SHREC 2024: Recognition of dynamic hand motions molding clay
Publication date
2024-10
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Abstract
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.
Keywords
3D shape retrieval challenge, Gesture recognition, Hand skeleton gestures, Motion capture, Neural networks, SHREC, Software, Signal Processing, General Engineering, Human-Computer Interaction, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design
Citation
Veldhuijzen, B, Veltkamp, R C, Ikne, O, Allaert, B, Wannous, H, Emporio, M, Giachetti, A, LaViola, J J, He, R, Benhabiles, H, Cabani, A, Fleury, A, Hammoudi, K, Gavalas, K, Vlachos, C, Papanikolaou, A, Romanelis, I, Fotis, V, Arvanitis, G, Moustakas, K, Hanik, M, Nava-Yazdani, E & von Tycowicz, C 2024, 'SHREC 2024 : Recognition of dynamic hand motions molding clay', Computers and Graphics (Pergamon), vol. 123, 104012. https://doi.org/10.1016/j.cag.2024.104012