增强现实中非刚性物体的虚实配准方法  

Non-rigid Registration Using AAM and Factorization Method for Augmented Reality Applications

作　　者：刘莉[1] 

机构地区：[1]洪山区武警武汉指挥学院信息技术教研室,湖北省武汉市430064

出　　处：《微计算机信息》2010年第27期137-139,164,共4页Control & Automation

摘　　要：本文提出一种基于AAM及因式分解法的非刚性物体虚实配准方法。该方法分为两个步骤:(1)离线阶段。利用AAM获得训练数据,然后利用因式分解法从图像序列中构建物体的三维形状基组。(2)在线阶段。给定初始的形状系数和旋转矩阵,由三维基本形状基组的线性组合得到非刚性物体在世界坐标系下的三维坐标,然后利用Levenberg-Marquardt优化算法求得摄像机的旋转矩阵和平移矩阵,从而实现非刚性物体的虚实配准。实验结果表明,该方法在增强现实的应用中是可行有效的。This paper presents a novel non-rigid registration method for augmented reality applications using AAM and factorization method. The method can be divided into two stages： offline construction of 3D shape basis and online estimation of the 3D pose parameters together with the 3D shape coefficients. In offline stage, we get the training data with the use of the AAM algorithm, then we use factorization method to obtain the object 3D shape basis set from image sequences. In online stage, given an initial 3D shape coefficients and the rotation matrix, we can get the non-rigid object coordinates under the world coordinate systems by projecting the 3D points which are the linear combination of the 3D shape basis to the 2D image. Then we use Levenberg-Marquardt algorithm to optimize the 3D shape coefficients and the 3D pose parameters simultaneously. Some experimental results demonstrate this method is effective and useful for augmented reality applications.

关 键 词：增强现实 计算机视觉 配准 因式分解法 AMM 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]