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Target tracking based on data fusion tree in intelligent space

机译:基于智能空间数据融合树的目标跟踪

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This paper puts forward a novel method based on multilevel information fusion to realize the real-time target detection and tracking. Based on the triangulation technique and least square method, the system matches the moving target by the information on color, and carries out the 3D reconstruction of target. Firstly, when the moving target is detected, the system will scan target human's leg by laser range finder to cluster the nearest neighbor, and the exact distance information will be got. Secondly, this article adopts a better Extend Kalman Filter for heterogeneous sensor information fusion to realize the simultaneous robot localization and target tracking in intelligent space. At last, the experimental results verify the effectiveness of the proposed method.
机译:本文提出了一种基于多级信息融合的新方法,实现实时目标检测和跟踪。 基于三角测量技术和最小二乘法,系统通过关于颜色的信息与移动目标匹配,并执行目标的3D重建。 首先,当检测到移动目标时,系统将通过激光测距仪扫描目标人腿以聚集最近的邻居,并且将得到确切的距离信息。 其次,本文采用更好的扩展卡尔曼滤波器,用于异构传感器信息融合,实现智能空间中的同时机器人定位和目标跟踪。 最后,实验结果验证了所提出的方法的有效性。

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