DBSCAN for Hand Tracking and Gesture Recognition

Abstract

Hand segmentation and tracking are important issues for hand-gesture recognition. Using depth data, it can speed up the segmentation process because we can delete unnecessary data like the background of the image easily. In this research, we modify DBSCAN clustering algorithm to make it faster and suitable for our system. This method is used in both hand tracking and hand gesture recognition. The results show that our method performs well in this system. The proposed method can outperform the original DBSCAN and the other clustering method in terms of computational time.