Gesture recognition is a hot research topic in the field of human-com p uter interaction.At present,the problem of gesture recognition based on vision is still a difficult point of research.There are still big problems in gesture recognition under the changing background.In recent years,with the rapid deve lopment of deep neural network technology,using network autonomous learning met hods to extract gesture-related features has received extensive attention.Beca u se the convolutional neural network has strong learning ability and individual f eature expression ability,for the traditional gesture recognition algorithm wit h low precision and poor robustnesst,this paper based TensorFlow framework to a dd flattened convolution module proposes a simple convolutional neural network g esture recognition algorithm FD-CNN network.After the data set is preprocessed , the gesture recognition method based on FD-CNN network can directly input the p reprocessed image into the network for training,and the recognition accuracy of the final output test result is 99.0%.Compared with the traditional method and the classical neural network,this paper method improves the network system to the sample data diversity and the complexity effective discrimination,has the h igher recognition rate and the better robustness effect.