期刊文献+

基于检索的人体运动识别和模拟 被引量:10

Human Motion Recognition and Simulation Based on Retrieval
在线阅读 下载PDF
导出
摘要 运动识别和模拟是人体运动分析中重要的研究内容·实现了以检索为基础的实验性的运动分析系统·小波矩具有平移、旋转和缩放不变性,能够提取局部多层次特征,被用来作为特征描述运动序列以及动作·根据相似性实现运动识别,利用动态时间变形(DTW)实现序列的动作匹配,在poser建模、依据正多面体分割的金字塔模型得到多视点投影视频的数据库中进行识别和匹配,并以三维模型的形式显示出来·实验结果可以模拟人体运动以及为进一步分析提供初始分析数据· Motion recognition and simulation are important in human motion analysis. In this paper, an experimental motion analysis system based on retrieval is implemented. Wavelet moments are translation, rotation and scale invariant, and can extract local multi-level features, so they are applied as features to describe motion sequence and actions. Motion recognition is implemented based on the similarity of motion sequences, while action match is addressed using dynamic time warping (DTW). Resulted motion simulation is represented in 3D models, Experiments show the algorithm based on retrieval is efficient for motion recognition and simulation. Retrieval results can simulate human motion, or provide the coarse human motion configuration data for further analysis.
出处 《计算机研究与发展》 EI CSCD 北大核心 2006年第2期368-374,共7页 Journal of Computer Research and Development
基金 国家"八六三"高技术研究发展计划基金项目(2001AA231031) 国家"九七三"重点基础研究发展规划基金项目(G1998030608) 国家科技攻关计划课题奥运科技专项基金项目(2001BA904B08)~~
关键词 小波矩 运动识别 动作检索 wavelet moment motion recognition action retrieval
  • 相关文献

参考文献11

  • 1R. Cutler, L. S. Davis. Robust real-time periodic motion detection, analysis, and applications, IEEE Trans. Pattern Analysis and Machine Intelligence, 2000, 22(8): 781-796.
  • 2A. J. Lipton, Local application of optic flow to analyse rigid versus non- rigid motion, http://www.eecs. lehigh, edu/FRAME[Lipton]iccv frame, html, 1999-09.
  • 3Liu Ren, Gregory Shakhnarovieh, Jessiea Hodgins, et al.Learning silhouette features for control of human motion. In:Proc. SIGGRAPH2004 Conf, Sketches & Applications. New York: ACM Press 2004.
  • 4陈睿,刘国翌,赵国英,张俊,李华.基于序列蒙特卡罗方法的3D人体运动跟踪[J].计算机辅助设计与图形学学报,2005,17(1):85-92. 被引量:21
  • 5Chris Stauffer, W. Eric, L. Grimson. Learning patterns of activity using real-time tracking. IEEE Trans. Pattern Analysis and Machine Intelligence, 2000, 22(8): 747-757.
  • 6A. Elgammal, D. Harwood, L. Davis. Non-parametric model for background subtraction. The 6th European Conference on Computer Vision, Dublin, Ireland, 2000.
  • 7陈睿,邓宇,向世明,李华.结合强度和边界信息的非参数前景/背景分割方法[J].计算机辅助设计与图形学学报,2005,17(6):1278-1284. 被引量:13
  • 8T. Horprasert, D. Harwood, L. S. Davis. A statistical approach for real-time robust background subtraction and shadow detection.IEEE ICCV'99 Frame-Rate Workshop, Kerkyra, Greece, 1999.
  • 9Dinggang Shen, Horace H. S. Ip. Discriminative wavelet shape descriptors for recognition of 2 D patterns. Pattern Recognition,1999, 32(2): 151-165.
  • 10M. Unser, A. Aldroubi, M. Eden. On the asymptotic convergence of B-spline wavelets to Gabor functions. IEEE Trans.Inform.Theory, 1992, 38(2): 864-872.

二级参考文献45

  • 1王天树 郑南宁 李岩 等.用于人体运动合成的运动纹理模型[A]..第4届中国计算机图形学大会[C].北京,2002.40-50.
  • 2Isard M, Blake A. CONDENSATION-Conditional density propagation for visual tracking[J]. International Journal of Computer Vision, 1998, 29(1): 5~28.
  • 3Gavrila D, Davis L. 3-D model based tracking of humans in action: A multiview approach[A]. In: IEEE Proceedings of International Conference on Computer Vision and Pattern Recognition, San Francisco, California, 1996. 73~80.
  • 4Wren C, Pentland A. Dynaman: A recursive model of human motion[R]. Cambridge, MA: MIT Media Lab, 1998.
  • 5Plaenkers R, Fua P. Articulated soft objects for video-based body modeling[A]. In: IEEE Proceedings of International Conference on Computer Vision, Vancouver, 2001. 394~401.
  • 6Deutscher J, Blake A, Reid I. Articulated body motion capture by annealed particle filtering[A]. In: IEEE Proceedings of International Conference on Computer Vision and Pattern Recognition, Hilton Head Island, 2000, 2: 126~133.
  • 7Deutscher J, Davidson A, Reid I. Articulated partitioning of high dimensional search spaces associated with articulated body motion capture[A]. In: IEEE Proceedings of International Conference on Computer Vision and Pattern Recognition. Hawaii, 2001, 2: 669~676.
  • 8Brand M. Shadow puppetry[A]. In: IEEE Proceedings of International Conference on Computer Vision, Corfu, 1999. 1237~1244.
  • 9Zhang J, Liu J S. A new sequential importance sampling method with its application to the 2D hydrophobic-hydrophilic model[J]. Journal of Chemical Physics, 2002, 117(7): 3492~3498.
  • 10Wang X, Chen R, Liu J S. Monte Carlo Bayesian signal processing for wireless communications[J]. Journal of VLSI Signal Processing. 2002, 30(2): 89~105.?A?A?A

共引文献32

同被引文献111

引证文献10

二级引证文献49

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部