WO2017185222A1 - Système et procédé de collecte et d'analyse de trajectoires de mouvement basés sur des jeux de balles - Google Patents

Système et procédé de collecte et d'analyse de trajectoires de mouvement basés sur des jeux de balles Download PDF

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Publication number
WO2017185222A1
WO2017185222A1 PCT/CN2016/080191 CN2016080191W WO2017185222A1 WO 2017185222 A1 WO2017185222 A1 WO 2017185222A1 CN 2016080191 W CN2016080191 W CN 2016080191W WO 2017185222 A1 WO2017185222 A1 WO 2017185222A1
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WIPO (PCT)
Prior art keywords
data
analysis
acquisition
motion
sensor
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PCT/CN2016/080191
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English (en)
Chinese (zh)
Inventor
黄宇
胡振江
李广贵
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深圳市优宝创科技有限公司
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Application filed by 深圳市优宝创科技有限公司 filed Critical 深圳市优宝创科技有限公司
Priority to CN201680011563.8A priority Critical patent/CN107454970A/zh
Priority to PCT/CN2016/080191 priority patent/WO2017185222A1/fr
Publication of WO2017185222A1 publication Critical patent/WO2017185222A1/fr

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    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/292—Multi-camera tracking

Definitions

  • the invention relates to the technical field of ball motion track monitoring, in particular to a system and method for collecting and analyzing motion track based on ball motion.
  • the existing motion recognition systems are composed of an acquisition module, a communication module and a calculation module.
  • the acquisition module mainly collects and preliminary analyzes data through sensors including acceleration sensors, gyroscopes, magnetometers, and motion and orientation-related sensors, and then transmits the data to the host computer equipment through mobile communication devices, including mobile phones, tablet computers, and the like.
  • the computer performs the final motion analysis. Since the algorithm of motion recognition is based on one or more integrals and spatial transformations of sensor data, the higher the sampling rate, the higher the final motion recognition rate and the higher the trajectory reduction degree. For some ball games with very high speeds, such as badminton, table tennis, baseball, softball, cricket, and football with pitching, the movement rate is very fast, and the sampling rate is not high enough.
  • the present invention provides a ball based motion.
  • Method of motion trajectory acquisition and analysis By using the method provided by the invention, the limitation of communication bandwidth and storage capacity can be solved, and the sampling speed of the sensor can be maximized to achieve the maximum sampling precision.
  • the entire motion process can be analyzed without gap tracking without losing the small motion data. Being able to work independently without relying on the host device greatly simplifies the system architecture, compresses system costs, and simultaneously improves the user experience.
  • a motion trajectory acquisition and analysis system based on ball motion the system comprises an integrated module for data acquisition and analysis, a communication module and a human-machine interface display module, and the integrated module for data acquisition and analysis is connected to a human-machine interface through a communication module.
  • the module, the data acquisition and analysis integration module has a built-in non-volatile memory, an acquisition sensor, and a local data analysis processor, and the acquisition sensor is electrically connected to the local data analysis processor.
  • the invention also includes a method for collecting and analyzing motion trajectories based on ball motion, including data acquisition, data analysis, and data result and important trajectory information output of the ball trajectory, and the data collection and data analysis are collected and analyzed.
  • the integrated module performs data analysis and directly outputs it through the display device that is included in the integrated module of the acquisition and analysis or transmits it to the external terminal device through the communication module.
  • the data acquisition comprises: selecting an applicable acquisition sensor, selecting an appropriate sampling rate, and data acquisition with local data processing capability, multi-axis data fusion through its own processing capability, selecting a required acquisition sensor, and then passing through itself
  • the axis fusion algorithm obtains the linear acceleration affected by the separation of gravity.
  • the acquisition sensor comprises one or more of an acceleration sensor, a gyroscope, a magnetic field sensor, and an audio sensor.
  • the data analysis comprises: the local data analysis processor included in the acquisition and analysis integration module monitors the data collected by the acquisition sensor, determines the current motion type according to the surface data result, and flexibly sets the motion sensor according to the severity of the exercise. Sampling speed.
  • the output of the data result and the important trajectory information comprises: obtaining the analysis result by collecting and analyzing the integrated module data analysis, directly outputting through the display device and the display device on the integrated module, and selectively saving the analysis result in the collection. And analysis of the non-volatile memory that comes with the integrated module The analysis result is filtered according to the predetermined setting condition, and the sound and light and vibration feedback output are output according to the trigger condition, and the user is promptly reminded of the specific event, and the stored data is selectively sent to the upper device through the communication module.
  • the host device can be connected in real time as needed to view real-time results or display for display.
  • the upper device includes a mobile phone, a tablet computer, a PC, and a dedicated terminal.
  • the present invention has the following beneficial effects:
  • the system and method for collecting and analyzing motion path based on ball motion of the present invention can analyze the collected data without gaps because the local data analysis processor does not need to consider the capacity of the data storage and the bandwidth of the transmitted data.
  • the complete analysis of the action solves the limitation of communication bandwidth and storage capacity, maximizes the sampling speed of the sensor, and achieves the maximum sampling accuracy. At the same time, it greatly simplifies the system architecture, compresses the system cost, and simultaneously improves the user experience.
  • FIG. 1 is a schematic structural diagram of a system for collecting and analyzing motion trajectories based on ball motions according to the present invention.
  • a motion trajectory acquisition and analysis system based on ball motion
  • the system includes an integrated module for data acquisition and analysis, a communication module, and a human-machine interface display module, and the data acquisition and analysis integration module communicates
  • the module is connected to the human-machine interface display module, and the data acquisition and analysis integrated module has a built-in non-volatile memory, an acquisition sensor, and a local data analysis processor.
  • the set sensor is electrically connected to the local data analysis processor.
  • the invention also discloses a method for collecting and analyzing motion trajectories based on ball sports, comprising an integrated module for data acquisition and analysis, a communication module and a human-machine interface module, the method comprising data collection, data analysis and data of ball motion trajectories.
  • the result and the important trajectory information output, the data acquisition and the data analysis are performed by the integrated module of the collection and analysis, and after the data analysis, the output device is directly outputted through the collection and analysis integrated module or transmitted to the outside through the communication module.
