Real-Time Motion Capture Analysis and Music Interaction with the Modosc Descriptor Library

Federico Visi, and Luke Dahl

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract:

We present modosc, a set of Max abstractions designed for computing motion descriptors from raw motion capture data in real time. The library contains methods for extracting descriptors useful for expressive movement analysis and sonic interaction design. modosc is designed to address the data handling and synchronization issues that often arise when working with complex marker sets. This is achieved by adopting a multiparadigm approach facilitated by odot and Open Sound Control to overcome some of the limitations of conventional Max programming, and structure incoming and outgoing data streams in a meaningful and easily accessible manner. After describing the contents of the library and how data streams are structured and processed, we report on a sonic interaction design use case involving motion feature extraction and machine learning.

Citation:

Federico Visi, and Luke Dahl. 2018. Real-Time Motion Capture Analysis and Music Interaction with the Modosc Descriptor Library. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.1302707

BibTeX Entry:

  @inproceedings{Visi2018,
 abstract = {We present modosc, a set of Max abstractions designed for computing motion descriptors from raw motion capture data in real time. The library contains methods for extracting descriptors useful for expressive movement analysis and sonic interaction design. modosc is designed to address the data handling and synchronization issues that often arise when working with complex marker sets. This is achieved by adopting a multiparadigm approach facilitated by odot and Open Sound Control to overcome some of the limitations of conventional Max programming, and structure incoming and outgoing data streams in a meaningful and easily accessible manner. After describing the contents of the library and how data streams are structured and processed, we report on a sonic interaction design use case involving motion feature extraction and machine learning.},
 address = {Blacksburg, Virginia, USA},
 author = {Federico Visi and Luke Dahl},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.1302707},
 editor = {Luke Dahl, Douglas Bowman, Thomas Martin},
 isbn = {978-1-949373-99-8},
 issn = {2220-4806},
 month = {June},
 pages = {144--147},
 publisher = {Virginia Tech},
 title = {Real-Time Motion Capture Analysis and Music Interaction with the Modosc Descriptor Library},
 url = {http://www.nime.org/proceedings/2018/nime2018_paper0031.pdf},
 year = {2018}
}