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Improved AP Clustering Algorithm Based on Target Segmentation

机译:基于目标分割的改进AP聚类算法

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This paper describe a feasible scheme of local visual navigation, local visual navigation application scenarios often some with complex background, target species more real scenario that the obstacle avoidance is particularly important. In particular the visual navigation target segmentation in the background and the foreground objects more complex scenarios important for predicting pre-step. This visual navigation closer to the qualitative analysis of the scene, so the performance can be weak, but easy to implement, without artificial markers, but more dependent on hardware performance, available online AP Cluster is running.
机译:本文描述了一种可行的局部视觉导航方案,局部视觉导航的应用场景往往有些具有复杂的背景,目标物种更真实的场景认为避障尤为重要。尤其是在背景和前景对象中的视觉导航目标分割,对于预测前置步骤而言更为重要。这种视觉导航更接近场景的定性分析,因此性能可能较弱,但易于实现,无需人工标记,但更多地取决于硬件性能,因此可以在线运行AP Cluster。

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