Proposes an online hand gesture recognition system using 3D CNNs achieving 98%+ detector accuracy and 90%+ classifier accuracy on Jester, with 37.5% Levenshtein accuracy on a homemade dataset.
2018 International Conference on Applied and Theoretical Electricity (ICATE) , pages=
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Online Hand Gesture Recognition Using 3D Convolutional Neural Networks
Proposes an online hand gesture recognition system using 3D CNNs achieving 98%+ detector accuracy and 90%+ classifier accuracy on Jester, with 37.5% Levenshtein accuracy on a homemade dataset.