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Real-time target tracking with particle filter in moving monocular camera

机译:运动单眼相机中具有粒子过滤器的实时目标跟踪

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In this paper, we propose an improved particle filter algorithm for real-time tracking a randomly moving target in dynamic environment with a moving monocular camera. For making the tracking task robustly and effectively, color histogram based target model is integrated into particle filter algorithm. Bhattacharyya distance is used to weight samples by calculating each sample's histogram with a specified target model and it makes the measurement matching and samples' weight updating more reasonable. In order to reduce sample depletion, the improved algorithm will be able to take the latest observation into account. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.
机译:在本文中,我们提出了一种改进的粒子滤波算法,用于通过动态单眼相机实时跟踪动态环境中的随机移动目标。为了稳健有效地完成跟踪任务,将基于颜色直方图的目标模型集成到了粒子滤波算法中。 Bhattacharyya距离用于通过使用指定的目标模型计算每个样本的直方图来加权样本,从而使测量匹配和样本的权重更新更加合理。为了减少样品消耗,改进的算法将能够考虑最新的观察结果。实验结果证实,即使单眼相机移动并且目标对象在杂乱的背景中被部分遮挡,该方法仍然有效。

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