Computer vision-based dynamic gesture recognition method

The invention discloses a computer vision-based dynamic gesture recognition method, and aims at solving the gesture recognition problems under complicated backgrounds. The method is realized through the following steps of: acquiring a gesture data set and carrying out artificial labelling; clustering a labelled image set real frame to obtain a trained prior frame; constructing an end-to-end convolutional neural network which is capable of predicting a target position, a size and a category at the same time; training the network to obtain a weight; loading the weight to the network; inputting agesture image to carrying out recognition; processing an obtained position coordinate and category information via a non-maximum suppression method so as to obtain a final recognition result image; and recording recognition information in real time to obtain a dynamic gesture interpretation result. According to the method, the defect that hand detection and category recognition in gesture recognition are carried out in different steps in the prior art is overcome, the gesture recognition process is greatly simplified, the recognition correctness and speed are improved, the recognition systemrobustness is strengthened, and a dynamic gesture interpretation function is realized.