  • the terminal device uses the appropriate sampling speed for different motions to achieve the highest performance power balance without considering the storage and communication bandwidth.
  • the data acquisition includes: selecting an applicable acquisition sensor, selecting an appropriate sampling rate, data acquisition with local data processing capability, multi-axis data fusion through its own processing capability, selecting a required sensor, and then using its own multi-axis fusion algorithm, The linear acceleration affected by the separation of gravity is obtained, providing an accurate source of data for motion recognition.
  • the multi-axis data fusion process is as follows:
  • the system tilt true angle ⁇ can be used to make a state vector.
  • the accelerometer is used to estimate the gyroscope constant deviation b, and the deviation is used as the state vector to obtain the corresponding state equation and observation equation:
  • ⁇ gyro is the angular velocity output of the gyroscope containing the fixed deviation
  • ⁇ acce is the angle value obtained by the accelerometer after processing
  • ⁇ g is the measurement noise of the gyroscope
  • ⁇ a is the accelerometer measurement noise
  • b is Gyro drift error
  • ⁇ g and ⁇ a are independent of each other.
  • the Kalman filter The recursive operation is performed until the optimal angle value is estimated.
  • the system process noise covariance matrix Q and the covariance matrix R of the measurement error are known to correct the Kalman filter.
  • the form of the Q and R matrix is as follows:
  • q_acce and q_gyro are the covariances measured by the accelerometer and the gyroscope, respectively, and their values represent the degree of trust of the Kalman filter on its sensor data. The smaller the value, the higher the degree of trust. In this system, the value of the gyroscope is closer to the exact value, so the value of q_gyro is less than the value of q_acce.
  • k-1) is the result of k prediction
  • k-1) is the optimal result at time k-1.
  • Equations (1) and (2) update the status of the system.
  • Equations (3), (4), and (5) are Kalman filter state update equations. After calculating the time update equation and the measurement update equation, the posterior estimate obtained from the previous calculation is repeated again as the prior calculation of the next calculation. It is estimated that, in this way, the cycle is repeated and repeated until the optimal result is found.
  • the earth's magnetic field, various magnetic conductive materials in the surface building, and other magnetic field sources together form a unique synthetic magnetic field whose direction is not necessarily the original geomagnetic direction, but is a fixed vector relative to the earth.
  • the 3-axis geomagnetic sensor can measure this vector. Since the geomagnetic sensor and other 6-axis sensor coordinate systems are set to be the same in circuit design, the geomagnetic vector provides an absolute direction reference vector for the resulting attitude after fusion, thus completing the 9-axis. Fusion.
  • the acquisition sensor includes one or more of an acceleration sensor, a gyroscope, a magnetic field sensor, and an audio sensor.
  • the present invention also introduces an audio sensor that analyzes motion characteristics from an audio dimension.
  • the audio sensor is a high-speed, high-precision sensor that provides more precise and detailed motion characteristics than motion sensors.
  • the invention uses an audio sensor to determine the collision time of the collision racquet and the ball, and the sampling speed of up to several tens of KHz ensures that the millisecond-level collision event will not be lost.
  • various features of the collision will be recorded differently, including: the collision position of the ball and the beat, the intensity of the collision, and the characteristics of the racket itself.
  • the data analysis includes: the local data analysis processor included in the acquisition and analysis integration module monitors the data collected by the acquisition sensor, determines the current motion type according to the surface data result, and flexibly sets the sampling speed of the motion sensor according to the severity of the motion.
  • the local data analysis processor will always monitor the data collected by the sensor, and can judge the current motion type according to the surface data result, and flexibly set the sampling speed of the motion sensor according to the severity of the motion to ensure that the power consumption is reduced without losing data, and at the same time Guaranteed sampling accuracy and power control.
  • the original application relies on the simplified migration of algorithms on PCs or other high-speed processors to the embedded system, making integration of acquisition and analysis possible.
  • the acceleration sensor detects that the threshold value b is continuously exceeded, and the angular velocity continuously exceeds the threshold; c, the attitude of the gravity detection or the fusion algorithm exceeds the change threshold d, A predetermined attitude or combination of actions, the system enters a high-speed sampling mode to cope with large dynamic motion analysis and recognition.
  • the data collected from the sensor group includes the original acceleration, angular velocity, and geomagnetic intensity.
  • the multi-axis fusion is combined with the original data to obtain the attitude parameter, the gravity parameter, the gravity-free linear acceleration parameter, and the azimuth of the relative earth.
  • the action type is obtained by the following analysis methods. And characteristics:
  • attitude parameters Through feature comparison and quantification through attitude parameters, gravity parameters, gravity-free linear acceleration parameters, instantaneous values of azimuth angles, and intermediate changes in velocity, displacement, attitude change, motion direction, direction of motion, and trend of change. Discriminate
  • the data result and the important trajectory information output include: obtaining the analysis result through the integrated module data analysis, directly outputting through the display device on the collection and analysis device, and selectively saving the analysis result in the collection analysis and the device.
  • the analysis result is filtered according to predetermined setting conditions, and the sound and light and vibration feedback output are output according to the trigger condition, and the user is promptly reminded of the specific event, and the stored data is selectively sent to the communication module.
  • Upper device According to the needs, you can connect the host device in real time, view the real-time results or display the display, filter the analysis results according to the predetermined setting conditions, and output the sound and light and vibration feedback devices in accordance with the trigger condition, prompting the user to a specific event.
  • the stored data can be selectively sent to a host device through a communication module, such as a mobile phone, a tablet computer, a PC, and a dedicated terminal, for continuing transmission to the cloud server for big data analysis.
  • a communication module such as a mobile phone, a tablet computer, a PC, and a dedicated terminal
  • the communication methods are not limited to: wireless communication modes of various frequency bands such as wifi, Bluetooth, NFC, and proprietary protocols, and wired connections such as USB, USART, 485, and CAN.
  • the upper device includes a mobile phone, a tablet computer, a PC, and a dedicated terminal.
  • the system and method for collecting and analyzing the motion trajectory based on the ball motion of the present invention may have no need to consider the capacity of the data storage and the bandwidth of the transmitted data because the local data analysis processor is used.
  • the gap analyzes the collected data to achieve a complete analysis of the action, solves the limitation of communication bandwidth and storage capacity, maximizes the sampling speed of the sensor, and achieves the maximum sampling accuracy; at the same time, greatly simplifies the system architecture and compresses the system cost. And at the same time improve the user experience.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
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Abstract

