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Real-time multi-object detection and tracking for autonomous robots in uncontrolled environments

机译:不受控制的环境中自主机器人的实时多目标检测和跟踪

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摘要

In this paper a new system is developed for autonomous robots to detect and track multi-objects in uncontrolled environments and in real time for the purpose of decreasing the processing time needed and obtaining better error rates than current systems. To achieve this, a novel multi object tracking algorithm is introduced, implemented and enhanced using multithreading where every thread corresponds to a detected motion area. The implementation considered not only objects tracking but also the object motion estimation to speed up the overall tracking process. In addition, a modified color tracking algorithm is also introduced and integrated in the built system. It is based on the HSV color space. This avoids the problems of overlapping detected motion areas. Experimental results on the built system demonstrate that the proposed system reduced the computational time to approximately 54% compared to published results and reduced the position error to less than 1%.
机译:在本文中,为自主机器人开发了一种新系统,以在不受控制的环境中实时检测和跟踪多目标,目的是减少所需的处理时间并获得比当前系统更好的错误率。为了实现这一点,引入了一种新颖的多对象跟踪算法,该算法使用多线程技术来实现和增强,其中每个线程都对应于检测到的运动区域。该实现不仅考虑了对象跟踪,还考虑了对象运动估计,以加快整个跟踪过程。此外,还引入了改进的颜色跟踪算法,并将其集成到构建的系统中。它基于HSV颜色空间。这避免了所检测的运动区域重叠的问题。在已构建系统上的实验结果表明,与已发布的结果相比,所提出的系统将计算时间减少到大约54%,并将位置误差减少到小于1%。

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