A Relational Database for Human Motion Data

Qaiser Riaz, Björn Krüger, and Andreas Weber
In: Lecture Notes in Computer Science, Computational Science and Its Applications - ICCSA 2015 (June 2015), 9159(234-249)
 

Abstract

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 data sets are freely available for research, there is no system which can provide a centralized access to all of them in an organized manner. In this paper we show that using a relational database management system (RDBMS) to store data does not only provide such a centralized 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.

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Bibtex

@ARTICLE{riaz2015b,
    author = {Riaz, Qaiser and Kr{\"u}ger, Bj{\"o}rn and Weber, Andreas},
     pages = {234--249},
     title = {A Relational Database for Human Motion Data},
   journal = {Lecture Notes in Computer Science, Computational Science and Its Applications - ICCSA 2015},
    volume = {9159},
      year = {2015},
     month = jun,
  abstract = {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 data sets are freely available for research, there is no
              system which can provide a centralized access to all of them in an organized manner.
              In this paper we show that using a relational database management system (RDBMS) to store data does
              not only provide such a centralized 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.},
       doi = {10.1007/978-3-319-21413-9_17}
}