L'invention concerne un système de collecte et d'analyse de trajectoires de mouvement basé sur des jeux de balles, comprenant un module d'intégration de collecte et d'analyse de données, un module de communication et un module d'affichage d'interface homme-machine. Le module d'intégration de collecte et d'analyse de données est connecté au module d'affichage d'interface homme-machine par l'intermédiaire du module de communication. Une mémoire non volatile, un capteur de collecte et un processeur d'analyse de données locales sont intégrés dans le module d'intégration de collecte et d'analyse de données. Le capteur de collecte est connecté électriquement au processeur d'analyse de données locales. L'invention concerne également un procédé de collecte et d'analyse de trajectoires de mouvement basé sur des jeux de balle.
PCT/CN2016/080191 2016-04-26 2016-04-26 Système et procédé de collecte et d'analyse de trajectoires de mouvement basés sur des jeux de balles WO2017185222A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201680011563.8A CN107454970A (zh) 2016-04-26 2016-04-26 一种基于球类运动的运动轨迹采集和分析的***与方法
PCT/CN2016/080191 WO2017185222A1 (fr) 2016-04-26 2016-04-26 Système et procédé de collecte et d'analyse de trajectoires de mouvement basés sur des jeux de balles

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CN112929332A (zh) * 2021-01-19 2021-06-08 北京睿芯高通量科技有限公司 一种多轴物体运动检测***及检测方法
CN114796986A (zh) * 2022-06-08 2022-07-29 深圳市汇泰科电子有限公司 一种识别壶铃运动信息的方法

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CN111767932B (zh) * 2019-04-02 2024-02-06 北京深蓝长盛科技有限公司 动作判定方法及装置、计算机设备及计算机可读存储介质
CN110440799A (zh) * 2019-09-19 2019-11-12 哈尔滨工程大学 一种基于陀螺仪和加速度计的姿态角度测量融合***及方法
CN112957688B (zh) * 2021-01-27 2022-02-01 牛鹤璇 一种智能体育运动数据测量方法及设备

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CN114796986B (zh) * 2022-06-08 2024-03-08 深圳市汇泰科电子有限公司 一种识别壶铃运动信息的方法

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