Relevant questions include:
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What types of features can be extracted from the continuous data? Would it help to look into the biological nature of micromotion (respiration, pulse, etc.)?
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Is it possible to make a "thumbnail" or "motion signature" based on people's standstill data?
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Are there any correlations between people's data? Are these related to people's background (age, gender, musical training, etc.)?
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Are there any correlations between the continuous motion capture data and musical features?
Key References:
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Oslo Standstill Database (data set)
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González Sánchez, V., Zelechowska, A., & Jensenius, A. R. (2018). Correspondences Between Music and Involuntary Human Micromotion During Standstill. Frontiers in Psychology, 9(1382). https://doi.org/10.3389/fpsyg.2018.01382
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González Sánchez, V., Zelechowska, A., & Jensenius, A. R. (2019). Analysis of the Movement-Inducing Effects of Music through the Fractality of Head Sway during Standstill. Journal of Motor Behavior, 1–16.
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Jensenius, A. R., Zelechowska, A., & Gonzalez-Sanchez, V. E. (2017). The Musical Influence on People’s Micromotion when Standing Still in Groups. Proceedings of the Sound and Music Computing Conference, 195–200. http://urn.nb.no/URN:NBN:no-58796
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Zelechowska, A., Sanchez, V. G., & Jensenius, A. R. (2020). Standstill to the “beat”: Differences in involuntary movement responses to simple and complex rhythms. Proceedings of the 15th International Conference on Audio Mostly, 107–113. https://doi.org/10.1145/3411109.3411139
Supervisor: Alexander Refsum Jensenius (a.r.jensenius@imv.uio.no) and Jim Tørresen (jimtoer@ifi.uio.no)