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Conference Papers Year : 2022

SPD Siamese Neural Network for Skeleton-based Hand Gesture Recognition

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Abstract

This article proposes a new learning method for hand gesture recognition from 3D hand skeleton sequences. We introduce a new deep learning method based on a Siamese network of Symmetric Positive Definite (SPD) matrices. We also propose to use the Contrastive Loss to improve the discriminative power of the network. Experimental results are conducted on the challenging Dynamic Hand Gesture (DHG) dataset. We compared our method to other published approaches on this dataset and we obtained the highest performances with up to 95,60% classification accuracy on 14 gestures and 94.05% on 28 gestures.

Dates and versions

hal-03774564 , version 1 (11-09-2022)

Identifiers

Cite

Mohamed Akremi, Rim Slama, Hedi Tabia. SPD Siamese Neural Network for Skeleton-based Hand Gesture Recognition. 17th International Conference on Computer Vision Theory and Applications VISAPP 2022), Feb 2022, Online Streaming, France. pp.394--402, ⟨10.5220/0010822500003124⟩. ⟨hal-03774564⟩
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