Enhancing Hand Gesture Recognition with Media Pipe and SVM Model on Custom Dataset

Gesture recognition is an important area of research with many potential applications such as human-computer interaction, language recognition, and gaming. In this research paper a new approach to motion recognition using the Media Pipe and SVM models has been explained. The approach includes preprocessing the video motion input, using Media Pipe to extract relevant features, and using an SVM model to classify the annotation and to evaluate the proposed methods in public information and demonstrate the effectiveness of the plan by achieving high accuracy.