TY - JOUR A1 - Veldhuijzen, Ben A1 - Veltkamp, Remco C. A1 - Ikne, Omar A1 - Allaert, Benjamin A1 - Wannous, Hazem A1 - Emporio, Marco A1 - Giachetti, Andrea A1 - LaViola Jr, Joseph J. A1 - He, Ruiwen A1 - Benhabiles, Halim A1 - Cabani, Adnane A1 - Fleury, Anthony A1 - Hammoudi, Karim A1 - Gavalas, Konstantinos A1 - Vlachos, Christoforos A1 - Papanikolaou, Athanasios A1 - Romanelis, Ioannis A1 - Fotis, Vlassis A1 - Arvanitis, Gerasimos A1 - Moustakas, Konstantinos A1 - Hanik, Martin A1 - Nava-Yazdani, Esfandiar A1 - von Tycowicz, Christoph T1 - SHREC 2024: Recognition Of Dynamic Hand Motions Molding Clay JF - Computers & Graphics N2 - Gesture recognition is a tool to enable novel interactions with different techniques and applications, like Mixed Reality and Virtual Reality environments. With all the recent advancements in gesture recognition from skeletal data, it is still unclear how well state-of- the-art techniques perform in a scenario using precise motions with two hands. This paper presents the results of the SHREC 2024 contest organized to evaluate methods for their recognition of highly similar hand motions using the skeletal spatial coordinate data of both hands. The task is the recognition of 7 motion classes given their spatial coordinates in a frame-by-frame motion. The skeletal data has been captured using a Vicon system and pre-processed into a coordinate system using Blender and Vicon Shogun Post. We created a small, novel dataset with a high variety of durations in frames. This paper shows the results of the contest, showing the techniques created by the 5 research groups on this challenging task and comparing them to our baseline method. Y1 - 2024 U6 - https://doi.org/10.1016/j.cag.2024.104012 VL - 123 SP - 104012 ER -