Ping-pong ball trajectory tracking device and method based on deep learning

A trajectory tracking and table tennis technology, applied in the embedded field, can solve the problems of players not being able to get a better batting plan, the shortcomings of difficult batting, and affecting the correct analysis of the game by the coaches.

Pending Publication Date: 2021-04-23
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

[0002] At present, the common analysis of table tennis events is based on the subjective judgment of human eyes and coaches. Because the coach observes the trajectory from a single perspective, there will be visual misalignment of the position of the table tennis ball. The coach cannot accurately obtain the three-dimensional trajectory information of the table tennis ball.
Correct game analysis has high requirements on the ability of coaches, which also makes it impossible for players to get better batting plans in most table tennis games
In addition, in some cases, the coach needs to review the previous ...

Method used

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  • Ping-pong ball trajectory tracking device and method based on deep learning
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  • Ping-pong ball trajectory tracking device and method based on deep learning

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Embodiment Construction

[0045] In view of this, the purpose of the present invention is to provide a neural network-based table tennis trajectory tracking device comprising: attitude sensing racket 14, six-axis sensor 13, wireless transmission device 24, first camera 11, second camera 12, USB3. 1 transmission device 21, FPGA22, visual processing unit 23, central processing unit 31, display screen 41, memory 32, GPRS module 33 and network device 42, wherein:

[0046] An attitude sensor is set in the attitude sensing racket 14 to obtain the batting state;

[0047] The six-axis sensor 13 is installed on the first camera 11 and the second camera 12 to obtain the pitch angle of the camera;

[0048] The wireless transmission device 24 wirelessly transmits the data of the attitude sensing racket 14 and the six-axis sensor 13 to the central processing unit 31 in the 2.4GHz frequency band;

[0049] The first camera 11 and the second camera 12 are two high-speed industrial cameras;

[0050] FPGA22 is used fo...

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Abstract

The invention discloses a ping-pong ball trajectory tracking device and method based on deep learning. The device comprises a posture sensing racket, a six-axis sensor, wireless transmission equipment, a first camera, a second camera, USB 3.1 transmission equipment, an FPGA, a visual processing unit, a central processing unit, a display screen, a memory, a GPRS module and network equipment. Two cameras capture table tennis pictures, the FPGA, the visual processing unit and the central processing unit are combined with the posture sensing racket to obtain a table tennis track, track analysis is conducted, the ball hitting condition of a player is obtained, the memorizer is used for storing data, the data is uploaded to the cloud through the GPRS module, and real-time checking is achieved. The three-dimensional position of the ping-pong ball is obtained in real time, the motion trail of the ping-pong ball is drawn, ball hitting conditions of players are analyzed, equipment is arranged in an embedded mode, utilized resources are small, and operation is easy and convenient.

Description

technical field [0001] The invention belongs to the embedded field, and in particular relates to a table tennis trajectory tracking device and method based on deep learning. Background technique [0002] At present, the common analysis of table tennis events is through the subjective judgment of human eyes and coaches. Because the coach observes the trajectory from a single perspective, there will be visual misalignment of the position of the table tennis ball. The coach cannot accurately obtain the three-dimensional trajectory information of the table tennis ball. Correct game analysis has high requirements on the ability of coaches, which also makes it impossible for players to get better batting plans in most table tennis games. In addition, in some cases, the coach needs to review the previous game video to review the table tennis game. The multiple switching of the camera perspective and a single perspective will also affect the coach’s judgment on the trajectory of the...

Claims

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Application Information

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IPC IPC(8): H04N5/225G06K9/62G06N3/04G06N3/08
CPCG06N3/08H04N23/50G06N3/045G06F18/23213
Inventor 顾程鑫郑雨欣李伟钟沁轩黄继业
Owner HANGZHOU DIANZI UNIV
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