Skeleton data from hand gestures is fused into RGB images and classified by an e2eET multi-stream CNN, yielding competitive accuracy on five datasets and real-time operation on consumer hardware.
An Efficient Graph Convolution Network for Skeleton-Based Dynamic Hand Gesture Recognition,
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Real-Time Hand Gesture Recognition: Integrating Skeleton-Based Data Fusion and Multi-Stream CNN
Skeleton data from hand gestures is fused into RGB images and classified by an e2eET multi-stream CNN, yielding competitive accuracy on five datasets and real-time operation on consumer hardware.