Relational databases for motion data

Motion capture data have been widely used in applications ranging from video games and animations to simulations and virtual environments. Moreover, all data-driven approaches for analysis and synthesis of motions are depending on motion capture data. Although multiple large motion capture datasets are freely available for research, there is no system which can provide a centralised access to all of them in an organised manner. In this paper, we show that using a relational database management system RDBMS to store data not only provide such a centralised access to the data, but also allows to include other sensor modalities e.g., accelerometer data and various semantic annotations. We present two applications for our system: a motion capture player where motions sequences can be retrieved from large datasets using SQL queries and the automatic construction of statistical models which can further be used for complex motion analysis and motions synthesis tasks.

[1]  Michael Garland,et al.  Free-form motion processing , 2008, TOGS.

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

[3]  Maryann Simmons,et al.  Model-based reconstruction for creature animation , 2002, SCA '02.

[4]  Tido Röder,et al.  Documentation Mocap Database HDM05 , 2007 .

[5]  Björn Krüger,et al.  Retrieval, recognition and reconstruction of quadruped motions , 2014, 2014 International Conference on Computer Graphics Theory and Applications (GRAPP).

[6]  Sharat Chandran,et al.  Search and transitioning for motion captured sequences , 2005, VRST '05.

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

[8]  Meinard Müller,et al.  Multi-Mode Tensor Representation of Motion Data , 2008, J. Virtual Real. Broadcast..

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

[10]  Eugene Fiume,et al.  An efficient search algorithm for motion data using weighted PCA , 2005, SCA '05.

[11]  Reinhard Klein,et al.  Efficient unsupervised temporal segmentation of human motion , 2014, SCA '14.

[12]  Michael Garland,et al.  Editing arbitrarily deforming surface animations , 2006, SIGGRAPH 2006.

[13]  Björn Krüger,et al.  One Small Step for a Man: Estimation of Gender, Age and Height from Recordings of One Step by a Single Inertial Sensor , 2015, Sensors.

[14]  Richard E. Parent,et al.  Automated generation of control skeletons for use in animation , 2002, The Visual Computer.

[15]  Thomas J. Cashman,et al.  A continuous, editable representation for deforming mesh sequences with separate signals for time, pose and shape , 2012, Comput. Graph. Forum.

[16]  Jane Wilhelms,et al.  Anatomically based modeling , 1997, SIGGRAPH.

[17]  Nicolas Courty,et al.  A Database Architecture for Real-Time Motion Retrieval , 2009, 2009 Seventh International Workshop on Content-Based Multimedia Indexing.

[18]  Gutemberg Guerra-Filho,et al.  The human motion database: A cognitive and parametric sampling of human motion , 2011, Face and Gesture 2011.

[19]  Scott Schaefer,et al.  Example-based skeleton extraction , 2007, Symposium on Geometry Processing.

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

[21]  Ilya Baran,et al.  Automatic rigging and animation of 3D characters , 2007, SIGGRAPH 2007.

[22]  Helmut Pottmann,et al.  Shape space exploration of constrained meshes , 2011, ACM Trans. Graph..

[23]  Hans-Peter Seidel,et al.  Automatic Conversion of Mesh Animations into Skeleton‐based Animations , 2008, Comput. Graph. Forum.

[24]  M. Kilian,et al.  Geometric modeling in shape space , 2007, SIGGRAPH 2007.

[25]  Jessica K. Hodgins,et al.  Animation of dynamic legged locomotion , 1991, SIGGRAPH.

[26]  Tobias Schreck,et al.  MotionExplorer: Exploratory Search in Human Motion Capture Data Based on Hierarchical Aggregation , 2013, IEEE Transactions on Visualization and Computer Graphics.

[27]  Jinxiang Chai,et al.  Synthesis and editing of personalized stylistic human motion , 2010, I3D '10.

[28]  Jinxiang Chai,et al.  Motion graphs++ , 2012, ACM Trans. Graph..

[29]  A. Karpathy,et al.  Locomotion skills for simulated quadrupeds , 2011, ACM Trans. Graph..

[30]  Jessica K. Hodgins,et al.  Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  Edgar Chia-Han Lin.  A Research on 3D Motion Database Management and Query System Based on Kinect , 2015 .

[32]  Jürgen Bernard,et al.  FuryExplorer: visual-interactive exploration of horse motion capture data , 2015, Electronic Imaging.

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

[34]  Q. Wu,et al.  Development of a Computer Tool for Anthropometric Analyses , 2003, METMBS.

[35]  John P. Lewis,et al.  Pose Space Deformation: A Unified Approach to Shape Interpolation and Skeleton-Driven Deformation , 2000, SIGGRAPH.

[36]  Raoul Wessel,et al.  Action graph a versatile data structure for action recognition , 2014, 2014 International Conference on Computer Graphics Theory and Applications (GRAPP).

[37]  David A. Forsyth,et al.  Automatic Annotation of Everyday Movements , 2003, NIPS.

[38]  Björn Krüger,et al.  Motion reconstruction using very few accelerometers and ground contacts , 2015, Graph. Model..

[39]  Reinhard Klein,et al.  Interactive steering of mesh animations , 2012, SCA '12.

[40]  Michael J. Black,et al.  HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion , 2010, International Journal of Computer Vision.

[41]  Yi Lin,et al.  Efficient human motion retrieval in large databases , 2006, GRAPHITE '06.

[42]  Rudy J. Lapeer,et al.  Physics-based animation of a trotting horse in a virtual environment , 2005, Ninth International Conference on Information Visualisation (IV'05).