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A 3D foot shape feature parameter measurement algorithm based on Kinect2

机译:基于Kinect2的3D脚形特征参数测量算法

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Abstract Accurate measurement of foot shape feature parameters is extremely important in the process of customized shoemaking. A 3D foot’s depth image collected by second-generation Kinect is used to propose a foot shape feature parameter measurement algorithm. Through 3D reconstruction of foot based on improved interactive closest points algorithm, the coordinate transformation, feature point selection, and B-spline curve fitting algorithm, the foot length, foot width, metatarsale girth, and other foot feature parameters were calculated. The 3D foot measurement system using this algorithm is tested, and the results of multiple measurements have a mean variance of less than 0.3?mm. The average error between the algorithm calculation result and the manual measurement result is less than 0.85?mm. The stability and accuracy of the system meet the requirements of custom shoes. It lays a good foundation for the automation and standardization of customized shoemaking.
机译:摘要在定制的擦鞋过程中,脚形特征参数的精确测量非常重要。第二代Kinect收集的3D脚的深度图像用于提出脚形特征参数测量算法。基于改进的交互式最近点算法,坐标变换,特征点选择和B样条曲线拟合算法,计算脚长,脚宽,跖骨周长和其他脚特征参数的三维重建。测试使用该算法的3D脚测量系统,并且多个测量结果的平均方差小于0.3Ωmm。算法计算结果和手动测量结果之间的平均误差小于0.85Ωmm。系统的稳定性和准确性符合定制鞋的要求。它为自动化擦鞋制造的自动化和标准化奠定了良好的基础。

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