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首页> 外文期刊>IEEE Transactions on Neural Networks >Motion segmentation based on motion/brightness integration and oscillatory correlation
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Motion segmentation based on motion/brightness integration and oscillatory correlation

机译：基于运动/亮度集成和振荡相关的运动分割

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摘要

A segmentation method based on the integration of motion and brightness is proposed for image sequences. The method is composed of two parallel pathways that process motion and brightness, respectively, Inspired by the visual system, the motion pathway has two stages. The first stage estimates local motion at locations with reliable information. The second stage performs segmentation based on local motion estimates. In the brightness pathway, the input scene is segmented into regions based on brightness distribution. Subsequently, segmentation results from the two pathways are integrated to refine motion estimates. The final segmentation is performed in the motion network based on refined estimates. For segmentation, locally excitatory globally inhibitory oscillator network (LEGION) architecture is employed whereby the oscillators corresponding to a region of similar motion/brightness oscillate in synchrony and different regions attain different phases. Results on synthetic and real image sequences are provided, and comparisons with other methods are made.
机译：提出了一种基于运动和亮度集成的图像分割方法。该方法由分别处理运动和亮度的两个平行路径组成，受视觉系统的启发，运动路径具有两个阶段。第一阶段用可靠的信息估算局部运动。第二阶段基于局部运动估计执行分割。在亮度路径中，基于亮度分布将输入场景划分为多个区域。随后，将来自这两个路径的分割结果进行整合以完善运动估计。最终的分割是基于改进的估计在运动网络中执行的。为了进行分段，采用了局部激励全局抑制性振荡器网络（LEGION）体系结构，由此，与具有相似运动/亮度的区域相对应的振荡器同步地振荡，并且不同的区域获得不同的相位。提供了合成和真实图像序列的结果，并与其他方法进行了比较。

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