The invention discloses a static gesture real-time recognition method based on YOLOv3, which comprises the following steps of making a training set, generating a migration Darknet-53 model, improveingcandidate frame parameters and carrying out the real-time gesture recognition, is based on the convolution neural network YOLOv3 model, uses the four types of image datasets collected by Kinect equipment to replace the common RGB image datasets, and the recognition results of four types of Kinect test images are fused to effectively improve the recognition accuracy. The K-Means clustering algorithm is used to improve the parameters of the initial candidate frame to improve the recognition speed effectively. And a transfer learning method is adopted to reduce the training time of the model.