Magic cube operation efficiency comparative analysis method used in multi-person confrontation mode

Abstract

The invention relates to the technical field of Rubik's cube operation, in particular to a Rubik's cube operation efficiency comparative analysis method used in a multi-person confrontation mode. The method comprises the following steps that unique identification information is produced according to identity information of all operators, an intelligent magic cube and an image data analysis system are matched, efficiency parameter data are obtained, the efficiency parameter data are transmitted to an efficiency evaluation system, and corresponding efficiency evaluation indexes are generated according to the unique identification information. The efficiency parameter data in the operation process of the intelligent Rubik's cube is obtained by adopting the structure that the intelligent Rubik's cube is matched with the sensor, and the efficiency parameter data is obtained by analyzing the image data obtained by the image data analysis system, so that the accurate efficiency parameter data can be obtained by comparing and verifying the efficiency parameter data of the two, and the efficiency of the intelligent Rubik's cube is improved. Efficiency parameter data acquired only through an intelligent magic cube in the prior art cannot be verified, so that the data cannot be accurate, and errors exist.

Description

Technical Field

[0001] The present invention relates to the field of Rubik's Cube operation technology, and in particular to a Rubik's Cube operation efficiency comparison and analysis method for a multi-player confrontation mode. Background Art

[0002] The Rubik's Cube, a classic three-dimensional puzzle toy, has evolved over decades since its invention in 1974, evolving from a simple recreational tool into a global competitive sport. In the field of Rubik's Cube manipulation competitions, the development of background technology has played a key role in promoting the advancement of competitions and raising the level of competition. In traditional speed-solving competitions, competitors master formulas such as CFOP (Cross, F2L, OLL, and PLL) to achieve the fastest possible time.

[0003] In the prior art, the efficiency of Rubik's Cube operation in multiplayer competition mode is often evaluated by timing. However, Rubik's Cube operation is a mental exercise, and evaluation based solely on operation time is very one-sided. As a result, more and more attention is paid to recording the efficiency of Rubik's Cube operation. The prior art uses smart Rubik's Cubes with internal sensors to record data such as angles, speeds, and steps. However, this method cannot be verified, and the steps for restoring the Rubik's Cube after it is scrambled are different. Therefore, the traditional method of restoring the Rubik's Cube using only smart Rubik's Cubes has certain limitations and cannot accurately record data, resulting in errors.

[0004] Chinese patent publication number CN111939553B discloses a method, system, medium, and device for monitoring, training, and blind-twisting Rubik's Cube operations. The present invention discloses a method, system, medium, and device for monitoring, training, and blind-twisting Rubik's Cube operations. During the monitoring process, the present invention considers the user's perspective, i.e., the user's natural viewing angle, as the principle for performing the Rubik's Cube restoration operation. The Rubik's Cube coordinate system is determined based on body position change information detected by a body position detection sensor. The user's perspective operation is reflected in the changes in the Rubik's Cube coordinate system. The actual operation of the Rubik's Cube in the current coordinate system is determined based on information detected by the body position detection sensors and face rotation detection sensors in the Rubik's Cube, thereby accurately monitoring the operation of the Rubik's Cube. Furthermore, the training method of the present invention avoids the prior art's need to use a large number of inverse algorithms to disrupt the Rubik's Cube to the target algorithm state before algorithm training can begin. This significantly saves the trainee's training time and allows the trainee to quickly form muscle memory through frequent and extensive practice in a short period of time, thereby improving training efficiency.

[0005] The above scheme can avoid the need for a large number of inverse algorithms in the prior art to scramble the Rubik's Cube to the target algorithm state to start the algorithm training, greatly saving the training time of the trainer, allowing the trainer to practice a large number of times in a short time to quickly form muscle memory to improve training efficiency, but it cannot be verified, and the recovery steps after the Rubik's Cube is scrambled are all different, so the traditional method of recovering the Rubik's Cube by the intelligent Rubik's Cube has certain limitations, and cannot accurately obtain data, resulting in errors, and the problems in the above background art cannot be solved.

