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A Novel Multi-target Detecting and Tracing Method for Robot Vision System

机译:机器人视觉系统的一种新型多目标检测和跟踪方法

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In this paper we study on multi-target detecting and tracing system for intelligent robot and give a good method to detect and track the targets such as pedestrians, which needs to extract the moving targets from the background in image sequence, and track them by probability statistics and controlling theory. In the first stage, we segment the foreground and background regions through GMM (Gaussian Mixture Model) [1] algorithm. Based on the results of the first stage, we build the tracing system with Kalman filter and Mean-Shift in order to capture the moving targets. At last, the experimental results show that our method is correct and robust, it lays a solid foundation for further study on target recognition.
机译:在本文中,我们研究了智能机器人的多目标检测和追踪系统,并提供了一种良好的方法来检测和跟踪行人等目标,需要从图像序列中提取移动目标,并通过概率跟踪它们 统计与控制理论。 在第一阶段,我们通过GMM(高斯混合模型)[1]算法将前景和背景区域进行分割。 根据第一阶段的结果,我们用卡尔曼滤波器和平均转变构建跟踪系统,以捕获移动目标。 最后,实验结果表明,我们的方法是正确且稳健的,它为进一步研究目标识别提供了坚实的基础。

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