Visual noise mask for human point-light displays: A coding-free approach

Human point-light displays consist of luminous dots representing human articulations, thus depicting actions without pictorial information. These stimuli are widely
used in action recognition experiments. Because humans excel in decoding human motion,
point-light displays (PLDs) are often masked with additional moving dots (noise masks),
thereby challenging stimulus recognition. These noise masks are typically found within
proprietary programming software, entail file format restrictions, and demand extensive
programming skills. To address these limitations, we present the first user-friendly stepby-step guide to develop visual noise to mask PLDs using free, open-source software that
offers compatibility with various file formats, features a graphical interface, and facilitates
the manipulation of both 2D and 3D videos. Further, to validate our approach, we tested
two generated masks in a pilot experiment with 12 subjects and demonstrated that they
effectively jeopardised human agent recognition and, therefore, action visibility. In sum, the
main advantages of the presented methodology are its cost-effectiveness and ease of use,
making it appealing to novices in programming. This advancement holds the potential to
stimulate young researchers’ use of PLDs, fostering further exploration and understanding
of human motion perception.
Olivia M. Lapenta is supported by the Psychology Research Centre [PSI/01662], School of Psychology, University of Minho, and by the Portuguese Foundation for Science and Technology through the Portuguese State Budget [UIDB/PSI/01662/2020] [SFRH/BPD/72710/2010]. Adriana C. S. Sampaio is supported by the Psychology Research Centre, School of Psychology, University of Minho, and by the Portuguese Foundation for Science and Technology through the Portuguese State Budget [UIDB/PSI/01662/2020].