Automatic Generation of a Subject-Specific Model for Accurate Markerless Motion Capture and Biomechanical Applications
Automatic Generation of a Subject-Specific Model for Accurate Markerless Motion Capture and Biomechanical Applications
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DOI：
10.1109/tbme.2008.2002103
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发表时间：
2010-04-01
影响因子：
4.6
通讯作者：
Andriacchi, Thomas P.
中科院分区：
文献类型：
--
作者：
Corazza, Stefano;Gambaretto, Emiliano;Andriacchi, Thomas P.
描述了一种用于自动生成由形态学和关节位置信息组成的对象特定模型的新方法。其目的是解决无标记运动捕捉（MMC）和生物力学研究的有效和准确的模型生成的需要。该算法应用并扩展了以前在人体形状空间[1]上的工作，通过在特定对象的自由曲面中嵌入十个关节中心的位置信息。通过线性回归，在一组9名受试者的关节中心是已知的，在3-D网格中的关节中心的最佳位置。该模型被证明是足够准确的运动学（关节中心）和形态（身体形状）的信息，以允许准确的跟踪与MMC系统。自动模型生成算法适用于不同质量和分辨率的3-D网格，例如激光扫描和可视外壳[2]。使用9名不同性别、体重指数（BMI）、年龄和种族的受试者对完整方法进行了测试。实验训练误差和交叉验证误差分别为19和25 mm，平均超过研究中分析的10个受试者的关节。
A novel approach for the automatic generation of a subject-specific model consisting of morphological and joint location information is described. The aim is to address the need for efficient and accurate model generation for markerless motion capture (MMC) and biomechanical studies. The algorithm applied and expanded on previous work on human shapes space [1] by embedding location information for ten joint centers in a subject-specific free-form surface. The optimal locations of joint centers in the 3-D mesh were learned through linear regression over a set of nine subjects whose joint centers were known. The model was shown to be sufficiently accurate for both kinematic (joint centers) and morphological (shape of the body) information to allow accurate tracking withMMCsystems. The automatic model generation algorithm was applied to 3-D meshes of different quality and resolution such as laser scans and visual hulls [2]. The complete-method was tested using nine subjects of different gender, body mass index (BMI), age, and ethnicity. Experimental training error and cross-validation errors were 19 and 25 mm, respectively, on average over the joints of the ten subjects analyzed in the study.