• Title/Summary/Keyword: Prediction unit

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Fast Prediction Unit Decision Using Quantized Transform Coefficient (양자화된 트랜스폼 계수를 이용한 고속 Prediction Unit 결정방법)

  • Gweon, Ryeong-Hee;Lee, Yung-Lyul
    • Journal of Broadcast Engineering
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    • v.17 no.5
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    • pp.725-733
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    • 2012
  • MPEG and VCEG have constituted a collaboration team called JCT-VC(Joint Collaborative Team on Video Coding) and have been developing the HEVC(High Efficiency Video Coding) standard. The next generation video coding standard HEVC shows higher compression rate compared with the H.264/AVC standard, but the encoder computational complexity of the HEVC encoder is significantly high. In order to reduce this computational complexity in the HEVC encoder, a fast prediction unit decision is proposed. The proposed fast prediction unit decision method reduces the encoder complexity by skipping the remaining prediction units if the current prediction unit does not have any non-zero quantized transform coefficient. The proposed method reduces the encoder computational complexity by 50.3% comparing with HM6.0 but it maintains the same level of coding efficiency.

Evaluation of Maximum Dry Unit Weight Prediction Model Using Deep Neural Network Based on Particle Size Analysis (입도분석에 기반한 Deep Neural Network를 이용한 최대 건조 단위중량 예측 모델 평가)

  • Kim, Myeong Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.65 no.3
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    • pp.15-28
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    • 2023
  • The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R2 of 0.70 or more, and DNN analysis showed R2 of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.

HEVC Coding Unit Mode Based Motion Frame Analysis

  • Jia, Qiong;Dong, Tianyu;Jang, Euee S.
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2021.06a
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    • pp.52-54
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    • 2021
  • In this paper we propose a method predict whether a video frame contains motion according to the invoking situation of the coding unit mode in HEVC. The motion prediction of video frames is conducive for use in video compression and video data extraction. In the existing technology, motion prediction is usually performed by high complexity computer vision technology. However, we proposed to analyze the motion frame based on HEVC coding unit mode which does not need to use the static background frame. And the prediction accuracy rate of motion frame analysis by our method has exceeded 80%.

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Design of an Instruction Fetch Unit for RAPTOR, a On-Chip Multiprocessor (RAPTOR의 명령어 페치 유닛 설계)

  • 이성권;오형철이상원한우종
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.767-770
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    • 1998
  • This paper introduces an instruction fetch unit which is designed for RAPTOR, an on-chip multiprocessor. In order to reduce control hazards, the proposed fetch unit supports a hybrid branch prediction scheme which consists of a static scheme and the 2bC branch prediction scheme. The fetch unit also utilizes the branch folding technique with two instruction buffers to avoid the branch penalty caused by imspredictions. Instructions are predecoded in the fetch unit to achieve extra performance gain.

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Whole Frame Error Concealment with an Adaptive PU-based Motion Vector Extrapolation for HEVC

  • Kim, Seounghwi;Lee, Dongkyu;Oh, Seoung-Jun
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.1
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    • pp.16-21
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    • 2015
  • Most video services are transmitted in wireless networks. In a network environment, a packet of video is likely to be lost during transmission. For this reason, numerous error concealment (EC) algorithms have been proposed to combat channel errors. On the other hand, most existing algorithms cannot conceal the whole missing frame effectively. To resolve this problem, this paper proposes a new Adaptive Prediction Unit-based Motion Vector Extrapolation (APMVE) algorithm to restore the entire missing frame encoded by High Efficiency Video Coding (HEVC). In each missing HEVC frame, it uses the prediction unit (PU) information of the previous frame to adaptively decide the size of a basic unit for error concealment and to provide a more accurate estimation for the motion vector in that basic unit than can be achieved by any other conventional method. The simulation results showed that it is highly effective and significantly outperforms other existing frame recovery methods in terms of both objective and subjective quality.

