Abstract: Most image coding algorithms, like the P $MUL 64 and MPEG-1 standards, use locally derived estimates of object motion to form a prediction of the current frame. But camera motion, such as zooms and pans, which systemically affect the entire frame, is seldom handled efficiently. In this paper, we study the modeling, estimation and compensation of global motion caused by camera zooms and pans, we model the global motion in each frame with just two parameters: a scalar zoom factor and a 2D pan vector. Parameter estimation minimizes the squared prediction error of either the difference frame or the optical flow field. The estimated parameters are then used to construct a zoom/pan compensated prediction of the current frame, upon which some local motion compensation algorithm can then be applied to model object motion. Simulations suggest that these two global motion estimation algorithms are robust and accurate, and that global motion compensation provides a better prediction of the current frame with a potentially large reduction of motion side information.!
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机译：摘要：大多数图像编码算法，例如P $ MUL 64和MPEG-1标准，都使用对象运动的本地估计来形成当前帧的预测。但是，很少有效地处理相机运动，例如缩放和平移，这种运动会系统地影响整个帧。在本文中，我们研究了由相机变焦和摇摄引起的全局运动的建模，估计和补偿，我们仅使用两个参数对每个帧中的全局运动进行建模：标量缩放因子和2D摇摄矢量。参数估计可最大程度减少差异帧或光流场的平方预测误差。然后，将估计的参数用于构造当前帧的缩放/平移补偿预测，然后可以将某些局部运动补偿算法应用于模型对象运动。仿真表明，这两种全局运动估计算法是鲁棒且准确的，并且全局运动补偿可提供对当前帧的更好预测，并可能大大减少运动辅助信息。
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