Abstract-Gesture recognition is a very essential technology for many wearable devices. While previous algorithms are mostly based on statistical methods including the hidden Markov model, we develop two dynamic hand gesture recognition techniques using low complexity recurrent neural network (RNN) algorithms. One is based on video signal and employs a combined structure of a convolutional neural network (CNN) and an RNN. The other uses accelerometer data and only requires an RNN. Fixed-point optimization that quantizes most of the weights into two bits is conducted to optimize the amount of memory size for weight storage and reduce the power consumption in hardware and software based implementations.
Shin et al. REF developed a dynamic hand gesture recognition technique using recurrent neural network (RNN) algorithm.
Dynamic hand gesture recognition for wearable devices with low complexity recurrent neural networks
2016 IEEE International Symposium on Circuits and Systems (ISCAS)
2016 IEEE International Symposium on Circuits and Systems (ISCAS)
Computer Science