Wireless Play Music Beep Sensor to Assist in Music Fountain Control. (18th August 2022)
- Record Type:
- Journal Article
- Title:
- Wireless Play Music Beep Sensor to Assist in Music Fountain Control. (18th August 2022)
- Main Title:
- Wireless Play Music Beep Sensor to Assist in Music Fountain Control
- Authors:
- Wang, Qian
- Other Names:
- Sun Gengxin Academic Editor.
- Abstract:
- Abstract : Musical water landscape combines landscape design with audiovisual art and is loved by the general public. However, the performance control form of musical water landscape generally adopts the manual offline preprogramming method, which needs to use the human subject's consciousness to perceive the style, emotion, and other advanced features of the music first and then choreographs the corresponding landscape performance, which is a high-cost design form and low usage rate of the landscape and is not conducive to the expansion of the music library. In this paper, we design and implement a musical water landscape simulation system using OpenGL and 3Dmax technology in combination with wireless music buzzer sensors, extract and analyze the music features based on this system, and study the system control of musical water landscape. Open GL particle system technology is used to realize the dynamic simulation of weather and fountain inside the landscape and improve the drawing scheme from both modeling and rendering aspects. For the fountain, the physical model and the wireless music beep sensor are combined to design a variety of water type actions for a single spout, and the parameter interface to control the water type changes is reserved. We propose a style recognition method based on CRNN and residual network, which has a higher accuracy rate compared with the existing methods; we use the DP algorithm to segment the pitch sequence of the music to reduce theAbstract : Musical water landscape combines landscape design with audiovisual art and is loved by the general public. However, the performance control form of musical water landscape generally adopts the manual offline preprogramming method, which needs to use the human subject's consciousness to perceive the style, emotion, and other advanced features of the music first and then choreographs the corresponding landscape performance, which is a high-cost design form and low usage rate of the landscape and is not conducive to the expansion of the music library. In this paper, we design and implement a musical water landscape simulation system using OpenGL and 3Dmax technology in combination with wireless music buzzer sensors, extract and analyze the music features based on this system, and study the system control of musical water landscape. Open GL particle system technology is used to realize the dynamic simulation of weather and fountain inside the landscape and improve the drawing scheme from both modeling and rendering aspects. For the fountain, the physical model and the wireless music beep sensor are combined to design a variety of water type actions for a single spout, and the parameter interface to control the water type changes is reserved. We propose a style recognition method based on CRNN and residual network, which has a higher accuracy rate compared with the existing methods; we use the DP algorithm to segment the pitch sequence of the music to reduce the redundancy of information and improve the calculation speed of the system. … (more)
- Is Part Of:
- Journal of sensors. Volume 2022(2022)
- Journal:
- Journal of sensors
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08-18
- Subjects:
- Detectors -- Periodicals
681.205 - Journal URLs:
- https://www.hindawi.com/journals/js/ ↗
- DOI:
- 10.1155/2022/7163937 ↗
- Languages:
- English
- ISSNs:
- 1687-725X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23202.xml