motione participant Arts, media and Engineering

computer screens

creating integrated physical-digital experiences research
dancers movement in real time
creating hybrid experiences

Real time, multi-level motion analysis (part 2)

Motion analysis in real time, as part of an interactive composition, creates increased challenges

  1. the motion capture challenges described above decrease substantially the quality of marker labeling, particularly when multiple movers are involved
  2. real time constraints limit the amount of computations that can be performed before an analysis decision needs to be made and feedback provided
  3. the computational load sometimes exceeds the ability of even high-end computational resources available at labs like AME/IREMA
  4. no opportunity exists to look forward in time for testing and corroborating analysis decisions

Real time motion analysis accomplishments of the motione project
Three key accomplishments have been developed and implemented in real time motion analysis for the motione project by the AME/IREMA team:

  1. real time pose recognition engine that works with labeled and unlabeled markers
  2. engine using only unlabelled markers that: tracks multiple dancers, recognizes dancer groupings and shapes in global space, calculate dancers’ speed of movement and rate of activity, calculates translational velocity correlation and activity correlation of dancers and related offsets.
  3. engine for the extraction of statistical (probabilistic) middle and high level features of choreography (form extraction) and use of these features for improvement of low level analysis.



The Katherine K. Herberger College of Fine Art and the Ira A. Fulton School of Engineering at Arizona State University.
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