Research on Motion Control Technology of Virtual Human’s Lower Limb Based on Optical Motion Capture Data

Abstract

Abstract: As passive-optical motion capture equipment could only capture the motion information of human’s key joints, a simplified skeleton structure model of virtual human was introduced; and then the error sources of motion data of virtual human were analyzed according to the acquisition process of optical motion capture data based on the skeleton structure model. Focusing on the problem of poor continuity of motion process of virtual human’s lower limb caused by continuity deficiency of motion capture data, a motion control method was proposed to strengthen the control of motion process of virtual human, which included data smoothing of motion process of key joints and the calculation of motion information of other joints in the lower limb kinematic chain based on inverse kinematics. An experiment and a virtual maintenance training platform of a transfer case have proved the validity and practicability of the proposed method.

Key words: motion capture equipment, motion control, data smoothing, inverse kinematics

CLC Number:

TP391.9

Liang Feng, Zhang Zhili, Li Xiangyang, Tang Zhibo, Ma Chao. Research on Motion Control Technology of Virtual Human’s Lower Limb Based on Optical Motion Capture Data[J]. Journal of System Simulation, 2015, 27(2): 327-335.

References

[1] 姚旭东. 基于运动捕捉数据的虚拟人建模及运动仿真[J]. 计算机仿真, 2010, 27(6): 225-229.
[2] 魏小鹏, 张强, 肖伯祥, 等. 基于模板匹配的人体运动捕捉数据处理方法[J]. 系统仿真学报, 2010, 22(10): 2368-2372.
[3] Andreas Aristidou, Joan Lasenby.Real-time marker prediction and CoR estimation in optical motion capture[J]. The Visual Computer (S0178-2789), 2013, 29(1): 7-26.
[4] Lou H, Chai J.Example-based human motion denoising[J]. IEEE Transactions on Visualization and Computer Graphics (S1077-2626), 2010, 16(5): 870-879.
[5] Alessandra Martins Coelho, Vania Vieira Estrela.Data-driven motion estimation with spatial adaptation[J]. International Journal of Image Processing (S1985-2304), 2012, 6(1): 54-67.
[6] Wu Sheng, Zhang Qiang, Xiao Boxiang, et al. An effective method of capture data processing for optical motion[J]. Journal of Basic Science and Engineering (S1005-0930), 2009, 17(5): 790-798.
[7] 邱世广, 周德吉, 范秀敏, 等. 虚拟操作仿真环境中基于运动捕捉的虚拟人实时控制技术[J]. 计算机集成制造系统, 2013, 19(3): 523-528.
[8] F J Alonso, J M Del Castillo, P Pintado. Motion data processing and wobbling mass modeling in the inverse dynamics of skeletal models[J]. Mechanism and Machine Theory (S0094-114X), 2007, 42: 1153-1169.
[9] Chen Shanmin, Ning Tao, Wang Ke.Motion control of virtual human based on optical motion capture in immersive virtual maintenance system[C]// Proceeding of 2011 International Conference on Virtual Reality and Visualization. Washington, DC, USA: IEEE, 2011: 52-56.
[10] Wang Songshan, Qi Yanqing.A virtual human’s driving method based on motion capture data[J]. Advanced Materials Research (S1022-6680), 2013, 711: 500-505.
[11] Li Xiangyang, Gao Qinhe, Zhang Zhili, et al. Collaborative virtual maintenance training system of complex equipment based on immersive virtual reality environment[J]. Assembly Automation (S0144-5154), 2012, 32(1): 72-85.
[12] 侯永隆, 宁涛, 王可. 基于光学运动捕捉的虚拟人体标定技术[J]. 图学学报, 2013, 34(9): 126-132.
[13] 肖伯祥, 魏小鹏, 张强, 等. 光学运动捕捉散乱数据处理的一种方法[J]. 系统仿真学报, 2008, 20(2): 382-385.
[14] 王军, 胡永刚, 韩崇昭. 被动式光学运动捕捉系统丢点检测与补偿[J]. 系统工程与电子技术, 2012, 34(11): 2374-2378.
[15] 张毅, 张烁, 罗元, 等. 基于Kinect深度图像信息的手势轨迹识别及应用[J]. 计算机应用研究, 2012, 29(9): 3547-3550.
[16] Zong Dan, Li Chunpeng, Xia Shihong, et al. Instruction level motion control of virtual human for maintenance process simulation[C]// Proceedings of 2010 International Conference on Audio Language and Image Processing. Washington, DC, USA: IEEE, 2011: 1289-1294.
[17] 容志能. 惯性运动捕捉系统中传感数据的传输与处理[D]. 杭州: 浙江大学, 2012.
[18] Lin Hongwei.Adaptive data fitting by the progressive-iterative approximation[J]. Computer Aided Geometric Design (S0167-8396), 2012, 29(7): 463-473.
[19] Naturalpoint Corporation. Delivering tracking technology since 1996 [EB/OL]. (2013-12-15) [2015-01-12]. http:// www. naturalpoint. com/ optitrack/ about/, 2013.