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<p>In this paper, we evaluate the validity of SmartDetector—a markerless motion capture device based on artificial intelligence—by comparing it to a conventional optoelectronic motion capture system (i.e., Qualisys) in the context of stimuli construction for psychological experiments. To this end, simultaneous motion capture recordings were performed using both the conventional system and the SmartDetector, enabling the creation of 2D kinematic data and the generation of two versions of point-light displays. Three perceptual experiments were then conducted to facilitate comparisons between the two systems: a recognition task, a detection task, and a discrimination task. Bayesian analysis was employed to test the null hypotheses regarding the stimuli generated by SmartDetector versus those produced by the conventional motion capture system. The results suggest that participants achieved comparable performance across both types of stimuli depending on the task with reduced processing time and lower costs for SmartDetector. These findings appear to validate SmartDetector as a reliable and accessible alternative for creating point-light displays, reducing processing time and costs, thus reinforcing its potential for widespread adoption by professionals in the field.</p>

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SmartDetector: a valid and affordable AI-based markerless motion capture system for psychological experiments

  • 期刊论文

  • 发表日期：

    2026年1月9日

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  • Victor Francisco,
  • Arnaud Decatoire,
  • Olfa Ben Ahmed,
  • Yannick Blandin,
  • Christel Bidet-Ildei

摘要

In this paper, we evaluate the validity of SmartDetector—a markerless motion capture device based on artificial intelligence—by comparing it to a conventional optoelectronic motion capture system (i.e., Qualisys) in the context of stimuli construction for psychological experiments. To this end, simultaneous motion capture recordings were performed using both the conventional system and the SmartDetector, enabling the creation of 2D kinematic data and the generation of two versions of point-light displays. Three perceptual experiments were then conducted to facilitate comparisons between the two systems: a recognition task, a detection task, and a discrimination task. Bayesian analysis was employed to test the null hypotheses regarding the stimuli generated by SmartDetector versus those produced by the conventional motion capture system. The results suggest that participants achieved comparable performance across both types of stimuli depending on the task with reduced processing time and lower costs for SmartDetector. These findings appear to validate SmartDetector as a reliable and accessible alternative for creating point-light displays, reducing processing time and costs, thus reinforcing its potential for widespread adoption by professionals in the field.