, all input images in specified region are allowed to use SR reconstruction as low-resolution input image and/or the reference image. The candidacy of an input LR image is decided by the threshold value and this threshold is calculated by using the maximum motion compensation error (MMCE) of the reference image. If the motion compensation error (MCE) of LR input image is in the range of 0 < MCE < MMCE then this LR input image is selected for SR reconstruction, else then LR input image are neglected. The optimal reference LR (ORLR) image is decided by comparing the number of the selected LR input (SLRI) images with each reference LR input (RLRI) image. Finally, we generate a HR image by using optimal reference LR image and selected LR images and by using the Hardie's interpolation method. This proposed algorithm is expected to improve the quality of SR without any user intervention.

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