• Title/Summary/Keyword: ultra wide viewing video

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Tile, Slice, and Deblocking Filter Parallelization Method in HEVC (HEVC 복호기에서의 타일, 슬라이스, 디블록킹 필터 병렬화 방법)

  • Son, Sohee;Baek, Aram;Choi, Haechul
    • Journal of Broadcast Engineering
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    • v.22 no.4
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    • pp.484-495
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    • 2017
  • The development of display devices and the increase of network transmission bandwidth bring demands for over 2K high resolution video such as panorama video, 4K ultra-high definition commercial broadcasting, and ultra-wide viewing video. To compress these image sequences with significant amount of data, High Efficiency Video Coding (HEVC) standard with the highest coding efficiency is a promising solution. HEVC, the latest video coding standard, provides high encoding efficiency using various advanced encoding tools, but it also requires significant amounts of computation complexity compared to previous coding standards. In particular, the complexity of HEVC decoding process is a imposing challenges on real-time playback of ultra-high resolution video. To accelerate the HEVC decoding process for ultra high resolution video, this paper introduces a data-level parallel video decoding method using slice and/or tile supported by HEVC. Moreover, deblocking filter process is further parallelized. The proposed method distributes independent decoding operations of each tile and/or each slice to multiple threads as well as deblocking filter operations. The experimental results show that the proposed method facilitates executions up to 2.0 times faster than the HEVC reference software for 4K videos.

Study on 3 DoF Image and Video Stitching Using Sensed Data

  • Kim, Minwoo;Chun, Jonghoon;Kim, Sang-Kyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4527-4548
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    • 2017
  • This paper proposes a method to generate panoramic images by combining conventional feature extraction algorithms (e.g., SIFT, SURF, MPEG-7 CDVS) with sensed data from inertia sensors to enhance the stitching results. The challenge of image stitching increases when the images are taken from two different mobile phones with no posture calibration. Using inertia sensor data obtained by the mobile phone, images with different yaw, pitch, and roll angles are preprocessed and adjusted before performing stitching process. Performance of stitching (e.g., feature extraction time, inlier point numbers, stitching accuracy) between conventional feature extraction algorithms is reported along with the stitching performance with/without using the inertia sensor data. In addition, the stitching accuracy of video data was improved using the same sensed data, with discrete calculation of homograph matrix. The experimental results for stitching accuracies and speed using sensed data are presented in this paper.

HEVC Encoding Method and Problem Analysis for Independent Tile Decoding (타일의 독립적 복호를 위한 HEVC 부호화 방법 및 문제점 분석)

  • Gwon, Daehyeok;Beak, Aram;Choi, Haechul
    • Journal of Broadcast Engineering
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    • v.22 no.6
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    • pp.765-773
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    • 2017
  • Ultra-high definition videos, panorama contents, and ultra-wide viewing videos have a huge spatial resolution. However, a whole region of images is not always interesting to viewers due to limitations of system resources and display devices. To allow one or more interesting tiles to be decoded freely without decoding other tiles, this paper introduces a tile-based independent coding method. The propose method restraints motion vectors to be within a tile region shifting motion search area and modifying an initial motion vector. Experiments results show that any desired tile is capable to be decoded independently of other tiles.

Enhancement on 3 DoF Image Stitching Using Inertia Sensor Data (관성 센서 데이터를 활용한 3 DoF 이미지 스티칭 향상)

  • Kim, Minwoo;Kim, Sang-Kyun
    • Journal of Broadcast Engineering
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    • v.22 no.1
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    • pp.51-61
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    • 2017
  • This paper proposes a method to generate panoramic images by combining conventional feature extraction algorithms (e.g., SIFT, SURF, MPEG-7 CDVS) with sensed data from an inertia sensor to enhance the stitching results. The challenge of image stitching increases when the images are taken from two different mobile phones with no posture calibration. Using inertia sensor data obtained by the mobile phone, images with different yaw angles, pitch angles, roll angles are preprocessed and adjusted before performing stitching process. Performance of stitching (e.g., feature extraction time, inlier point numbers, stitching accuracy) between conventional feature extraction algorithms is reported along with the stitching performance with/without using the inertia sensor data.