Modified Dynamic Time Warping Based on Direction Similarity for Fast Gesture Recognition

Abstract

We propose a modified dynamic time warping (DTW) algorithm that compares gesture-position sequences based on the direction of the gestural movement. Standard DTW does not specifically consider the two-dimensional characteristic of the user’s movement. Therefore, in gesture recognition, the sequence comparison by standard DTW needs to be improved. The proposed gesture-recognition system compares the sequences of the input gesture’s position with gesture positions saved in the database and selects the most similar gesture by filtering out unrelated gestures. The suggested algorithm uses the cosine similarity of the movement direction at each moment to calculate the difference and reflects the characteristics of the gesture movement by using the ratio of the Euclidean distance and the proportional distance to the calculated difference. Selective spline interpolation assists in solving the issue of recognition-decline at instances of gestures. Through experiments with public databases (MSRC-12 and G3D), the suggested algorithm revealed an improved performance on both databases compared to other methods.