Dynamically Weighted DTW for Dynamic Full-Body Gesture Recognition

نویسندگان

  • Hyo-Rim Choi
  • HyeYeon Cho
  • TaeYong Kim
چکیده

As sensor technology has become more advanced, research projects exploring new ways in human-computer interaction have been enabled. Especially, after the Kinect released, study of gesture recognition for human-computer interaction using Kinect has become popular. Dynamic Time Warping (DTW) is one of the template matching algorithm used in the field of gesture recognition. By selecting the most similar gesture compared with the DTW to input sequence and reference sequence of the database, it is possible to achieve a gesture recognition. When trying to recognize a dynamic full-body gesture in Kinect environment, we have to compare all joints throughout the body. When calculating the similarity of the two sequences, all joints of the body is not important in the same way. We propose a dynamically weighted DTW method based on the displacement of the joint. The proposed method shows good performance in the experimental results.

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تاریخ انتشار 2015