[0006] Therefore, the present application is proposed. SUMMARY

[0007] The present application aims to provide a Rubik's Cube operation efficiency comparison and analysis method in a multi-player confrontation mode to solve the problem that the traditional method of recovering the Rubik's Cube by the intelligent Rubik's Cube has certain limitations and cannot accurately obtain data, resulting in errors, and the problems in the above background art cannot be solved.

[0008] To achieve the above-mentioned purpose, one of the purposes of the present application is to provide a Rubik's Cube operation efficiency comparison and analysis method in a multi-player confrontation mode, comprising the following steps:

[0009] S1: generating unique identification information for all operator identity information;

[0010] S2: matching the intelligent Rubik's Cube and the image data analysis system through the unique identification information;

[0011] S3: obtaining efficiency parameter data of the operator in the Rubik's Cube operation process through the intelligent Rubik's Cube and the image data analysis system;

[0012] S4: transmitting the efficiency parameter data to the efficiency evaluation system;

[0013] S5: generating corresponding efficiency evaluation indexes through the efficiency evaluation system and the unique identification information.

[0014] As a further improvement of the present technical solution, in the S2, the intelligent Rubik's Cube comprises a hardware layer and an algorithm layer, the hardware layer comprises a Hall sensor, a six-axis sensor and an intelligent central shaft, the hardware layer is electrically connected with the algorithm layer, and the algorithm layer comprises a sensor fusion module, a rotation step recognition module and a speed calculation module.

[0015] The sensor fusion module is used to obtain the data transmitted by the Hall sensor and capture the instantaneous angular velocity IMU data by using the Kalman filtering algorithm.

[0016] The rotation step identification module is used to obtain the data transmitted by the Hall sensor, to judge the effective rotation data according to the detection threshold, and to obtain the rotation direction data according to the time sequence change of the Hall sensor based on the effective rotation data.

[0017] The speed calculation module is used to obtain the instantaneous speed parameter data, the peak speed parameter data and the smoothing filter in the intelligent magic cube operation through the hardware layer.

[0018] As a further improvement of the technical solution, in the S2, the intelligent magic cube and the image data analysis system use the same state coding, the displacement coding is performed on the corner blocks and the edge blocks of the intelligent magic cube, and the intelligent magic cube uses the sensor data collected by the sensor contained in the hardware layer to update the magic cube state to the terminal in real time.

[0019] As a further improvement of the technical solution, the image data analysis system comprises an image acquisition module, an image preprocessing module, a dynamic feature extraction module and a step identification recording module, the image acquisition module is electrically connected with the image preprocessing module, the image preprocessing module is electrically connected with the dynamic feature extraction module and the step identification recording module.

[0020] The image acquisition module is used to obtain the initial state image data of the intelligent magic cube, and to obtain the image data in the operation process of the intelligent magic cube according to the capture threshold, and to transmit the initial state image data of the intelligent magic cube and the image data in the operation process of the intelligent magic cube to the image preprocessing module.

[0021] The image preprocessing module is used to complete the preprocessing of the initial state image data of the intelligent magic cube and the image data in the operation process of the intelligent magic cube.

[0022] The dynamic feature extraction module is used to receive the preprocessed image data in the operation process of the intelligent magic cube, and to obtain the dynamic feature database therein, the dynamic feature data being the angle feature data and the space-time domain feature data calculated by the speed.

[0023] The step identification recording module is used to identify and record the operation process of the operator to the intelligent magic cube.

[0024] As a further improvement of the technical solution, the specific operation process of the image data analysis system is as follows:

[0025] Step one: the image acquisition device electrically connected with the image acquisition module is arranged in a multi-view array mode;

[0026] Step two: the image acquisition module controls the image acquisition device to obtain the initial state image data of the intelligent magic cube and the image data in the operation process of the intelligent magic cube;

[0027] Step three: the image preprocessing module completes the initial state image data of the smart Rubik's Cube and the preprocessing of the image data in the smart Rubik's Cube operation process;

[0028] Step four: the preprocessed image data in the smart Rubik's Cube operation process is dynamically extracted through the dynamic feature extraction module;

[0029] Step five: finally, the step recognition and recording module is used to recognize and record the operation process of the operator on the smart Rubik's Cube.

