计算机科学 ›› 2013, Vol. 40 ›› Issue (4): 292-294.

• 图形图像与模式识别 • 上一篇    下一篇

无需人工干预的关节点提取和三维重建

魏玮,王丹丹,刘静,刘命   

  1. 河北工业大学计算机科学与软件学院天津300401;河北工业大学计算机科学与软件学院天津300401;河北工业大学计算机科学与软件学院天津300401;河北工业大学计算机科学与软件学院天津300401
  • 出版日期:2018-11-16 发布日期:2018-11-16

Articulation Points Extraction without Manual Intervention and 3D Reconstruction

WEI Wei,WANG Dan-dan,LIU Jing and LIU Ming   

  • Online:2018-11-16 Published:2018-11-16

摘要: 随着现在人体的运动捕获和行为理解的研究的发展,对这项研究有了越来越高的要求。相对于原来的手动提取人体关节点作为特征点来研究,如何使得提取特征点更加自动化,对以后的运动捕获和行为理解的研究意义重大。提出一种在单目视觉条件下在第一帧自动提取人体关节点位置的方法,来解决传统的以手动标定提取人体关节点的问题,并且利用光流稀疏L_K算法 对提取出的关节点进行运动跟踪,得到运动人体二维坐标信息,结合像机模型通过几何计算获得人体关节点的深度信息。

关键词: 关节点,比例正交投影,比例因子,重建

Abstract: Now with the development of the research of the motion capture and the behavior understanding of the human,the demand is increasing.The people extracted the articulation points as the feature points manually before,compared with that.How to make the extraction of the feature points much more automated is meaningful to the research of the motion capture and the behavior understanding later.This paper proposed the method of extracting the dynamic human’s articulation points and obtaining the position of the articulation points on the first frame image automatically from monocular video sequences to solve the disadvantage of traditional method about extracting the points from marked human body manually.Then the points were tracked with the light flow sparse L_K algorithm to acquire the information of two-dimensional coordinate about the moving human.Finally,combining the camera model the relative depth of the points can be obtained through geometric calculation.

Key words: Articulation points,Scaled-orthographic camera model,Scale factor,Reconstruction

[1] Furukawa Y,Ponce J.Accuate,dense and robust multi-viewstereopsis[J].IEEE Pattem Analysis and Machine Intelligenee,2008,1(1):1-14
[2] 罗忠祥.视频流中的人体运动提取与运动合成[D].杭州:浙江大学,2002
[3] 庄越挺,刘小明,潘云鹤,等.运动图像序列的人体三维运动骨架重建[J].计算机辅助设计与图形学学报,2000,4(12):245-250
[4] 雷涛,罗薇薇,樊养余,等.复杂环境下的运动人体骨架提取算法[J].计算机应用研究,2010,8(27):3194-3197
[5] 陈国栋,李建微,潘林,等.基于人体特征三维人体模型的骨架提取算法[J].计算机科学,2009,7(36):295-297
[6] Yoo J-H,Nixon M S,Harris C J.Extracting Human Gait Signatures by Body Segment Properties [C]∥Proceedings of IEEE Southwest Symposium on Image Analysis and Intepretation.Southampton,2002
[7] 于国防,王莉.压缩型顶点链码的研究[J].中国图像图形学报,2010,5(10):1465-1470
[8] 宫宇.运动人体二维特征点间的与三维重建[D].大连:大连理工大学,2009
[9] 张永亮,卢焕章,高劼,等.一种改进的Lucas-Kanade光流估计方法[J].海军航空工程学院学报,2009,4(4):444-445
[10] Zhao J,Li L.Human Motion Reconstruction from Monocular Images using Genetic Algorithms[J].Computer Animation and Virtual World,2004,5(1):407-414
[11] Bregler C,Malik J.Tracking people with twists and exponential maps[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recongnition.Santa Barbara.CA,1998:8-15
[12] 马颂德.计算机视觉——计算理论与算法基础[M].北京:科学出版社,1997

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!