Research on Gesture Recognition Method Based on Image Processing and SIFT-SVM

Aiming at the problem that the accuracy of gesture recognition is not high due to the camera's shooting angle and depth information being affected by illumination, this paper proposes a gesture recognition method based on image processing and SIFT-SVM. First construct a gesture recognition data set, perform image processing such as denoising and segmentation on the collected pictures, then extract the geometric features of gestures through the Scale-invariant feature transform (SIFT) algorithm, and finally use the support vector machine (SVM) to classifies and recognizes different detected gestures. The simulation experiment results show that the accuracy of the method proposed in this paper reaches 99.89%, it has strong robustness, and the recognition speed is faster to meet the needs of general applications.