The Experts below are selected from a list of 15264 Experts worldwide ranked by ideXlab platform

Yan Zhang - One of the best experts on this subject based on the ideXlab platform.

  • fast multiview video coding using adaptive prediction structure and Hierarchical Mode decision
    IEEE Transactions on Circuits and Systems for Video Technology, 2014
    Co-Authors: Huanqiang Zeng, Xiaolan Wang, Jing Chen, Yan Zhang
    Abstract:

    The multiview video coding (MVC) adopts Hierarchical B picture prediction structure and offers many prediction Modes to effectively remove the spatial, temporal, and inter-view redundancies inherited in multiview video (MVV), but at the price of extremely high computational complexity. To address this problem, a fast MVC method by jointly using adaptive prediction structure (APS) and Hierarchical Mode decision (HMD) is proposed in this paper. The complexity reduction is achieved by: 1) designing four APSs for different MVV contents based on the fact that the contribution of the inter-view prediction varies from sequence to sequence and 2) developing an HMD scheme based on the observation that the relationship between the rate distortion (RD) cost and size of prediction Mode is a unimodal function. In particular, for the current group of picture of the input MVV, the prediction structure is adaptively selected based on its characteristic, which is measured by the ratio of the average RD cost of the base view frames to the sum of the average RD cost of the base view frames and that of anchor frames in nonbase views, and then an HMD scheme is further performed to skip the checking process of those unlikely Modes. The experimental results have shown that compared with the exhaustive Mode decision in the MVC, the proposed algorithm achieves a reduction of the computational complexity by 83.49% on average, whereas incurring only a 0.086 dB loss in Bjontegaard delta peak signal-to-noise ratio and 2.97% increment on the total Bjontegaard delta bit rate.

Huanqiang Zeng - One of the best experts on this subject based on the ideXlab platform.

  • fast multiview video coding using adaptive prediction structure and Hierarchical Mode decision
    IEEE Transactions on Circuits and Systems for Video Technology, 2014
    Co-Authors: Huanqiang Zeng, Xiaolan Wang, Jing Chen, Yan Zhang
    Abstract:

    The multiview video coding (MVC) adopts Hierarchical B picture prediction structure and offers many prediction Modes to effectively remove the spatial, temporal, and inter-view redundancies inherited in multiview video (MVV), but at the price of extremely high computational complexity. To address this problem, a fast MVC method by jointly using adaptive prediction structure (APS) and Hierarchical Mode decision (HMD) is proposed in this paper. The complexity reduction is achieved by: 1) designing four APSs for different MVV contents based on the fact that the contribution of the inter-view prediction varies from sequence to sequence and 2) developing an HMD scheme based on the observation that the relationship between the rate distortion (RD) cost and size of prediction Mode is a unimodal function. In particular, for the current group of picture of the input MVV, the prediction structure is adaptively selected based on its characteristic, which is measured by the ratio of the average RD cost of the base view frames to the sum of the average RD cost of the base view frames and that of anchor frames in nonbase views, and then an HMD scheme is further performed to skip the checking process of those unlikely Modes. The experimental results have shown that compared with the exhaustive Mode decision in the MVC, the proposed algorithm achieves a reduction of the computational complexity by 83.49% on average, whereas incurring only a 0.086 dB loss in Bjontegaard delta peak signal-to-noise ratio and 2.97% increment on the total Bjontegaard delta bit rate.

Xiaolan Wang - One of the best experts on this subject based on the ideXlab platform.

  • fast multiview video coding using adaptive prediction structure and Hierarchical Mode decision
    IEEE Transactions on Circuits and Systems for Video Technology, 2014
    Co-Authors: Huanqiang Zeng, Xiaolan Wang, Jing Chen, Yan Zhang
    Abstract:

