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MDL-based segmentation and motion modeling in a long image sequence of scene with multiple independently moving objects

机译:具有多个独立移动对象的长图像场景序列中基于MDL的分割和运动建模

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This paper presents a method for spatiotemporal segmentation of long image sequences of scenes which include multiple independently moving objects, based on the minimum description length (MDL) principle. First, a family of motion models is constructed, each of which corresponds to a physically meaningful motion such as translation with constant velocity or a combination of translation and rotation. Then, the motion description length is formulated. When an object changes the type of the motion or a new part of an object appears, the corresponding temporal or spatial segmentation is carried out. Ambiguous segmentation of two consecutive images can be resolved by minimizing the motion description length in a long sequence of images. Experiments on several real image sequences show the validity of our method.
机译:本文提出了一种基于最小描述长度(MDL)原理的时空分割包含多个独立运动物体的场景的时空分割方法。首先,构造一个运动模型族,每个运动模型都对应一个物理上有意义的运动,例如以恒定速度进行平移或平移和旋转的组合。然后,制定运动描述长度。当对象改变运动的类型或出现对象的新部分时,将执行相应的时间或空间分割。可以通过最小化长图像序列中的运动描述长度来解决两个连续图像的歧义分割问题。在几个真实图像序列上的实验证明了我们方法的有效性。

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