Abstract
Recent improvements in imaging sensors and computing units have led to the development of a range of image-based human-machine interfaces (HMIs). An important approach in this direction is the use of dynamic hand gestures for a gesture-based interface, and some methods have been developed to provide real-time hand skeleton generation from depth images for dynamic hand gesture recognition. Towards this end, we propose a skeleton-based dynamic hand gesture recognition method that divides geometric features into multiple parts and uses a gated recurrent unit-recurrent neural network (GRU-RNN) for each feature part. Because each divided feature part has fewer dimensions than an entire feature, the number of hidden units required for optimization is reduced. As a result, we achieved similar recognition performance as the latest methods with fewer parameters.
Highlights
Gestures are the basic elements used by humans to express meaningful movements [1], and many studies have been conducted on the development of gesture-based human–machine interfaces (HMIs) [2]
We propose a neural-network-based recognition method for dynamic hand gestures that is suitable for constructing HMI systems
Unlike existing methods that used the entire feature for their input, our method divided the features into multiple parts and used them as inputs for the gated recurrent unit-recurrent neural network (GRU-RNN) for each hand part
Summary
Gestures are the basic elements used by humans to express meaningful movements [1], and many studies have been conducted on the development of gesture-based human–machine interfaces (HMIs) [2]. Hand gestures are natural and frequently used in face-to-face interactions; they can be used to make intuitive HMIs [3]. Some researchers have used ‘‘data gloves’’ to acquire hand movement information [4], this method cannot be widely implemented because it requires expensive hardware. Recent studies have proposed hand gesture recognition using image-based methods incorporating relatively cheap imaging sensors. Hand gestures can be either static or dynamic [5]. Dynamic hand gestures involve both hand shape and movement, and, The associate editor coordinating the review of this manuscript and approving it for publication was Huanqing Wang
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