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使用簡易深度成像設(shè)備的高爾夫揮桿動態(tài)貝葉斯網(wǎng)絡(luò)三維重建

呂東岳 黃志蓓 陶冠宏 俞能海 吳健康

呂東岳, 黃志蓓, 陶冠宏, 俞能海, 吳健康. 使用簡易深度成像設(shè)備的高爾夫揮桿動態(tài)貝葉斯網(wǎng)絡(luò)三維重建[J]. 電子與信息學(xué)報(bào), 2015, 37(9): 2076-2081. doi: 10.11999/JEIT150165
引用本文: 呂東岳, 黃志蓓, 陶冠宏, 俞能海, 吳健康. 使用簡易深度成像設(shè)備的高爾夫揮桿動態(tài)貝葉斯網(wǎng)絡(luò)三維重建[J]. 電子與信息學(xué)報(bào), 2015, 37(9): 2076-2081. doi: 10.11999/JEIT150165
Lü Dong-yue, Huang Zhi-pei, Tao Guan-hong, Yu Neng-hai, Wu Jian-kang. Dynamic Bayesian Network Model Based Golf Swing 3D Reconstruction Using Simple Depth Imaging Device[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2076-2081. doi: 10.11999/JEIT150165
Citation: Lü Dong-yue, Huang Zhi-pei, Tao Guan-hong, Yu Neng-hai, Wu Jian-kang. Dynamic Bayesian Network Model Based Golf Swing 3D Reconstruction Using Simple Depth Imaging Device[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2076-2081. doi: 10.11999/JEIT150165

使用簡易深度成像設(shè)備的高爾夫揮桿動態(tài)貝葉斯網(wǎng)絡(luò)三維重建

doi: 10.11999/JEIT150165
基金項(xiàng)目: 

國家自然科學(xué)基金(61431017)和科技部國際科技合作專項(xiàng)(2012DFG11820)

Dynamic Bayesian Network Model Based Golf Swing 3D Reconstruction Using Simple Depth Imaging Device

  • 摘要: 基于簡易深度成像設(shè)備的動作捕捉系統(tǒng)因其與傳統(tǒng)設(shè)備相比更加廉價(jià)且易于使用而倍受關(guān)注。然而,此類設(shè)備圖像分辨率很低,肢體間互相遮擋,缺乏3維動作重建的基本數(shù)據(jù)條件。該文融合人體關(guān)節(jié)點(diǎn)父子關(guān)系與關(guān)節(jié)點(diǎn)在運(yùn)動中的多階馬爾可夫性,提出一個(gè)描述人體關(guān)節(jié)點(diǎn)空間關(guān)系與動態(tài)特性的動態(tài)貝葉斯網(wǎng)絡(luò)(DBN)模型,基于該DBN模型并利用高爾夫揮桿運(yùn)動的相似性,構(gòu)建了一種高爾夫揮桿3維重建系統(tǒng)DBN-Motion(DBN-based Motion reconstruction system),使用簡易深度成像設(shè)備Kinect,有效地解決了肢體遮擋的問題,實(shí)現(xiàn)了高爾夫揮桿動作的捕獲和3維重建。實(shí)驗(yàn)結(jié)果表明,該系統(tǒng)能夠在重建精度上媲美商用光學(xué)動作捕捉系統(tǒng)。
  • Zhou H and Hu H. Human motion tracking for rehabilitation a survey[J]. Biomedical Signal Processing and Control, 2008, 3(1): 1-18.
    Noiumkar S and Tirakoat S. Use of optical motion capture in sports science: a case study of golf swing[C]. 2013 International Conference on Informatics and Creative Multimedia (ICICM), Kuala Lumpur, 2013: 310-313.
    Holte M B, Chakraborty B, Gonzalez J, et al.. A local 3-D motion descriptor for multi-view human action recognition from 4-D spatio-temporal interest points[J]. IEEE Journal of Selected Topics in Signal Processing, 2012, 6(5): 553-565.
    Nam C N K, Kang H J, and Suh Y S. Golf swing motion tracking using inertial sensors and a stereo camera[J]. IEEE Transactions on Instrumentation and Measurement, 2014, 63(4): 943-952.
    Chun S, Kang D, Choi H R, et al.. A sensor-aided self coaching model for uncocking improvement in golf swing[J]. Multimedia Tools and Applications, 2014, 72(1): 253-279.
    Livingston M A, Sebastian J, Ai Z, et al.. Performance measurements for the microsoft kinect skeleton[C]. 2012 IEEE Virtual Reality Short Papers and Posters (VRW), Costa Mesa, CA, 2012: 119-120.
    Shum H P, Ho E S, Jiang Y, et al.. Real-time posture reconstruction for Microsoft Kinect[J]. IEEE Transactions on Cybernetics, 2013, 43(5): 1357-1369.
    Rosado J, Silva F, Santos V, et al.. Reproduction of human arm movements using kinect-based motion capture data[C]. 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO), Shenzhen, 2013: 885-890.
    Xiang C, Hsu H H, Hwang W Y, et al.. Comparing real-time human motion capture system using inertial sensors with microsoft kinect[C]. 2014 7th International Conference on Ubi-Media Computing and Workshops (UMEDIA), Ulaanbaatar, 2014: 53-58.
    Kao W C, Hsu S C, and Huang C L. Human upper-body motion capturing using kinect[C]. 2014 International Conference on Audio, Language and Image Processing (ICALIP), Shanghai, 2014: 245-250.
    Zhang L, Hsieh J C, Ting T T, et al.. A kinect based golf swing score and grade system using GMM and SVM[C]. 2012 5th International Congress on Image and Signal Processing (CISP), Chongqing, 2012: 711-715.
    Zhang L, Hsieh J C, and Wang J. A kinect-based golf swing classification system using HMM and Neuro-Fuzzy[C]. 2012 International Conference on Computer Science and Information Processing (CSIP), Xi,an, 2012: 1163-1166.
    Lin Y H, Huang S Y, Huang S Y, et al.. A kinect-based system for golf beginners training[J]. Information Technology Convergence, 2013, 253(1): 121-129.
    Shen W, Deng K, Bai X, et al.. Exemplar-based human action pose correction and tagging[C]. 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, 2012: 1784-1791.
    Smisek J, Jancosek M, and Pajdla T. 3D with kinect[C]. 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, 2011: 1154-1160.
    Arvind D and Bates A. The speckled golfer[C]. The ICST 3rd International Conference on Body Area Networks, Tempe, Arizona, 2008: 1-7.
    McGuan S P. Achieving commercial success with biomechanics simulation[C]. 20 International Symposium on Biomechanics in Sports, Cceres, Spain, 2002: 20, 451-460.
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出版歷程
  • 收稿日期:  2015-01-29
  • 修回日期:  2015-05-11
  • 刊出日期:  2015-09-19

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