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Research and Implementation of Target Tracking Algorithm Based on Convolution Neural Network

机译:基于卷积神经网络的目标跟踪算法的研究与实现

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Video target tracking is an important research topic in computer vision, and has been widely used in video surveillance, robot, human-computer interaction and so on. The emergence of large data age and the emergence of in-depth learning methods provide a new opportunity for the study of video target tracking. This paper first analyzes the research problems of video target tracking at present, analyzes the characteristics and trends of video target tracking in the new period, introduces the emerging recursive neural network frame structure, combined with Kalman filterAnd the experimental results show that the accuracy and robustness of the target tracking based on the convolution neural network algorithm are all good.
机译:视频目标跟踪是计算机视觉中的重要研究课题,已广泛应用于视频监控,机器人,人机交互等领域。大数据时代的出现和深度学习方法的出现为视频目标跟踪的研究提供了新的机会。本文首先分析了当前视频目标跟踪的研究问题,分析了新时期视频目标跟踪的特点和趋势,介绍了新兴的递归神经网络框架结构,并结合卡尔曼滤波,实验结果表明该方法的准确性和鲁棒性。基于卷积神经网络算法的目标跟踪都很好。

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