Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition
AbstractCyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. View Full-Text
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Choi, H.-R.; Kim, T. Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition. Sensors 2017, 17, 1893.
Choi H-R, Kim T. Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition. Sensors. 2017; 17(8):1893.Chicago/Turabian Style
Choi, Hyo-Rim; Kim, TaeYong. 2017. "Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition." Sensors 17, no. 8: 1893.
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