Two stage motion-based region merging algorithm for content-based coding

Kun-Woen Song, Ho-Young Lee
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引用次数: 5

Abstract

We propose a two stage motion-based region merging algorithm for content-based coding. It uses a six-parameter motion model and the change image obtained from the conventional change detector. First, the type of each region is decided as one of an object, background and uncertain region using the change image. In the first region merging stage, all pairs of two adjacent object regions and two adjacent regions are extracted. Affine motion model parameters for each pair are computed. Then, the merging for one pair that has the smallest error is performed for each type. In particular a large threshold value is used to efficiently merge many redundant regions segmented in the background. In the second region merging stage, the merging for the adjacent uncertain regions or adjacent regions of different types are performed with the same procedure as that of the first stage. A small threshold value is used to merge the extracted adjacent regions which are represented with homogeneous motion parameters while preventing the merging of adjacent object region and background region in the wide range of the threshold value. From the experimental results the proposed merging algorithm is shown to efficiently reduce many redundant regions into one or a few regions in the wide range of the threshold value.
基于内容编码的两级运动区域合并算法
针对基于内容的编码,提出了一种基于动作的两阶段区域合并算法。它采用六参数运动模型和常规变化检测器获得的变化图像。首先,利用变化图像确定每个区域的类型为目标、背景和不确定区域之一;在第一个区域合并阶段,提取两个相邻目标区域和两个相邻区域的所有对。计算了每一对的仿射运动模型参数。然后,对每个类型执行错误最小的一对的合并。特别是采用较大的阈值来有效地合并背景中分割的冗余区域。在第二区域合并阶段,对相邻的不确定区域或不同类型的相邻区域,按照与第一阶段相同的步骤进行合并。采用较小的阈值对提取的以均匀运动参数表示的相邻区域进行合并,同时在较大的阈值范围内防止相邻目标区域和背景区域合并。实验结果表明,该算法能在较宽的阈值范围内有效地将多个冗余区域分解为一个或几个区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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