[0030] As a further improvement of the technical solution, in the S3, the efficiency parameter data of the operator in the Rubik's Cube operation process is obtained through the smart Rubik's Cube and the image data analysis system, and the specific steps are as follows:

[0031] S3.1: obtaining the rotation step parameter data, the smart Rubik's Cube restoration time parameter data and the smart Rubik's Cube operation speed parameter data through the smart Rubik's Cube and the image data analysis system;

[0032] S3.2: comparing the rotation step parameter data, the smart Rubik's Cube restoration time parameter data and the smart Rubik's Cube operation speed parameter data obtained by the smart Rubik's Cube and the image data analysis system;

[0033] S3.3: confirming the rotation step parameter data, the smart Rubik's Cube restoration time parameter data and the smart Rubik's Cube operation speed parameter data of the operator;

[0034] S3.4: transmitting the rotation step parameter data, the smart Rubik's Cube restoration time parameter data and the smart Rubik's Cube operation speed parameter data of the operator to the efficiency evaluation system.

[0035] As a further improvement of the technical solution, in the S4, the efficiency evaluation system includes a step parameter data acquisition module, a standardization processing module, a weight confirmation module and a fusion module;

[0036] The step parameter data acquisition module is used to obtain the standard step parameter data of the smart Rubik's Cube restoration corresponding to the unique identification information;

[0037] The standardization processing module is used to complete the standardization processing of the rotation step parameter data, the smart Rubik's Cube restoration time parameter data and the smart Rubik's Cube operation speed parameter data;

[0038] The weight confirmation module is used to determine the step weight of the unique identification information according to the step parameter data acquisition module, and to determine the time weight and the speed weight;

[0039] The fusion module fuses the step weight, the time weight and the speed weight with the corresponding standardized step parameter data, the intelligent magic cube restoration time parameter data and the intelligent magic cube operation speed parameter data, and simultaneously collects the fused step parameter data, the intelligent magic cube restoration time parameter data and the intelligent magic cube operation speed parameter data to determine the efficiency evaluation index.

[0040] As a further improvement of the technical solution, the step parameter data acquisition module acquires the standard step of the intelligent magic cube as follows:

[0041] (1) color block color recognition is completed;

[0042] (2) an intelligent magic cube reset model is constructed;

[0043] (3) an intelligent magic cube reset step is completed based on machine learning;

[0044] (4) step parameter verification is completed through geometric constraint verification;

[0045] (5) step simplification processing is completed.

[0046] As a further improvement of the technical solution, the standard mode of the rotation step parameter data is to receive the rotation step parameter data of the operator, and the minimum number of steps in the sample is S min , and the maximum number of steps is S max , the fewer the number of steps, the closer the normalized value to 1, and the higher the efficiency, and the standard formula of the rotation step parameter data is:

[0047]

[0048] The standard mode of the intelligent magic cube restoration time parameter data is to receive the intelligent magic cube restoration time parameter data, and the shortest time in the sample is T min , and the longest time is T max , the closer the normalized value to 1, the higher the efficiency, and the standard formula of the intelligent magic cube restoration time parameter data is:

[0049]

[0050] The standard mode of the intelligent magic cube operation speed parameter data is to receive the intelligent magic cube operation speed parameter data, and the minimum average step consumption time in the sample is W min , and the maximum is W max , and the standard formula of the intelligent magic cube operation speed parameter data is:

[0051]

[0052] As a further improvement of the technical solution, the smart magic cube adopts Bluetooth low power transmission, and after the sensor data is processed by the microcontroller, it is transmitted to the terminal through the BLE4.0 protocol, or the smart magic cube is equipped with a built-in flash memory to store rotation data, and the smart magic cube is checked by serial number and state hash value to ensure the integrity of data transmission.

