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In this paper, we propose a new hand gesture recognition method based onskeletal data by learning SPD matrices with neural networks. We model the handskeleton as a graph and introduce a neural network for SPD matrix learning,taking as input the 3D coordinates of hand joints. The proposed network isbased on two newly designed layers that transform a set of SPD matrices into aSPD matrix. For gesture recognition, we train a linear SVM classifier usingfeatures extracted from our network. Experimental results on a challengingdataset (Dynamic Hand Gesture dataset from the SHREC 2017 3D Shape RetrievalContest) show that the proposed method outperforms state-of-the-art methods.

Skeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks