一种三维非刚体图像运动重建算法改进设计

An Improved Design of 3D Non-rigid Image Motion Reconstruction Algorithm

传统三维非刚体图像运动重建算法直接对物体图像动态形心进行确定,未对三维形状进行预估与恢复,导致重建误差较大,效率较低。对此,研究三维非刚体图像运动重建改进方法,通过提取图像帧中的特征点计算三维特征和旋转矩阵,来分析动态形心的变化,可以精确地恢复物体的三维形状和运动轨迹。使用特征点演化和碰撞检测等方法确定物体图像的动态形心。物体图像的动态形心变化代表了物体的动态行为模式。通过对动态形心的变化进行建模和分析,可以提供更丰富和准确的动态行为表示,从而改进三维非刚体图像运动重建算法对物体动作的捕捉和描述。实验结果表明,采用该研究方法重建误差最小仅为2%,最短重建时间为0.234 75 s,具有实用性。

Traditional 3D non-rigid image motion reconstruction algorithms directly determine the dynamic centroid of object images without predicting and restoring the 3D shape,resulting in significant reconstruction errors and low efficiency.Therefore,an improved method for 3D non-rigid image motion reconstruction is studied.By extracting feature points from image frames and calculating 3D features and rotation matrices to analyze changes in dynamic centroids,the 3D shape and motion trajectory of objects can be accurately restored.Using methods such as feature point evolution and collision detection to determine the dynamic centroid of an object image.The dynamic centroid changes of object images represent the dynamic behavior patterns of the object.By modeling and analyzing the changes in dynamic centroids,a richer and more accurate representation of dynamic behavior can be provided,thereby improving the capture and description of object actions in 3D non-rigid image motion reconstruction algorithms.The experimental results show that the minimum reconstruction error using this research method is only 2%,and the shortest reconstruction time is 0.234 75s,which is practical.