Muneeb Ur Rehman1, Fawad Ahmed1, Muhammad Attique Khan2, Usman Tariq3, Faisal Abdulaziz Alfouzan4, Nouf M. Alzahrani5, Jawad Ahmad6,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4675-4690, 2022, DOI:10.32604/cmc.2022.019586
- 11 October 2021
Abstract Recognition of dynamic hand gestures in real-time is a difficult task because the system can never know when or from where the gesture starts and ends in a video stream. Many researchers have been working on vision-based gesture recognition due to its various applications. This paper proposes a deep learning architecture based on the combination of a 3D Convolutional Neural Network (3D-CNN) and a Long Short-Term Memory (LSTM) network. The proposed architecture extracts spatial-temporal information from video sequences input while avoiding extensive computation. The 3D-CNN is used for the extraction of spectral and spatial features More >
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