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Trajectory Prediction Algorithm of Moving Target Based on Markov Chains

机译:基于马尔可夫链的运动目标轨迹预测算法

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In the field of computer vision, trajectory prediction is one of hottest issues. Based on the study of the existing Markov chains algorithm on the trajectory prediction of the moving target, the predict model had not taken the trajectory of abnormal behavior into account In this paper, the model can re-learn their own adjustment by capturing data of abnormal behavior, and can quickly detect abnormal trajectory behavior, and update the transition probability of prediction model. Simulation results show that the Markov chains model through its own re-learning has highly accuracy in the trajectory prediction.
机译:在计算机视觉领域,轨迹预测是最热门的问题之一。在对现有的运动目标轨迹预测进行马尔可夫链算法研究的基础上,该预测模型并未考虑异常行为的轨迹。行为,并可以快速检测异常轨迹行为,并更新预测模型的转移概率。仿真结果表明,马尔可夫链模型通过自身的重新学习在轨迹预测中具有很高的准确性。

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