| 摘要(英) |
Human-computer interaction has risen in recent years, and the manipulation of things is no longer limited to the remote control via buttons. With the development of gesture recognition research, there have been more and more research institutions actively investing in handwriting recognition in the air, in addition to being widely used globally. Chinese characters that are used by a large number of people have also gradually received attention.
Different from touch-screen handwriting, the in-air written character has no pen-lift information, i.e., a character is always finished writing in one stroke. Compared with the Latin alphabet, the Chinese characters have more than one hundred times more change. In addition, each user′s stroke order when writing Traditional Chinese characters will have a direct impact on the number, position, and direction of strokes generated by the virtual pen.
In this paper, Kinect is used for image capture to obtain depth information, and the movement of the hand become trajectory by analyzing the human skeleton, and the strokes of each word are formed by using the starting and ending motions. After normalization to a certain size, the dimension of the text trajectory is reduced, and features such as turning point, shape context, and eight-direction ratio are extracted. Finally, the identification module is entered and a suitable loss function is designed in conjunction with dynamic time warping to display the first three candidate words. |
| 參考文獻 |
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