Multi-modal Pedestrian Trajectory Prediction based on Pedestrian Intention for Intelligent Vehicle

  • Youguo He;Yizhi Sun;Yingfeng Cai;Chaochun Yuan;Jie Shen;Liwei Tian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.6
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    • pp.1562-1582
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    • 2024
  • The prediction of pedestrian trajectory is conducive to reducing traffic accidents and protecting pedestrian safety, which is crucial to the task of intelligent driving. The existing methods mainly use the past pedestrian trajectory to predict the future deterministic pedestrian trajectory, ignoring pedestrian intention and trajectory diversity. This paper proposes a multi-modal trajectory prediction model that introduces pedestrian intention. Unlike previous work, our model makes multi-modal goal-conditioned trajectory pedestrian prediction based on the past pedestrian trajectory and pedestrian intention. At the same time, we propose a novel Gate Recurrent Unit (GRU) to process intention information dynamically. Compared with traditional GRU, our GRU adds an intention unit and an intention gate, in which the intention unit is used to dynamically process pedestrian intention, and the intention gate is used to control the intensity of intention information. The experimental results on two first-person traffic datasets (JAAD and PIE) show that our model is superior to the most advanced methods (Improved by 30.4% on MSE0.5s and 9.8% on MSE1.5s for the PIE dataset; Improved by 15.8% on MSE0.5s and 13.5% on MSE1.5s for the JAAD dataset). Our multi-modal trajectory prediction model combines pedestrian intention that varies at each prediction time step and can more comprehensively consider the diversity of pedestrian trajectories. Our method, validated through experiments, proves to be highly effective in pedestrian trajectory prediction tasks, contributing to improving traffic safety and the reliability of intelligent driving systems.

Prototype 모델 MDU의 신뢰도 예측

  • Kim, Joon-Yun;Jung, Hae-Seung;Lee, Jae-Deuk
    • Aerospace Engineering and Technology
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    • v.4 no.1
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    • pp.203-210
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    • 2005
  • Prototype model of MDU(Master Data Unit), to be employed on KSLV-I, has been developed and tested being interfaced with other units. Before stepping into the development of engineering and flight model phases, we have carried out reliability prediction of prototype MDU in order to assure availability of the unit. This paper describes the method of reliability prediction of prototype MDU and prediction results based on MIL-HDBK-217F, 'Electronic Reliability Design Handbook'.

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An Experimental Study on Prediction of Unit-Water Content of Cement Paste Using Ultrasonic Equipment (초음파 장비를 활용한 시멘트 페이스트 단위수량 예측에 관한 실험적 연구)

  • Cho, Yang-Je;Lee, Han-Seung
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2020.06a
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    • pp.33-34
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    • 2020
  • Unit-water content is an element directly related to durability and unit-water content of concrete used at construction site has a great effect on the durability of construction structure. Many methods are being discussed for more convenient and accurate measurements of unit-water content. Therefore, an experimental study was conducted on the prediction of unit-water content using ultrasonic equipment. Depending on the amount of cement in cement paste, the speed of ultrasonic waves varies and the experiment will be carried out using the same reception sensitivity in the future.

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Design of Intra Prediction Circuit for H.264 Decoder Sharing Common Operations Unit (공통연산부를 공유하는 H.264 디코더용 인트라 예측 회로 설계)

  • Shim, Jae-Oh;Lee, Seon-Young;Cho, Kyeong-Soon
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.45 no.9
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    • pp.103-109
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    • 2008
  • This paper presents the architecture and design of intra prediction circuit for H.264 decoder. There are a total of 17 operational modes in the intra prediction of H.264- nine modes for a luma $4\times4$ block, four modes for a luma $16\times16$ block and four modes for a chroma $8\times8$ block. We extracted common operations included in all prediction modes and defined the common operations unit to perform those operations. The proposed circuit architecture sharing this unit in all prediction modes is systematic from the design point of view and efficient in terms of circuit size.

Whole Frame Error Concealment with an Adaptive PU-based Motion Vector Extrapolation and Boundary Matching (적응적인 PU 기반 움직임 벡터 외삽과 경계 정합을 통한 프레임 전체 오류 은닉 방법에 관한 연구)

  • Kim, Seounghwi;Lee, Dongkyu;Oh, Seoung-Jun
    • Journal of Broadcast Engineering
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    • v.20 no.4
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    • pp.533-544
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    • 2015
  • Recently, most of the video services are usually transmitted in wireless networks. In networks environment, a packet of video is likely to be lost during transmission. For this reason, this paper proposes a new Error Concealment (EC) algorithm. For High Efficiency Video Coding (HEVC) bitstreams, the proposed algorithm includes Adaptive Prediction Unit-based Motion Vector Extrapolation (APMVE) and Boundary Matching (BM) algorithm, which employs both the temporal and spatial correlation. APMVE adaptively decides a Error Concealment Basic Unit (ECBU) by using the PU information of the previous frame and BM employing the spatial correlation is applied to only unreliable blocks. Simulation results show that the proposed algorithm provides the higher subjective quality by reducing blocking artifacts which appear in other existing algorithms.