[0053] Compared with the prior art, the present application has the following advantages:

[0054] 1. In the magic cube operation efficiency comparison and analysis method for multi-person confrontation mode, the efficiency parameter data in the operation process of the smart magic cube is obtained by adopting the structure of the smart magic cube and the sensor, and the efficiency parameter data is obtained by analyzing the image data obtained by the image data analysis system. The efficiency parameter data of the two is compared and verified, and accurate efficiency parameter data can be obtained. The efficiency parameter data obtained by the traditional smart magic cube cannot be verified, which leads to inaccurate data and causes errors.

[0055] 2. In the magic cube operation efficiency comparison and analysis method for multi-person confrontation mode, the efficiency parameters of different operators operating the smart magic cube can be obtained objectively in the use process, and the problem of unobjective efficiency parameters caused by different steps of the smart magic cube is avoided. The time efficiency parameter data and step efficiency parameter data are fused with weight to obtain corresponding objective efficiency parameters, so that the efficiency comparison and analysis method of the present application is very fair, and the existence of difference in the competition process is avoided.

[0056] 3. In the magic cube operation efficiency comparison and analysis method for multi-person confrontation mode, the efficiency parameter data can be standardized in the use process, and the efficiency parameter data after standardization is more convenient for decision makers to check. At the same time, the corresponding efficiency evaluation index is generated by unique identification information, which is more helpful for magic cube operation efficiency comparison and analysis in multi-person confrontation mode, and improves the practicality and convenience. DETAILED DESCRIPTION

[0057] Figure 1 The specific steps of the magic cube operation efficiency comparison and analysis method for multi-person confrontation mode of the present application are shown in the figure;

[0058] Figure 2 The specific operation process of the image data analysis system of the present application is shown in the figure;

[0059] Figure 3 The specific steps of the magic cube operation efficiency comparison and analysis method for multi-person confrontation mode of the present application are shown in the figure;

[0060] Figure 4 The step parameter data acquisition module of the application acquires the standard response step diagram of the smart Rubik's Cube;

[0061] Figure 5 The module structure diagram of the smart Rubik's Cube in the application;

[0062] Figure 6 The structure diagram of the image data analysis system in the application;

[0063] Figure 7 The module structure diagram of the efficiency evaluation system in the application. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0065] Embodiment 1

[0066] Please refer to Figures 1-7 The embodiment aims to provide a Rubik's Cube operation efficiency comparative analysis method in a multi-player confrontation mode, which comprises the following steps:

[0067] S1: generating unique identification information for all operator identity information;

[0068] S2: matching the smart Rubik's Cube and the image data analysis system through the unique identification information;

[0069] S3: acquiring the efficiency parameter data of the operator in the Rubik's Cube operation process through the smart Rubik's Cube and the image data analysis system;

[0070] S4: transmitting the efficiency parameter data to the efficiency evaluation system;

[0071] S5: generating corresponding efficiency evaluation indexes through the efficiency evaluation system and the unique identification information.

[0072] In S2, the smart Rubik's Cube comprises a hardware layer and an algorithm layer. The hardware layer comprises a Hall sensor, a six-axis sensor and a smart middle shaft. The hardware layer is electrically connected with the algorithm layer. The algorithm layer comprises a sensor fusion module, a rotation step recognition module and a speed calculation module.

[0073] The sensor fusion module is configured to acquire data transmitted by the Hall sensor, acquire instantaneous angular velocity IMU data by using a Kalman filtering algorithm, acquire instantaneous angular velocity IMU data by using a compensation method for high-frequency noise in rapid rotation, and finally output a smooth angle curve to optimize the instantaneous angular velocity IMU data.

[0074] The rotation step recognition module is configured to acquire data transmitted by the Hall sensor, judge effective rotation data by using a rotation detection threshold, acquire rotation direction data according to the effective rotation data and a time sequence change of the Hall sensor, and judge effective rotation by using a set angular velocity threshold to avoid misrecording of a small adjustment action.

