Evidence map›Paper›PMID 39138735›Full record

ArticleBehavior research methods2024

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

Christel Bidet-Ildei, Olfa BenAhmed, Diaddin Bouidaine, Victor Francisco, Arnaud Decatoire, Yannick Blandin, Jean Pylouster, Christine Fernandez-Maloigne

Abstract read
PubMed Publisher
In one paragraph

Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Christel Bidet-IldeiCNRS, Centre de Recherches sur la Cognition et l'Apprentissage CeRCA/MSHS, Université de Poitiers, Université de Tours, Bâtiment A5, 5, rue Théodore Lefebvre, TSA 21103, 86073, Poitiers Cedex 9, France. christel.bidet@univ-poitiers.fr.ORCID 0000-0002-4699-179X
Olfa BenAhmedXLIM Research Institute, UMR CNRS 7252, University of Poitiers, Poitiers, France.
Diaddin BouidaineXLIM Research Institute, UMR CNRS 7252, University of Poitiers, Poitiers, France.
Victor FranciscoCNRS, Centre de Recherches sur la Cognition et l'Apprentissage CeRCA/MSHS, Université de Poitiers, Université de Tours, Bâtiment A5, 5, rue Théodore Lefebvre, TSA 21103, 86073, Poitiers Cedex 9, France.
Arnaud DecatoireISAE-ENSMA, CNRS, PPRIME, Université de Poitiers, Poitiers, France.
Yannick BlandinCNRS, Centre de Recherches sur la Cognition et l'Apprentissage CeRCA/MSHS, Université de Poitiers, Université de Tours, Bâtiment A5, 5, rue Théodore Lefebvre, TSA 21103, 86073, Poitiers Cedex 9, France.
Jean PylousterCNRS, Centre de Recherches sur la Cognition et l'Apprentissage CeRCA/MSHS, Université de Poitiers, Université de Tours, Bâtiment A5, 5, rue Théodore Lefebvre, TSA 21103, 86073, Poitiers Cedex 9, France.
Christine Fernandez-MaloigneXLIM Research Institute, UMR CNRS 7252, University of Poitiers, Poitiers, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial IntelligenceAdultFemaleHumansMaleVisual PerceptionYoung AdultArtificial intelligenceBiological movementsDeep learningPerceptionPoint-light displayPsychologyScrambled movements

Identifiers

PMID39138735

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.