Abstract:

With the popularity of Internet of things equipment,the smart wearing equipment industry develops rapidly,in which wristband smart bracelets and watches are the mainstream.Intelligent wearable devices have abundant sensors and certain computing power.As human-computer interaction for itself and other devices of the Internet of things through gesture recognition,they have a wide range of needs.A 3D gesture recognition system based on dynamic template matching algorithm was proposed.The gesture meaning was judged by collecting user’s specific gesture from hand-held smart devices,and the control of smart devices was realized by using more natural human-computer interaction technology.The motion sensor of intelligent devices was used to read the corresponding 3D gesture data,and the optimized dynamic time warping algorithm was used to recognize gesture.Based on the characteristics of mobile devices and dynamic programming,the curve path was defined by slope.At the same time,the calculation of template matching and the cost of gesture recognition were reduced by pre-storage distortion threshold.The test is carried out on mobile phones,compared with the traditional algorithm,the proposed algorithm takes less time,has higher recognition efficiency and accuracy,and can bring better human-computer interaction experience.

Key words: intelligent wearing, gesture recognition, human-computer interaction, dynamic template matching algorithm, dynamic time warping