[0075] The speed calculation module is configured to acquire instantaneous speed parameter data, peak speed parameter data and smooth filtering in the intelligent Rubik's Cube operation by using a hardware layer, calculate the instantaneous speed parameter data by using a time difference between adjacent two angle samples, calculate the peak speed parameter data by identifying a maximum speed of a single rotation, analyze a player's force habit according to the peak speed parameter data, and use a sliding average or a low-pass filter to eliminate high-frequency noise to ensure the authenticity of a speed curve.

[0076] The Hall sensor is a linear Hall element, the Hall sensor is installed in an intelligent Rubik's Cube internal rotating shaft area, and the Hall sensor cooperates with a magnet to constitute a rotation angle detection, the Hall sensor is configured to output an electric signal by detecting a magnetic field change when the intelligent Rubik's Cube rotates.

[0077] The six-axis sensor is an inertial measurement component composed of a gyroscope and an accelerometer, and the six-axis sensor is configured to capture a motion trajectory of the intelligent Rubik's Cube in a three-dimensional space in real time.

[0078] The intelligent central shaft is configured to monitor rotation states of two Rubik's Cube layers at the same time.

[0079] In S2, the intelligent Rubik's Cube and the image data analysis system use the same state code, the angle block and the edge block of the intelligent Rubik's Cube are both subjected to displacement coding, and the intelligent Rubik's Cube uses sensor data collected by the sensor contained in the hardware layer to update the Rubik's Cube state to the terminal in real time.

[0080] The image data analysis system includes an image acquisition module, an image preprocessing module, a dynamic feature extraction module and a step recognition recording module, the image acquisition module is electrically connected with the image preprocessing module, the image preprocessing module is electrically connected with the dynamic feature extraction module and the step recognition recording module.

[0081] The image acquisition module is configured to acquire the initial state image data of the smart Rubik's Cube and image data in the operation process of the smart Rubik's Cube according to a capture threshold, and transmit the initial state image data of the smart Rubik's Cube and the image data in the operation process of the smart Rubik's Cube to the image preprocessing module.

[0082] The image preprocessing module is configured to complete preprocessing of the initial state image data of the smart Rubik's Cube and the image data in the operation process of the smart Rubik's Cube.

[0083] The dynamic feature extraction module is configured to receive the preprocessed image data in the operation process of the smart Rubik's Cube, and acquire dynamic feature data in the image data, the dynamic feature data being angle feature data and space-time domain feature data calculated by speed measurement.

[0084] The step recognition and recording module is configured to recognize and record a completed step of an operation process of the smart Rubik's Cube by an operator.

[0085] The preprocessing of the initial state image data of the smart Rubik's Cube and the image data in the operation process of the smart Rubik's Cube specifically includes Gaussian filtering processing of an original image, adaptive threshold binarization, elimination of noise points in a color block through morphological closing operation, color space conversion, elimination of local strong light influence through a Retinex algorithm, estimation of a blur kernel and deconvolution restoration of a rotation frame of ≥200° / second through a Lucas-Kanade optical flow algorithm, and generation of a perspective transformation matrix through recognition of six face corner points of the smart Rubik's Cube to correct a tilted visual angle to an orthographic view.

[0086] The angle feature data is calculated by a pixel-level calculation based on color block displacement, color segmentation of adjacent frames, extraction of profiles of a center block and an edge block of each face, calculation of a relative displacement vector of the center block, calculation of a rotation angle through an atan2 function, and fitting of a three-dimensional model through a least square method by using a geometric constraint of the smart Rubik's Cube.

[0087] The space-time domain feature data calculated by speed measurement is obtained by performing FFT transformation on feature point motion of 10 continuous frames through a frequency domain analysis method, and extracting a dominant frequency component for identifying a periodic rotation mode.

[0088] The step recognition and recording module is configured to recognize and record a completed step of an operation process of the smart Rubik's Cube by an operator, specifically, to realize initial state calibration through the initial state image data of the smart Rubik's Cube, classify a rotation track through a CNN model, identify R / U / F face rotation, and eliminate ambiguity through a geometric constraint.

[0089] In S4, the efficiency evaluation system includes a step parameter data acquisition module, a standardization processing module, a weight confirmation module, and a fusion module.