    The multiview video coding (MVC) adopts Hierarchical B picture prediction structure and offers many prediction Modes to effectively remove the spatial, temporal, and inter-view redundancies inherited in multiview video (MVV), but at the price of extremely high computational complexity. To address this problem, a fast MVC method by jointly using adaptive prediction structure (APS) and Hierarchical Mode decision (HMD) is proposed in this paper. The complexity reduction is achieved by: 1) designing four APSs for different MVV contents based on the fact that the contribution of the inter-view prediction varies from sequence to sequence and 2) developing an HMD scheme based on the observation that the relationship between the rate distortion (RD) cost and size of prediction Mode is a unimodal function. In particular, for the current group of picture of the input MVV, the prediction structure is adaptively selected based on its characteristic, which is measured by the ratio of the average RD cost of the base view frames to the sum of the average RD cost of the base view frames and that of anchor frames in nonbase views, and then an HMD scheme is further performed to skip the checking process of those unlikely Modes. The experimental results have shown that compared with the exhaustive Mode decision in the MVC, the proposed algorithm achieves a reduction of the computational complexity by 83.49% on average, whereas incurring only a 0.086 dB loss in Bjontegaard delta peak signal-to-noise ratio and 2.97% increment on the total Bjontegaard delta bit rate.

Jing Chen - One of the best experts on this subject based on the ideXlab platform.

  • fast multiview video coding using adaptive prediction structure and Hierarchical Mode decision
    IEEE Transactions on Circuits and Systems for Video Technology, 2014
    Co-Authors: Huanqiang Zeng, Xiaolan Wang, Jing Chen, Yan Zhang
    Abstract:

    The multiview video coding (MVC) adopts Hierarchical B picture prediction structure and offers many prediction Modes to effectively remove the spatial, temporal, and inter-view redundancies inherited in multiview video (MVV), but at the price of extremely high computational complexity. To address this problem, a fast MVC method by jointly using adaptive prediction structure (APS) and Hierarchical Mode decision (HMD) is proposed in this paper. The complexity reduction is achieved by: 1) designing four APSs for different MVV contents based on the fact that the contribution of the inter-view prediction varies from sequence to sequence and 2) developing an HMD scheme based on the observation that the relationship between the rate distortion (RD) cost and size of prediction Mode is a unimodal function. In particular, for the current group of picture of the input MVV, the prediction structure is adaptively selected based on its characteristic, which is measured by the ratio of the average RD cost of the base view frames to the sum of the average RD cost of the base view frames and that of anchor frames in nonbase views, and then an HMD scheme is further performed to skip the checking process of those unlikely Modes. The experimental results have shown that compared with the exhaustive Mode decision in the MVC, the proposed algorithm achieves a reduction of the computational complexity by 83.49% on average, whereas incurring only a 0.086 dB loss in Bjontegaard delta peak signal-to-noise ratio and 2.97% increment on the total Bjontegaard delta bit rate.

Chao Yang - One of the best experts on this subject based on the ideXlab platform.

  • a robust h control based Hierarchical Mode transition control system for plug in hybrid electric vehicle
    Mechanical Systems and Signal Processing, 2018
    Co-Authors: Chao Yang, Xiaohong Jiao, Yuanbo Zhang, Zheng Chen
    Abstract:

    Abstract To realize a fast and smooth operating Mode transition process from electric driving Mode to engine-on driving Mode, this paper presents a novel robust Hierarchical Mode transition control method for a plug-in hybrid electric bus (PHEB) with pre-transmission parallel hybrid powertrain. Firstly, the Mode transition process is divided into five stages to clearly describe the powertrain dynamics. Based on the dynamics Models of powertrain and clutch actuating mechanism, a Hierarchical control structure including two robust H ∞ controllers in both upper layer and lower layer is proposed. In upper layer, the demand clutch torque can be calculated by a robust H ∞ controller considering the clutch engaging time and the vehicle jerk. While in lower layer a robust tracking controller with L 2 -gain is designed to perform the accurate position tracking control, especially when the parameters uncertainties and external disturbance occur in the clutch actuating mechanism. Simulation and hardware-in-the-loop (HIL) test are carried out in a traditional driving condition of PHEB. Results show that the proposed Hierarchical control approach can obtain the good control performance: Mode transition time is greatly reduced with the acceptable jerk. Meanwhile, the designed control system shows the obvious robustness with the uncertain parameters and disturbance. Therefore, the proposed approach may offer a theoretical reference for the actual vehicle controller.