Abstract
In recent years, gesture recognition has been widely used in the fields of intelligent driving, virtual reality, and human-computer interaction. With the development of artificial intelligence, deep learning has achieved remarkable success in computer vision. To help researchers better understanding the development status of gesture recognition in video, this article provides a detailed survey of the latest developments in gesture recognition technology for videos based on deep learning. The reviewed methods are broadly categorized into three groups based on the type of neural networks used for recognition: twostream convolutional neural networks, 3D convolutional neural networks, and Long-short Term Memory (LSTM) networks. In this review, we discuss the advantages and limitations of existing technologies, focusing on the feature extraction method of the spatiotemporal structure information in a video sequence, and consider future research directions.
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