论文标题
通过Beltrami描述符的纵向变形的分解
Decomposition of Longitudinal Deformations via Beltrami Descriptors
论文作者
论文摘要
我们提出了一个数学模型，将纵向变形分解为正常和异常成分。目的是从视频序列中的周期性动作中检测和提取微妙的颤抖。它在医学图像分析中具有重要的应用。为了实现这一目标，我们考虑了基于准文献理论的纵向变形的表示，称为Beltrami描述符。 Beltrami描述符是一个复杂值的矩阵。每个纵向变形都与Beltrami描述符相关，反之亦然。为了分解纵向变形，我们建议进行Beltrami描述符的低等级和稀疏分解。低等级分量对应于周期性运动，而稀疏部分对应于纵向变形的异常运动。在合成和真实视频序列上都进行了实验。结果证明了我们提出的模型将纵向变形分解为规则和不规则成分的功效。
We present a mathematical model to decompose a longitudinal deformation into normal and abnormal components. The goal is to detect and extract subtle quivers from periodic motions in a video sequence. It has important applications in medical image analysis. To achieve this goal, we consider a representation of the longitudinal deformation, called the Beltrami descriptor, based on quasiconformal theories. The Beltrami descriptor is a complex-valued matrix. Each longitudinal deformation is associated to a Beltrami descriptor and vice versa. To decompose the longitudinal deformation, we propose to carry out the low rank and sparse decomposition of the Beltrami descriptor. The low rank component corresponds to the periodic motions, whereas the sparse part corresponds to the abnormal motions of a longitudinal deformation. Experiments have been carried out on both synthetic and real video sequences. Results demonstrate the efficacy of our proposed model to decompose a longitudinal deformation into regular and irregular components.
