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PoseNet Based Acupoint Recognition of Blind Massage Robot

机译:基于PoseNet的盲人按摩机器人穴位识别

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In allusion to the current common acupoint recognition is based on the edge extraction of neural network, which is affected by too many factors of human, there are certain interferences and errors in finding acupoints. This paper put forward a novel method combining posture tracking algorithm with proportional bone measurement, which can fully fit the skeleton of human body to provide a new idea for acupoint recognition of massage robot, and improve its accuracy and efficiency. The above method is simulated in Python to realize the function of massage robot to find acupoints automatically. The result shows that it takes less time to find more accurate and more quantities acupoints.
机译:考虑到当前常见的穴位识别是基于神经网络的边缘提取,这受人为因素的影响很大,在寻找穴位时存在一定的干扰和错误。提出了一种将姿态跟踪算法与比例骨测量相结合的新方法,该方法可以完全拟合人体的骨骼,为按摩机器人的穴位识别提供新思路,并提高其准确性和效率。上面的方法在Python中进行了仿真,以实现按摩机器人自动找到穴位的功能。结果表明,找到更准确,数量更多的穴位所需的时间更少。

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