[0090] The step parameter data acquisition module is configured to acquire the standard step parameter data of the smart Rubik's Cube restoration corresponding to the unique identification information.

[0091] The standardization processing module is configured to complete the standardization processing on the rotation step parameter data, the smart Rubik's Cube restoration time parameter data and the smart Rubik's Cube operation speed parameter data.

[0092] The weight confirmation module is configured to determine the step weight, the time weight and the speed weight of the unique identification information according to the step parameter data acquisition module.

[0093] The fusion module is configured to fuse the step weight, the time weight and the speed weight with the corresponding standardization-processed step parameter data, smart Rubik's Cube restoration time parameter data and smart Rubik's Cube operation speed parameter data, and to determine the efficiency evaluation index by collecting the step parameter data, the smart Rubik's Cube restoration time parameter data and the smart Rubik's Cube operation speed parameter data after the fusion.

[0094] The standardization method of the rotation step parameter data is configured to receive the rotation step parameter data of the operator, and to assume that the minimum number of steps in the sample is S min and the maximum number of steps is S max . The fewer the number of steps, the closer the standardization value is to 1, and the higher the efficiency is. The standardization method of the rotation step parameter data is as follows:

[0095]

[0096] The standardization method of the smart Rubik's Cube restoration time parameter data is configured to receive the smart Rubik's Cube restoration time parameter data, and to assume that the shortest time in the sample is T min and the longest time is T max . The closer the standardization value is to 1, the higher the efficiency is. The standardization method of the smart Rubik's Cube restoration time parameter data is as follows:

[0097]

[0098] The standardization method of the smart Rubik's Cube operation speed parameter data is configured to receive the smart Rubik's Cube operation speed parameter data, and to assume that the minimum average step consumption time in the sample is W min and the maximum is W max . The standardization method of the smart Rubik's Cube operation speed parameter data is as follows:

[0099]

[0100] 10. The method for comparing and analyzing the operation efficiency of Rubik's Cube in a multi-player competitive mode according to claim 1, characterized in that the intelligent Rubik's Cube uses Bluetooth Low Energy transmission, and the sensor data is processed by a microcontroller and then transmitted to a terminal through a BLE4.0 or above protocol, or the intelligent Rubik's Cube has a built-in flash memory to store rotation data, and the intelligent Rubik's Cube uses a serial number check sum and a state hash value to ensure the integrity of data transmission.

[0101] Embodiment 2

[0102] As shown in Figure 2 and Figure 6 , one of the purposes of the present embodiment is to provide a method for comparing and analyzing the operation efficiency of Rubik's Cube in a multi-player competitive mode, which includes an image data analysis system. The specific operation process of the image data analysis system is as follows:

[0103] Step 1: Use a multi-view array to arrange image acquisition devices that are electrically connected to an image acquisition module;

[0104] Step 2: The image acquisition module controls the image acquisition devices to acquire initial state image data of the intelligent Rubik's Cube and image data during the operation process of the intelligent Rubik's Cube;

[0105] Step 3: The image preprocessing module completes the preprocessing of the initial state image data of the intelligent Rubik's Cube and the image data during the operation process of the intelligent Rubik's Cube;

[0106] Step 4: The preprocessed image data during the operation process of the intelligent Rubik's Cube is dynamically extracted by a dynamic feature extraction module;

[0107] Step 5: Finally, the step recognition and recording module is used to recognize and record the operation process of the operator on the intelligent Rubik's Cube.

[0108] In step 1, the number of image acquisition devices is three, and the blind area is eliminated by a space-time synchronization algorithm, which is suitable for multi-angle interference monitoring in a multi-player competitive scene. The frame rate of the image acquisition device is ≥120fps, the resolution parameter of the image acquisition device is 1080P or above, the photosensitive element of the image acquisition device is COMS, the light supplement system of the image acquisition device is a ring-shaped LED, and the lens focal length of the image acquisition device is 8mm-12mm.

