摘要
确定被视察物体和摄像机之间的三维相对运动是计算机视觉领域的一个重要课题。假定物体上有若干特征点,它们在空间的位置已由双目视觉求得。在此假定下,本文讨论如何由特征点空间位置的观察值来估计运动参数。现有文献中所用的目标函数导致的是一个非线性最优化问题。本文利用凯莱(Cayley)定理提出一种新的目标函数,它导致的是一个十分简单的线性最小二乘问题。文中还讨论了这两种目标函数之间的关系。
Determining the 3-D relative motion between the camera and the viewed object is an important topic in the field of computer vision. Assume that there are some feature points on the object and their positions in space have been recovered by the stereo vision, this paper discusses how to estimate the motion parameters from the observed position vectors of the feature points. The objective function available in the literatures lead to a nonlinear optimization problem. A new objective function based on the Cayley's theorem is presented in this paper. The relationship between the two objective functions is also discussed.
出处
《自动化学报》
EI
CSCD
北大核心
1992年第4期440-447,共8页
Acta Automatica Sinica
基金
国家教委
清华大学资助
关键词
参数估计
机器视觉
Computer vision
3-D motion
quaternion
RS decomposition
Cayley's formula
