Abstract
With Microsoft’s launch of Kinect in 2010, and release of Kinect SDK in 2011, numerous applications and research projects exploring new ways in human-computer interaction have been enabled. Gesture recognition is a technology often used in human-computer interaction applications. Dynamic time warping (DTW) is a template matching algorithm and is one of the techniques used in gesture recognition. To recognize a gesture, DTW warps a time sequence of joint positions to reference time sequences and produces a similarity value. However, all body joints are not equally important in computing the similarity of two sequences. We propose a weighted DTW method that weights joints by optimizing a discriminant ratio. Finally, we demonstrate the recognition performance of our proposed weighted DTW with respect to the conventional DTW and state-of-
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