动态场景中运动目标的检测与跟踪研究

Bowen Cheng, Shuai Jiang, Yalong Pang, Shenshen Luan, Jing Lu
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引用次数: 0

摘要

针对动态场景下运动目标检测与跟踪算法鲁棒性差的问题,提出了一种结合光流法和卡尔曼预测器的动态场景下运动目标跟踪算法,解决了目标跟踪中的遮挡问题。光流法解决了运动目标的检测问题,利用卡尔曼预测器完成运动目标的预测和关联。实验结果表明,该算法在静态场景和动态场景下都能很好地工作,并且在动态场景中对运动物体的检测精度比光流法更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Detection and Tracking of Moving Objects in Dynamic Scenes
Aiming at the poor robustness of the moving objects detection and tracking algorithm in the dynamic scenes, a new moving objects tracking algorithm in the dynamic scenes is proposed, which combines the optical flow method and Kalman predictor, can solve the occlusion problem in target tracking. The optical flow method solves the detection of the moving objects problem, and the Kalman predictor is used to complete the moving target prediction and association. The experimental results show that, the proposed algorithm can work well in the stationary scenes and the dynamic scenes, and the accuracy of detection of moving objects in dynamic scenes is more effective than the optical flow method only.
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