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A framework for fully automatic moving video-object segmentation based on graph partitioning and object tracking

机译：基于图分割和对象跟踪的全自动运动视频对象分割框架

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摘要

We present a novel fully automatic moving video-object extraction algorithm based on graph partitioning and object tracking. A sophisticated graph partitioning algorithm is first used to (intra-frame) segment the moving video objects (VOs) of a specific (key) frame without any prior knowledge of segmentation results of previous frame(s). Once the VOs for this key frame are extracted, the (inter-frame) segmentation of VOs of subsequent frames is accomplished by tracking the segmented objects of consecutive frames by means of motion projection and modified histogram back-projection. To avoid significant error propagation caused by the (inter-frame) object tracking, a new key frame has to be identified periodically, based on a criterion in terms of camera motion parameters. Simulation results illustrate that the proposed algorithm gives comparable results to semi-automatic methods introduced in the literature.
机译：我们提出了一种新颖的基于图划分和目标跟踪的全自动运动视频目标提取算法。首先使用复杂的图形分区算法对特定（关键）帧的运动视频对象（VO）进行（帧内）分段，而无需事先了解先前帧的分段结果。一旦提取了此关键帧的VO，就可以通过运动投影和修正的直方图反投影跟踪连续帧的分割对象来完成后续帧VO的（帧间）分割。为了避免由于（帧间）对象跟踪而导致的严重错误传播，必须基于相机运动参数方面的标准定期识别新的关键帧。仿真结果表明，所提出的算法与文献中介绍的半自动方法具有可比的结果。

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