LAUSR

Gesture recognition has become a hot spot in the direction of artificial intelligence and has great research significance. At present, some classical algorithms, such as the neural network method and the hidden Markov method, have the disadvantages of large computational complexity and long training time. This paper proposes the support vector machine (SVM) algorithm to realize gesture recognition. In order to make the recognition more accurate, SVM is combined with the principal component analysis (PCA) algorithm, performs the dimensionality reduction on the gesture image to form the PCA + SVM algorithm for gesture recognition. At the same time, a new dynamic gesture recognition processing method is proposed, and its effectiveness is proved by various methods. Using open-source computer vision library (OPENCV), the algorithm is simulated on visual studio 2015 environment. The results show that the algorithm has an excellent recognition effect.