用迭代最小二乘法求解使用局部运动矢量和运动模型建立的线性参数系统获得全局平移、旋转及缩放运动参数。
Then a linear system is constructed from these local motion vectors and solved to determine the global motion parameters which are refined by the motion iteration process.
该算法把惯性权重和学习因子分别通过结合全局和局部最优最小值来进行改写，速度更新公式也做了相应的简化。
The inertia weight and the acceleration coefficient of the algorithm were both adapted by the global best and the local best minimum (GLBM). The velocity equation of the GLBM-PSO was also simplified.
由于本文提出的角特征不随旋转、平移和尺度的变化而变化，所以配准最终收敛到全局最小值，而不是局部最小值。
Because the proposed angular feature is invariant to rotation, translation and scale transformation, the registration result will converge to global minimization rather than local one.
由于本文提出的角特征不随旋转、平移和尺度的变化而变化，所以配准最终收敛到全局最小值，而不是局部最小值。
Because the proposed angular feature is invariant to rotation, translation and scale transformation, the registration result will converge to global minimization rather than local one.
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