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Motion Tracker: Camera-Based Monitoring of Bodily Movements Using Motion Silhouettes

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  • Jacqueline Kory Westlund
  • Sidney K D’Mello
  • Andrew M Olney

Abstract

Researchers in the cognitive and affective sciences investigate how thoughts and feelings are reflected in the bodily response systems including peripheral physiology, facial features, and body movements. One specific question along this line of research is how cognition and affect are manifested in the dynamics of general body movements. Progress in this area can be accelerated by inexpensive, non-intrusive, portable, scalable, and easy to calibrate movement tracking systems. Towards this end, this paper presents and validates Motion Tracker, a simple yet effective software program that uses established computer vision techniques to estimate the amount a person moves from a video of the person engaged in a task (available for download from http://jakory.com/motion-tracker/). The system works with any commercially available camera and with existing videos, thereby affording inexpensive, non-intrusive, and potentially portable and scalable estimation of body movement. Strong between-subject correlations were obtained between Motion Tracker’s estimates of movement and body movements recorded from the seat (r =.720) and back (r = .695 for participants with higher back movement) of a chair affixed with pressure-sensors while completing a 32-minute computerized task (Study 1). Within-subject cross-correlations were also strong for both the seat (r =.606) and back (r = .507). In Study 2, between-subject correlations between Motion Tracker’s movement estimates and movements recorded from an accelerometer worn on the wrist were also strong (rs = .801, .679, and .681) while people performed three brief actions (e.g., waving). Finally, in Study 3 the within-subject cross-correlation was high (r = .855) when Motion Tracker’s estimates were correlated with the movement of a person’s head as tracked with a Kinect while the person was seated at a desk (Study 3). Best-practice recommendations, limitations, and planned extensions of the system are discussed.

Suggested Citation

  • Jacqueline Kory Westlund & Sidney K D’Mello & Andrew M Olney, 2015. "Motion Tracker: Camera-Based Monitoring of Bodily Movements Using Motion Silhouettes," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-27, June.
  • Handle: RePEc:plo:pone00:0130293
    DOI: 10.1371/journal.pone.0130293
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    1. repec:thr:techub:10027:y:2022:i:1:p:269-289 is not listed on IDEAS
    2. Ting Tao & Ryota Sato & Yusuke Matsuda & Jumpei Takata & Fijun Kim & Yukio Daikubara & Koji Fujita & Kotaro Hanamoto & Fumio Kinoshita & Ricki Colman & Mamiko Koshiba, 2020. "Elderly Body Movement Alteration at 2nd Experience of Digital Art Installation with Cognitive and Motivation Scores," J, MDPI, vol. 3(2), pages 1-13, April.
    3. Bahaa Mustafa, 2022. "Using 3D Animation and Virtual Reality in Educations," Technium Social Sciences Journal, Technium Science, vol. 27(1), pages 269-289, January.

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