SmartDetector: Automatic and vision-based approach to point-light display generation for human action perception

Over the past four decades, point-light displays (PLD) have been integrated into psychology and psychophysics, providing a valuable means to probe human perceptual skills. Leveraging the inherent kinematic information and controllable display parameters, researchers have utilized this technique to examine the mechanisms involved in learning and rehabilitation. However, classical PLD generation methods (e.g., motion capture) are difficult to apply for behavior analysis in real-world situations, such as patient care or sports activities. Therefore, there is a demand for automated and affordable tools that enable efficient and real-world-compatible generation of PLDs for psychological research. In this paper, we propose SmartDetector, a new artificial intelligence (AI)-based tool for automatic PLD creation from RGB videos. To evaluate humans' perceptual skills for processing PLD building with SmartDetector, 126 participants were randomly assigned to recognition, discrimination, or detection tasks. Results demonstrated that, irrespective of the task, PLDs generated by SmartDetector exhibited commendable perceptual performance in terms of accuracy and response times compared to literature findings. Moreover, to enhance usability and broaden accessibility, we developed an intuitive web interface for our method, making it available to a wider audience. The resulting application is available at https://plavimop.prd.fr/index.php/en/automatic-creation-pld . SmartDetector offers interesting possibilities for using PLD in research and makes the use of PLD more accessible for nonacademic applications.

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Institutions

Publication Details

Journal
Behavior Research Methods
Published
2024-08-13
DOI
https://doi.org/10.3758/s13428-024-02478-1
Citations
4
Primary Topic
Visual perception and processing mechanisms
Type
article
Field-Weighted Citation Impact
1.37

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article

SmartDetector: Automatic and vision-based approach to point-light display generation for human action perception

Jean Pylouster, Victor Francisco, Christel Bidet-Ildei, Arnaud Decatoire et al.
4 citations
Behavior Research Methods
Visual perception and processing mechanisms
1.37
article

SmartDetector: Automatic and vision-based approach to point-light display generation for human action perception

Jean Pylouster, Victor Francisco, Christel Bidet-Ildei, Arnaud Decatoire, Yannick Blandin, Diaddin Bouidaine, Olfa Ben-Ahmed, Christine Fernández-Maloigne
article en
4 citations

Abstract

Over the past four decades, point-light displays (PLD) have been integrated into psychology and psychophysics, providing a valuable means to probe human perceptual skills. Leveraging the inherent kinematic information and controllable display parameters, researchers have utilized this technique to examine the mechanisms involved in learning and rehabilitation. However, classical PLD generation methods (e.g., motion capture) are difficult to apply for behavior analysis in real-world situations, such as patient care or sports activities. Therefore, there is a demand for automated and affordable tools that enable efficient and real-world-compatible generation of PLDs for psychological research. In this paper, we propose SmartDetector, a new artificial intelligence (AI)-based tool for automatic PLD creation from RGB videos. To evaluate humans' perceptual skills for processing PLD building with SmartDetector, 126 participants were randomly assigned to recognition, discrimination, or detection tasks. Results demonstrated that, irrespective of the task, PLDs generated by SmartDetector exhibited commendable perceptual performance in terms of accuracy and response times compared to literature findings. Moreover, to enhance usability and broaden accessibility, we developed an intuitive web interface for our method, making it available to a wider audience. The resulting application is available at https://plavimop.prd.fr/index.php/en/automatic-creation-pld . SmartDetector offers interesting possibilities for using PLD in research and makes the use of PLD more accessible for nonacademic applications.

Behavior Research MethodsVol. 56(8)
Université de Tours (FR), Centre National de la Recherche Scientifique (FR), École Nationale Supérieure de Mécanique et d'Aérotechnique (FR), Institut Universitaire de France (FR), Institut Pprime (FR), Université de Poitiers (FR), XLIM (FR), Institut Régional de Médecine Physique et de Réadaptation (FR), Centre de Recherches sur la Cognition et l'Apprentissage (FR)
European Commission, Institut Universitaire de France, Conseil Régional Aquitaine, European Regional Development Fund
Reduced inequalities
Openalex Percentile: Top 20%
Visual perception and processing mechanisms
1.37
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