CNRS, 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.
Institut Universitaire de France (IUF), Paris, France.
Behav Res Methods. 2024 Dec;56(8):8349-8361. doi: 10.3758/s13428-024-02478-1. Epub 2024 Aug 13.
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.
在过去的四十年中,点光显示(PLD)已经被整合到心理学和心理物理学中,为探究人类感知技能提供了一种有价值的手段。利用固有运动信息和可控显示参数,研究人员利用该技术研究了学习和康复过程中涉及的机制。然而,经典的 PLD 生成方法(例如运动捕捉)难以应用于现实情况下的行为分析,例如患者护理或体育活动。因此,需要一种自动化和经济实惠的工具,以实现用于心理学研究的高效且与现实世界兼容的 PLD 生成。在本文中,我们提出了 SmartDetector,这是一种基于人工智能(AI)的新工具,用于从 RGB 视频中自动创建 PLD。为了评估 SmartDetector 创建 PLD 的人类感知技能,我们随机分配了 126 名参与者进行识别、区分或检测任务。结果表明,无论任务如何,与文献发现相比,SmartDetector 生成的 PLD 在准确性和响应时间方面表现出令人赞赏的感知性能。此外,为了提高可用性并扩大受众范围,我们为我们的方法开发了一个直观的网络界面,使其可供更广泛的受众使用。由此产生的应用程序可在 https://plavimop.prd.fr/index.php/en/automatic-creation-pld 获得。SmartDetector 为在研究中使用 PLD 提供了有趣的可能性,并使非学术应用更容易使用 PLD。