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Particle filter based on multi-window

机译:基于多窗口的粒子过滤器

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摘要

A novel particle filter based on multi-window is proposed for target tracking, which represents the tracking target with several windows that each one corresponds with a particle filter. Because tracking performance is usually influenced by factors such as camera angle, illumination. Meanwhile the target may be occluded by obstacles in the clutter background or be occluded by other target. A multi-window particle filter tracking method is proposed. And the multi-window may overlap or contain the scene around the target. In the tracking process, the different particles have different tracking cues of the targets. In the novel algorithm, through the spatial relation of the non-overlap windows and overlap windows, the spatial configuration of the tracking target is included and considered. All particle filter trackers are used to estimate the target status parameters. Using this algorithm, we can overcome the tracking failure because of the object spatial features considered. And experiment results clearly demonstrate the effectiveness of the novel method on illumination influence or self-occlusion problem in a complex background.
机译:提出了一种基于多窗口的新型粒子过滤器进行目标跟踪,该目标过滤器用多个窗口表示跟踪目标,每个窗口对应一个粒子过滤器。因为跟踪性能通常受摄像机角度,照明度等因素影响。同时,目标可能被杂物背景中的障碍物遮挡或被其他目标遮挡。提出了一种多窗口粒子滤波跟踪方法。并且多窗口可能会重叠或包含目标周围的场景。在跟踪过程中,不同的粒子对目标具有不同的跟踪线索。在该新颖算法中,通过非重叠窗口和重叠窗口的空间关系,包括并考虑了跟踪目标的空间配置。所有粒子过滤器跟踪器均用于估计目标状态参数。使用该算法,由于考虑了对象空间特征,我们可以克服跟踪失败。实验结果清楚地证明了该新方法在复杂背景下对照明影响或自遮挡问题的有效性。

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