Calligraphy attitude automatic identification method based on Wi-Fi signals

Abstract

The invention discloses a calligraphy attitude automatic identification method based on Wi-Fi signals. The method comprises the following steps: calligraphy character attitude data is acquired through Wi-Fi signals; feature extraction and stroke segmentation are performed on the data in turn; the data is reconstructed using a learning algorithm; and the writing font is identified by comparing the data with a standard database. The method is implemented using the existing commercial equipment. There is no need to modify the hardware. There is no need for extra deployment for users. Wireless signals are easy to obtain, and can be emitted by opening a hotspot via an ordinary smart mobile device. The CSI value of the physical layer is analyzed using the existing wireless local area network in a non-intrusive and device-independent way. There is no need to change the wireless signal communication protocol. The method has a wide application prospect.

Description

technical field

[0001] The invention relates to the technical field of wireless signal tracking perception and human-computer interaction, in particular to a method for automatic recognition of calligraphy gestures based on Wi-Fi signals. Background technique

[0002] Chinese calligraphy is the art of writing Chinese characters with a special Chinese conical brush, and is an important carrier of Chinese culture. In 2015, the Ministry of Education issued the "Guidelines for Improving the Education of Excellent Chinese Traditional Culture", which further clearly requires students to be able to write Chinese characters in a standardized way, to copy the calligraphy of famous masters, and to experience the beauty and artistic conception of calligraphy. For a long time, the traditional on-the-spot observation-style calligraphy teaching method requires teachers to guide students to make posts, demonstrate and correct calligraphy strokes one by one. In the process of practice, the...

Examples

Embodiment Construction

[0048] The main problems faced by the inventor team in the process of researching calligraphy gesture recognition based on WiFi signals are as follows: First, it is difficult to predict and define the gestures involved in the process of calligraphy movement, the frame structure of writing fonts, the thickness of ink and ink, and the strength of strokes. and quantify. Second, solve the problem of automatic separation of continuous strokes. For the posture tracking process, the collected data is a continuous posture change, but Chinese characters are composed of multiple strokes rather than continuous strokes. The distinction between the two action points of raising the pen and falling the pen is very important. If it is impossible to distinguish between the gestures after the pen is lifted and the pen is put down, and the result is a graffiti-like gesture, then the recognition will be meaningless. Third, there is the problem of different writing scales, that is, the problem of...

technical field

[0001] The invention relates to the technical field of wireless signal tracking perception and human-computer interaction, in particular to a method for automatic recognition of calligraphy gestures based on Wi-Fi signals. Background technique

[0002] Chinese calligraphy is the art of writing Chinese characters with a special Chinese conical brush, and is an important carrier of Chinese culture. In 2015, the Ministry of Education issued the "Guidelines for Improving the Education of Excellent Chinese Traditional Culture", which further clearly requires students to be able to write Chinese characters in a standardized way, to copy the calligraphy of famous masters, and to experience the beauty and artistic conception of calligraphy. For a long time, the traditional on-the-spot observation-style calligraphy teaching method requires teachers to guide students to make posts, demonstrate and correct calligraphy strokes one by one. In the process of practice, the...

Examples

Embodiment Construction

[0048] The main problems faced by the inventor team in the process of researching calligraphy gesture recognition based on WiFi signals are as follows: First, it is difficult to predict and define the gestures involved in the process of calligraphy movement, the frame structure of writing fonts, the thickness of ink and ink, and the strength of strokes. and quantify. Second, solve the problem of automatic separation of continuous strokes. For the posture tracking process, the collected data is a continuous posture change, but Chinese characters are composed of multiple strokes rather than continuous strokes. The distinction between the two action points of raising the pen and falling the pen is very important. If it is impossible to distinguish between the gestures after the pen is lifted and the pen is put down, and the result is a graffiti-like gesture, then the recognition will be meaningless. Third, there is the problem of different writing scales, that is, the problem of...

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