基于IMU的手语识别骨骼模型构建

IMU Based Construction of Sign Language Skeleton Model

手语识别属于手势识别的研究范畴。传统的基于数据手套的手语识别方法不能完整捕捉手语的所有要素,无法识别手部与肢体配合的手语动作。惯性测量单元(IMU)由于体积小、成本低而被越来越多地应用到动作捕捉项目中。借鉴机器人运动学相关知识,提出了基于IMU的手语识别骨骼模型,该模型符合人体生物学特征。模型的构建步骤为首先进行骨骼的选取,然后进行尺寸标定。最后提出了标定模型尺寸的实验方法,使用IMU获得的动作集的数据可以进行求解。

Sign language recognition belongs to the research category of gesture recognition.The traditional method of sign language recognition based on data glove can not capture all the elements of sign language,as it can not recognize sign language movements cooperated by hand and limbs.For IMU(Inertial Measurement Unit),due to its small size,low cost,it has been applied to the motion capture project widely.Based on the knowledge of robot kinematics,we proposed an IMU based language recognition skeleton model,which is in line with the biological characteristics of human body.The first construction procedure of the model is to make a selection of the skeleton,and then tocalibrate the size of the skeleton.Finally,an experimental method was proposed to calibrate the model size,which can be solved by using the data of the action set obtained by IMU.