分层运动估计

R.J. Schutten, A. Pelagotti, G. De Haan
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引用次数: 8

摘要

提出了一种分层运动估计算法,允许准同时运动估计/分割达到固定的最大层数。估计结果是每层一个运动参数集,以及一个分割映射,将这些集分配给图像的不同部分(运动层)。在一个层中的运动是建模最多四个参数能够描述平移,倾斜和缩放。这个概念显示了一些层次结构,即运动层的排序。这样,关于一层的运动参数估计排除了由层次结构中排名较高的层描述的图像的那些部分,并且不受层次结构中排名较低的层更好地描述的图像部分的污染。这个概念导致了非常低的操作计数。即使在关键扫描速率转换应用中,特别是在图像速率上转换中,它也表现良好。一个包含三层的变体计划在飞利浦TriMedia处理器上实时运行。
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Layered motion estimation

A layered motion estimation algorithm is proposed that permits quasisimultaneous motion estimation/segmentation up to a fixed maximum number of layers. The estimation results in one motion parameter set per layer, and a segmentation map that assigns these sets to different parts of the image (motion layers). Motion in a layer is modelled with at maximum four parameters capable of describing pan, tilt and zoom. The concept shows some hierarchy, i.e. a ranking of the motion layers. In this way the motion parameter estimation concerning one layer excludes those parts of the image that have been described by a layer ranked higher in the hierarchy and are not polluted by parts of the image that are better described by layers ranked lower in the hierarchy. The concept results in a very low operations count. It has been shown to perform well even in critical scan rate conversion applications, particularly in picture rate up-conversion. A variant including three layers has been scheduled to run in real-time on a Philips TriMedia processor.

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