Review of Human Gesture Recognition Based on Computer Vision Technology

Over the years, with continuous expansion of the application fields of intelligent video surveillance, technologies related to human gesture recognition have received more attention and become a research hotspot. This paper first shows the architecture of the intelligent surveillance system, and the corresponding computer vision task of human gesture recognition, such as target detection, feature fusion and scene understanding. Then, in order to better understand related technologies, typical methods based on statistics, template and deep learning are summarized, the characteristics and implementation of convolutional neural networks are introduced in detail. Third, some data sets are listed, and we compare existing models in different projects of human body pose estimation from performance indicators. Finally, the flow chart of crowd posture estimation is designed, with the key modules being explained, which helps better understand the mechanism of gesture recognition. Therefore, this paper has certain theoretical value and application significance.