The invention relates to a Chinese gesture language recognition method based on a convolutional neural network. The method comprises the following steps of collecting various gesture pictures of Chinese gesture language, and obtaining multiple gesture samples through gesture segmentation and preprocessing; dividing an obtained gesture sample dataset into a training set, a verifying set and a testing set according to the proportion of 5:1:1; building seven layers of convolutional neural network CNN models, wherein the convolutional neural network CNN models include three convolutional layers, two pooling layers and one fully-connecting layer; using the gesture features of the CNN model training set to set the image quantity of batchsize after batching every time, and selecting the featuresafter each convulsion through maximal pooling; after the last convolution of layers, classifying feature vectors through a Softmax function, classifying the result, comparing labels, and updating theweight of the model; comparing the accuracy of the verification set after each iteration, and comparing the result with the last verification result; if the accuracy is lowered, continuing the iteration, and if the accuracy is not lowered, stopping the iteration.