机译:使用2D和3D梯度自相关特征的加权融合从深度序列进行动作识别
Univ Texas Dallas, Dept Elect Engn, Richardson, TX 75080 USA;
Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China;
Changzhou Univ, Sch Informat Sci & Engn, Changzhou, Peoples R China;
China Univ Geosci, Sch Comp Sci, Wuhan, Peoples R China;
Peking Univ, Shenzhen Grad Sch, Engn Lab Intelligent Percept Internet Things ELIP, Shenzhen, Peoples R China;
Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China;
Action recognition; Depth data; Depth motion maps; Gradient local autocorrelations; Space-time auto-correlation of gradients; Extreme learning machine; Weighted fusion;
机译:颈椎的磁共振成像:比较2D T2加权涡轮旋转回波,2D T2 *加权梯度调用回波和3D T2加权可变翻转角涡轮旋转回波序列。
机译:颈椎磁共振成像:比较2D T2加权涡轮旋转回波,2D T2 *加权梯度调用回波和3D T2加权可变翻转角涡轮旋转回波序列
机译:具有径向3D采样方法的T1加权梯度回忆回忆(GRE)序列的优点与头部和颈部MRI的2D Turbo Sppo-Echo和Cartesian 3D Gre序列
机译:使用多尺度子动作深度运动图和时空梯度局部自相关的基于深度的动作识别
机译:在2D到立体3D转换的无约束图像和视频序列中半自动深度图生成。
机译:基于面向梯度的特征融合的直方图用于行动视频序列中的人体行动识别
机译:深度人类行动识别的梯度本地自动相关特征