Abstract

A new algorithm of 6-coordinate tracking of a moving object on a sequence of RGB-images that is based on the convolutional neural network is proposed. Training the neural network is carried out by using the synthesized data of the object with a dynamic model of motion. A Kalman filter is included into the feedback from the network output to its input to obtain a smoothed estimate of the object coordinates. Preliminary results of object tracking on synthesized images demonstrates the efficiency of the proposed approach.

中文翻译：

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卷积神经网络在视频流中的目标跟踪

摘要

提出了一种基于卷积神经网络的在RGB图像序列上对运动物体进行6坐标跟踪的新算法。训练神经网络是通过将对象的合成数据与动态运动模型结合使用来进行的。卡尔曼滤波器包含在从网络输出到其输入的反馈中，以获得对象坐标的平滑估计。对合成图像进行目标跟踪的初步结果证明了该方法的有效性。