Modosc: A Library of Real-Time Movement Descriptors for Marker-Based Motion Capture

被引:3
|
作者
Dahl, Luke [1 ]
Visi, Federico [2 ]
机构
[1] Univ Virginia, Dept Mus, Charlottesville, VA 22903 USA
[2] Univ Hamburg, Inst Systemat Musicol, Hamburg, Germany
来源
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON MOVEMENT AND COMPUTING (MOCO'18) | 2018年
基金
欧洲研究理事会;
关键词
Motion capture; motion descriptors; motion analysis; expressive movement; interaction design; Max; Open Sound Control; modosc;
D O I
10.1145/3212721.3212842
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Marker-based motion capture systems that stream precise movement data in real-time afford interaction scenarios that can be subtle, detailed, and immediate. However, challenges to effectively utilizing this data include having to build bespoke processing systems which may not scale well, and a need for higher-level representations of movement and movement qualities. We present modosc, a set of Max abstractions for computing motion descriptors from raw motion capture data in real time. Modosc is designed to address the data handling and synchronization issues that arise when working with complex marker sets, and to structure data streams in a meaningful and easily accessible manner. This is achieved by adopting a multiparadigm programming approach using o.dot and Open Sound Control. We describe an initial set of motion descriptors, the addressing system employed, and design decisions and challenges.
引用
收藏
页数:4
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