Owing to the recent push toward efficient energy storage/conversion devices, fuel cells have become a strong candidate for energy conversion equipments. On the other hand, block copolymer polyelectrolytes are interest...Owing to the recent push toward efficient energy storage/conversion devices, fuel cells have become a strong candidate for energy conversion equipments. On the other hand, block copolymer polyelectrolytes are interesting materials for proton exchange membranes in fuel cells. Thus a considerable attention has been paid to the development of block copolymer polyelectrolyte membranes. In this study, the microdomains in block copolymer polyelectrolytes were controlled by external electric fields to develop high performance membranes with improved proton conductivity. The microdomain alignments in sulfonated polystyrene-b-hydrogenated poly butadiene-b-polystyrene block copolymer electrolyte were monitored by cross-sectional transmission electron microscopy analysis. The proton conductivities of the block copolymer electrolyte membranes were measured before and after exposure to electric field. In addition, the morphological features of the block copolymer electrolyte were observed with small angle x-ray scattering and atomic force microscopy.展开更多
Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilizatio...Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.展开更多
为自动识别视频中表情类别,提出基于面部块表情特征编码的视频表情识别方法框架。检测并精确定位视频中人脸关键点位置,以检测到的关键点为中心,提取面部显著特征块。沿着时间轴方向,对面部各特征块提取LBP-TOP(local binary pattern fr...为自动识别视频中表情类别,提出基于面部块表情特征编码的视频表情识别方法框架。检测并精确定位视频中人脸关键点位置,以检测到的关键点为中心,提取面部显著特征块。沿着时间轴方向,对面部各特征块提取LBP-TOP(local binary pattern from three orthogonal planes)动态特征描述子,将这些描述子作为表情特征并输入Adaboost分类器进行训练和识别,预测视频表情类型。在国际通用表情数据库BU-4DFE的纹理图像上进行测试,取得了81.2%的平均识别率,验证了所提算法的有效性,与同领域其它主流算法相比,其具有很强的竞争性。展开更多
为了提高分布式视频压缩感知(Distributed Video Compressive Sensing,DVCS)的率失真性能,文中提出根据视频非关键帧图像的时间相关性将帧内各块分为静止块与运动块两类,并对它们设定不同的测量率以提高压缩感知(Compressive Sensing,CS...为了提高分布式视频压缩感知(Distributed Video Compressive Sensing,DVCS)的率失真性能,文中提出根据视频非关键帧图像的时间相关性将帧内各块分为静止块与运动块两类,并对它们设定不同的测量率以提高压缩感知(Compressive Sensing,CS)捕获信息的效率。在重构过程中,提出运动对齐多假设预测模型进行重构,该预测模型在测量域内实现运动估计,并根据运动信息在参考帧内寻找到待重构块的若干候选匹配块,利用它们的线性加权和残差重构得到非关键帧图像的重构结果。仿真实验结果表明,文中所提出的DVCS重构算法能有效提升系统的率失真性能,与现有方法相比,在重构时间基本不变的情况下,获得更好的主客观视频重构质量。展开更多
文摘Owing to the recent push toward efficient energy storage/conversion devices, fuel cells have become a strong candidate for energy conversion equipments. On the other hand, block copolymer polyelectrolytes are interesting materials for proton exchange membranes in fuel cells. Thus a considerable attention has been paid to the development of block copolymer polyelectrolyte membranes. In this study, the microdomains in block copolymer polyelectrolytes were controlled by external electric fields to develop high performance membranes with improved proton conductivity. The microdomain alignments in sulfonated polystyrene-b-hydrogenated poly butadiene-b-polystyrene block copolymer electrolyte were monitored by cross-sectional transmission electron microscopy analysis. The proton conductivities of the block copolymer electrolyte membranes were measured before and after exposure to electric field. In addition, the morphological features of the block copolymer electrolyte were observed with small angle x-ray scattering and atomic force microscopy.
文摘Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.
文摘为自动识别视频中表情类别,提出基于面部块表情特征编码的视频表情识别方法框架。检测并精确定位视频中人脸关键点位置,以检测到的关键点为中心,提取面部显著特征块。沿着时间轴方向,对面部各特征块提取LBP-TOP(local binary pattern from three orthogonal planes)动态特征描述子,将这些描述子作为表情特征并输入Adaboost分类器进行训练和识别,预测视频表情类型。在国际通用表情数据库BU-4DFE的纹理图像上进行测试,取得了81.2%的平均识别率,验证了所提算法的有效性,与同领域其它主流算法相比,其具有很强的竞争性。
文摘为了提高分布式视频压缩感知(Distributed Video Compressive Sensing,DVCS)的率失真性能,文中提出根据视频非关键帧图像的时间相关性将帧内各块分为静止块与运动块两类,并对它们设定不同的测量率以提高压缩感知(Compressive Sensing,CS)捕获信息的效率。在重构过程中,提出运动对齐多假设预测模型进行重构,该预测模型在测量域内实现运动估计,并根据运动信息在参考帧内寻找到待重构块的若干候选匹配块,利用它们的线性加权和残差重构得到非关键帧图像的重构结果。仿真实验结果表明,文中所提出的DVCS重构算法能有效提升系统的率失真性能,与现有方法相比,在重构时间基本不变的情况下,获得更好的主客观视频重构质量。
