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Joint space-time motion-based video segmentation and occlusion detection using multiphase level sets

机译:基于多时相水平集的时空运动联合视频分割和遮挡检测

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Spatial video segmentation is usually performed based on motion between two frames. Some recent approaches extend this to joint segmentation in space-time; the resulting 3-D segmentation can be interpreted as a volume "carved out" by a moving object in the image sequence domain, or the so-called,"object tunnel". In this paper, we extend this concept to explicit modeling of occlusion events in space-time. In addition to the modeling of object evolution, we also explicitly model occluded and newly-exposed areas in the background by means of "occlusion volume", a new space-time concept. A voxel belongs to occlusion volume if its intensity is consistent with past intensities along its motion trajectory but inconsistent with future intensities (reversed for "exposed volume"). We propose a variational formulation of the problem that we solve using the multiphase level set method. We show encouraging experimental results for synthetic and natural image sequences.
机译:通常基于两个帧之间的运动来执行空间视频分割。最近的一些方法将其扩展到时空联合分割。可以将生成的3-D分割解释为图像序列域中的运动对象或所谓的“对象通道”“雕刻”出的体积。在本文中,我们将此概念扩展到时空中遮挡事件的显式建模。除了对象演化的建模外,我们还通过“时空量”(一种新的时空概念)在后台显式地对被遮挡的区域和新暴露的区域进行建模。如果体素的强度与沿其运动轨迹的过去强度一致,但与将来的强度不一致(属于“暴露体积”),则该体素属于遮挡体积。我们提出了使用多阶段水平集方法解决的问题的变分形式。我们展示了令人鼓舞的合成和自然图像序列的实验结果。

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