A windowed dynamic time warping approach for 3D continuous hand gesture recognition

Detecting the beginning and end of a specific gesture from an infinite trajectory gesture sequence has gained considerable interests in the past several years. Traditional begin-end dynamic time warping approach for gesture recognition could provide multiple different gesture labels for one trajectory segment. This paper presents a Windowed Dynamic Time Warping (WDTW) approach for 3D continuous hand trajectory gesture recognition. The main contribution is that we introduce a parameterized searching window in the cost matrix of traditional DTW approach to detect the beginning and end of the specific gesture from an infinite trajectory gesture sequence. By doing so, we formulate continuous gesture recognition into online parameter estimation of the searching window. Moreover, the proposed gesture recognition can handle the multilabel issue. We evaluate the proposed windowed dynamic time warping approach in our gesture dataset. The experimental results show that the proposed WDTW can significantly improve the begin-end gesture recognition performance.