Efficient motion retrieval in large motion databases

There has been a recent paradigm shift in the computer animation industry with an increasing use of pre-recorded motion for animating virtual characters. A fundamental requirement to using motion capture data is an efficient method for indexing and retrieving motions. In this paper, we propose a flexible, efficient method for searching arbitrarily complex motions in large motion databases. Motions are encoded using keys which represent a wide array of structural, geometric and, dynamic features of human motion. Keys provide a representative search space for indexing motions and users can specify sequences of key values as well as multiple combination of key sequences to search for complex motions. We use a trie-based data structure to provide an efficient mapping from key sequences to motions. The search times (even on a single CPU) are very fast, opening the possibility of using large motion data sets in real-time applications.

[1]  Edward Fredkin,et al.  Trie memory , 1960, Commun. ACM.

[2]  Christos Faloutsos,et al.  Fast subsequence matching in time-series databases , 1994, SIGMOD '94.

[3]  Zhigang Deng,et al.  Perceptually consistent example-based human motion retrieval , 2009, I3D '09.

[4]  V. Maletic.  Body - Space - Expression: The Development of Rudolf Laban's Movement and Dance Concepts , 1987 .

[5]  Zhaoqi Wang,et al.  Indexing and retrieval of human motion data by a hierarchical tree , 2009, VRST '09.

[6]  Michiel van de Panne,et al.  Motion doodles: an interface for sketching character motion , 2004, SIGGRAPH Courses.

[7]  Jessica K. Hodgins,et al.  Statistical analysis of natural human motion for animation , 2006 .

[8]  Clu-istos Foutsos,et al.  Fast subsequence matching in time-series databases , 1994, SIGMOD '94.

[9]  Jessica K. Hodgins,et al.  Interactive control of avatars animated with human motion data , 2002, SIGGRAPH.

[10]  Seiji Okajima,et al.  Human Motion Retrieval System Based on LMA Features Using Interactive Evolutionary Computation Method , 2012 .

[11]  Hans-Peter Seidel,et al.  Motion reconstruction using sparse accelerometer data , 2011, TOGS.

[12]  K HodginsJessica,et al.  Interactive control of avatars animated with human motion data , 2002 .

[13]  Patrick Gros,et al.  A Geometrical Key-Frame Selection Method Exploiting Dominant Motion Estimation in Video , 2004, CIVR.

[14]  Tao Yu,et al.  MotionMaster: authoring and choreographing Kung-fu motions by sketch drawings , 2006, SCA '06.

[15]  Jernej Barbic,et al.  Segmenting Motion Capture Data into Distinct Behaviors , 2004, Graphics Interface.

[16]  Chao-Hung Lin,et al.  Human Motion Retrieval from Hand-Drawn Sketch , 2012, IEEE Transactions on Visualization and Computer Graphics.

[17]  Yueting Zhuang,et al.  An Efficient Keyframe Extraction from Motion Capture Data , 2006, Computer Graphics International.

[18]  Jessica K. Hodgins,et al.  Performance animation from low-dimensional control signals , 2005, ACM Trans. Graph..

[19]  David A. Forsyth,et al.  Motion synthesis from annotations , 2003, ACM Trans. Graph..

[20]  Norman I. Badler,et al.  Semantic Segmentation of Motion Capture Using Laban Movement Analysis , 2007, IVA.

[21]  Tido Röder,et al.  Efficient content-based retrieval of motion capture data , 2005, SIGGRAPH 2005.

[22]  Wei Wang,et al.  A system for analyzing and indexing human-motion databases , 2005, SIGMOD '05.

[23]  R. Laban,et al.  The mastery of movement , 1950 .

[24]  Norman I. Badler,et al.  The EMOTE model for effort and shape , 2000, SIGGRAPH.

[25]  Lucas Kovar,et al.  Motion Graphs , 2002, ACM Trans. Graph..

[26]  Pierre Poulin,et al.  Motion cues for illustration of skeletal motion capture data , 2007, NPAR '07.

[27]  Norman I. Badler,et al.  Acquiring and validating motion qualities from live limb gestures , 2005, Graph. Model..

[28]  Lorenzo Torresani,et al.  Learning Motion Style Synthesis from Perceptual Observations , 2006, NIPS.

[29]  Atsushi Nakazawa,et al.  A puppet interface for retrieval of motion capture data , 2011, SCA '11.

[30]  Lucas Kovar,et al.  Automated extraction and parameterization of motions in large data sets , 2004, ACM Trans. Graph..

[31]  Yoshihiro Okada,et al.  IEC-Based Motion Retrieval System Using Laban Movement Analysis , 2010, KES.

[32]  Yasuhiko Sakamoto,et al.  Motion map: image-based retrieval and segmentation of motion data , 2004, SCA '04.

[33]  Dimitrios Gunopulos,et al.  Indexing Large Human-Motion Databases , 2004, VLDB.

[34]  Meinard Müller,et al.  Motion templates for automatic classification and retrieval of motion capture data , 2006, SCA '06.

[35]  Michael Gleicher,et al.  Retargetting motion to new characters , 1998, SIGGRAPH.

[36]  Daniel Cohen-Or,et al.  Action synopsis: pose selection and illustration , 2005, ACM Trans. Graph..

[37]  Michael Gleicher,et al.  Automated extraction and parameterization of motions in large data sets , 2004, SIGGRAPH 2004.

[38]  Lucas Kovar,et al.  Motion graphs , 2002, SIGGRAPH Classes.

[39]  Meinard Müller,et al.  Efficient content-based retrieval of motion capture data , 2005, SIGGRAPH '05.

[40]  Tao Yu,et al.  Motion retrieval based on movement notation language , 2005, Comput. Animat. Virtual Worlds.

[41]  D. Cohen-Or,et al.  Action synopsis: pose selection and illustration , 2005, SIGGRAPH 2005.

[42]  Arno Zinke,et al.  Fast local and global similarity searches in large motion capture databases , 2010, SCA '10.

[43]  Takeo Igarashi,et al.  Retrieval and Visualization of Human Motion Data via Stick Figures , 2012, Comput. Graph. Forum.

[44]  James Davis,et al.  Motion capture data retrieval using an artist’s doll , 2008, 2008 19th International Conference on Pattern Recognition.