• Title/Summary/Keyword: Motion prediction flag

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An Efficient coding Method for Motion Prediction Flag in the Scalable Video Encoding Standard (스케일러블 동영상 부호화 표준에서 움직임 예측 플래그를 위한 효율적인 부호화 방식)

  • Moon, Yong-Ho;Eom, Il-Kyu;Ha, Seok-Wun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.2
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    • pp.81-86
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    • 2014
  • In the scalable video coding standard, inter-layer prediction based on the coding information of the base layer was adopted to increase the coding performance. This prediction tool results in new syntax elements called motion_prediction_flag (mPF) and residul_prediction_flag(rPF), which are carried to notify the motion vector predictor (MVP) and reference block required in the motion compensation of the decoder. In this paper, an efficient coding method for mPF is proposed to enhance coding efficiency of the salable video coding standard. Through an analysis on the transmission of mPF based on the relationship between the MVPs, we discover the conditions where mPF is unnecessary at the decoder and suggest a modified rate-distortion (RD) cost function to make RD optimization more effective. Simulation results show that the proposed method offers BD rate savings of approximately 1.4%, compared with the conventional SVC standard.

Prediction of Energy Harvesting Efficiency of an Inverted Flag Using Machine Learning Algorithms (머신 러닝 알고리즘을 이용한 역방향 깃발의 에너지 하베스팅 효율 예측)

  • Lim, Sehwan;Park, Sung Goon
    • Journal of the Korean Society of Visualization
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    • v.19 no.3
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    • pp.31-38
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    • 2021
  • The energy harvesting system using an inverted flag is analyzed by using an immersed boundary method to consider the fluid and solid interaction. The inverted flag flutters at a lower critical velocity than a conventional flag. A fluttering motion is classified into straight, symmetric, asymmetric, biased, and over flapping modes. The optimal energy harvesting efficiency is observed at the biased flapping mode. Using the three different machine learning algorithms, i.e., artificial neural network, random forest, support vector regression, the energy harvesting efficiency is predicted by taking bending rigidity, inclination angle, and flapping frequency as input variables. The R2 value of the artificial neural network and random forest algorithms is observed to be more than 0.9.

Adaptive coding method of MVP candidate flag by redundancy check among AMVP candidates in HEVC (HEVC의 화면 간 예측에서 AMVP 후보의 중복성 확인을 통한 적응적인 MVP Flag 코딩 방법)

  • Won, Dong-jae;Lim, Sung-won;Moon, Joo-hee
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2014.11a
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    • pp.180-181
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    • 2014
  • 현재 HEVC의 AMVP(Adaptive Motion Vector Prediction) 모드에서는 공간적, 시간적 후보를 고려하여 최종 후보 2개를 결정 한 후 어떤 후보를 사용하였는지 MVP flag를 이용하여 디코더로 알려준다. 이때, 최종 2개의 후보가 동일하다면 AMVP의 성능이 저하 될 수 있다. 따라서 본 논문에서는 그러한 경우를 고려하여 개선된 알고리즘을 제안한다. 실험결과는 휘도 기준 최대 -0.5%의 성능이 나오며 제안된 알고리즘이 효율적임을 보여준다.

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Motion Estimation and Coding Technique using Adaptive Motion Vector Resolution in HEVC (HEVC에서의 적응적 움직임 벡터 해상도를 이용한 움직임 추정 및 부호화 기법)

  • Lim, Sung-Won;Lee, Ju Ock;Moon, Joo-Hee
    • Journal of Broadcast Engineering
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    • v.17 no.6
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    • pp.1029-1039
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    • 2012
  • In this papar, we propose a new motion estimation and coding technique using adaptive motion vector resolution. Currently, HEVC encodes a video using 1/4 motion vector resolution. If there are high texture regions in a picture, HEVC can't get a performance enough. So, we insert additional 1-bit flag meaning whether motion vector resolution is 1/4 or 1/8 in PU syntax. Therefore, decoder can recognize the transmitted motion vector resolution. Experimental results show that maximum coding efficiency gain of the proposed method is up to 5.3% in luminance and 7.9% in chrominance. Average computional time complexity is increased about 33% in encoder and up to 5% in decoder.