[0109] Embodiment 3

[0110] As shown in Figure 3 , Figure 5 and Figure 6 , one of the purposes of the present embodiment is to provide a method for comparing and analyzing the operation efficiency of Rubik's Cube in a multi-player competitive mode. In S3, the specific steps for obtaining the efficiency parameter data of the operator during the operation process of the Rubik's Cube by the intelligent Rubik's Cube and the image data analysis system are as follows:

[0111] S3.1: Obtain the rotation step parameter data, the smart Rubik's Cube restoration time parameter data, and the smart Rubik's Cube operation speed parameter data through the smart Rubik's Cube and the image data analysis system;

[0112] S3.2: Compare the rotation step parameter data, the smart Rubik's Cube restoration time parameter data, and the smart Rubik's Cube operation speed parameter data obtained by the smart Rubik's Cube and the image data analysis system;

[0113] S3.3: Confirm the rotation step parameter data, the smart Rubik's Cube restoration time parameter data, and the smart Rubik's Cube operation speed parameter data of the operator;

[0114] S3.4: Transmit the rotation step parameter data, the smart Rubik's Cube restoration time parameter data, and the smart Rubik's Cube operation speed parameter data of the operator to the efficiency evaluation system.

[0115] In S3.1, the rotation step parameter data is obtained through the smart Rubik's Cube algorithm layer rotation step recognition module and the dynamic feature extraction module.

[0116] In S3.1, the smart Rubik's Cube restoration time parameter data is obtained through the first time that the sensor generates data to the last time that the sensor obtains data in the hardware layer, and through the dynamic feature extraction module.

[0117] In S3.1, the smart Rubik's Cube operation speed parameter data is obtained through the speed calculation module, and through the dynamic feature extraction module.

[0118] Embodiment 4

[0119] Please refer to Figure 4 and Figure 7 , one of the purposes of the present embodiment is to provide a Rubik's Cube operation efficiency comparison and analysis method in a multi-player confrontation mode, which includes a step parameter data acquisition module, and the smart Rubik's Cube standard restoration step diagram obtained by the step parameter data acquisition module is as follows:

[0120] (1): Complete color block color recognition;

[0121] (2): Construct a smart Rubik's Cube reset model;

[0122] (3): Complete the smart Rubik's Cube reset step based on machine learning;

[0123] (4): Complete step parameter verification through geometric constraint verification;

[0124] (5): Complete step simplification processing.

[0125] In (1), first, the RGB pixel value is converted into HSV or LAB space, and the threshold range of the color contained in each color intelligent magic cube is determined by sample training, and finally the pixel mean value of each color block area is taken, and the noise is excluded.

[0126] In (2), the construction of the intelligent magic cube reset model first determines the fixed standard direction of the operable direction of the intelligent magic cube, and then constructs the state matrix.

[0127] In (3), the intelligent magic cube reset step based on machine learning is specifically to train the CNN-LSTM model, and learn the step mode through a large amount of restoration data.

[0128] In (4), the step parameter verification is completed through geometric constraint checking, which is specifically to check whether the step sequence meets the physical rules of the magic cube, and then verify whether the initial state can be restored through the step sequence through simulation rotation.

[0129] In (5), the step simplification processing is specifically to use the post-processing optimization of Kociemba algorithm, merge adjacent reverse rotation, and then convert into the standard speed twist formula.

[0130] The above shows and describes the basic principles, main features and advantages of the present application. It should be understood by those skilled in the art that the present application is not limited by the above examples, and the above examples and descriptions in the specification are only preferred examples of the present application, and are not intended to limit the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A comparative analysis method for Rubik's Cube operation efficiency in a multiplayer competition mode, characterized by: The following steps are involved: S1: Generate unique identification information based on the identity information of all operators; S2: Matching the smart cube and image data analysis system through unique identification information; S3: Obtaining efficiency parameter data of the operator during the Rubik's Cube operation through the intelligent Rubik's Cube and image data analysis system; S4: Transmitting efficiency parameter data to the efficiency evaluation system; S5: Generate corresponding efficiency evaluation indicators using unique identification information through the efficiency evaluation system.

2. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 1, characterized in that: In S2, the smart Rubik's Cube includes a hardware layer and an algorithm layer, the hardware layer includes a Hall sensor, a six-axis sensor and an intelligent central axis, the hardware layer is electrically connected to the algorithm layer, and the algorithm layer includes a sensor fusion module, a rotation step recognition module and a speed calculation module; The function of the sensor fusion module is to obtain the data transmitted by the Hall sensor and capture the instantaneous angular velocity IMU data by adopting the Kalman filter algorithm. The function of the rotation step identification module is to obtain the data transmitted by the Hall sensor, determine the effective rotation data based on the rotation detection threshold, and obtain the rotation direction data based on the effective rotation data and the timing change of the Hall sensor. The function of the speed calculation module is to obtain instantaneous speed parameter data, peak speed parameter data and smoothing filtering in the intelligent Rubik's Cube operation through the hardware layer.

3. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 1, characterized in that: In S2, the smart Rubik's Cube and the image data analysis system both use the same state encoding, and displacement encoding is performed on the corner blocks and edge blocks of the smart Rubik's Cube. At the same time, the smart Rubik's Cube uses the sensor data collected by the sensors contained in the hardware layer to update the Rubik's Cube state to the terminal in real time.

4. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 2, characterized in that: The image data analysis system includes an image acquisition module, an image preprocessing module, a dynamic feature extraction module and a step identification and recording module, wherein the image acquisition module is electrically connected to the image preprocessing module, and the image preprocessing module is electrically connected to the dynamic feature extraction module and the step identification and recording module; The image acquisition module is used to acquire the image data of the initial state of the intelligent Rubik's Cube and the image data of the intelligent Rubik's Cube during operation according to the capture threshold, and transmit the image data of the initial state of the intelligent Rubik's Cube and the image data of the intelligent Rubik's Cube during operation to the image preprocessing module; The image preprocessing module is used to preprocess the image data of the initial state of the intelligent Rubik's Cube and the image data during the operation of the intelligent Rubik's Cube; The function of the dynamic feature extraction module is to receive the pre-processed image data during the intelligent Rubik's Cube operation and obtain the dynamic feature database therein, wherein the dynamic feature data is the angle feature data and the spatiotemporal feature data of the speed measurement; The function of the step identification and recording module is to identify and record the steps completed by the operator in the intelligent Rubik's Cube operation process.

5. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 4, characterized in that: The specific operation process of the image data analysis system is as follows: Step 1: Arrange an image acquisition device electrically connected to the image acquisition module in a multi-view array manner; Step 2: The image acquisition module controls the image acquisition device to acquire image data of the initial state of the intelligent Rubik's Cube and image data during the operation of the intelligent Rubik's Cube; Step 3: The image preprocessing module completes the preprocessing of the image data of the initial state of the intelligent Rubik's Cube and the image data during the operation of the intelligent Rubik's Cube; Step 4: Dynamically extract the pre-processed image data during the intelligent Rubik's Cube operation through the dynamic feature extraction module; Step 5: Finally, the step recognition and recording module completes the step recognition and recording of the operator's operation process of the smart Rubik's Cube.

6. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 1, characterized in that: In S3, the specific steps of obtaining the efficiency parameter data of the operator during the operation of the Rubik's Cube through the intelligent Rubik's Cube and the image data analysis system are as follows: S3.1: Obtain rotation step parameter data, smart cube restoration time parameter data, and smart cube operation speed parameter data through the smart cube and image data analysis system; S3.2: Compare the rotation step parameter data, the intelligent Rubik's Cube restoration time parameter data, and the intelligent Rubik's Cube operation speed parameter data obtained from the intelligent Rubik's Cube and the image data analysis system; S3.3: Confirm the operator's rotation step parameter data, intelligent Rubik's Cube recovery time parameter data, and intelligent Rubik's Cube operation speed parameter data; S3.4: Transmit the operator's rotation step parameter data, the intelligent Rubik's Cube restoration time parameter data, and the intelligent Rubik's Cube operation speed parameter data to the efficiency evaluation system.

7. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 1, characterized in that: In said S4, said efficiency evaluation system includes a step parameter data acquisition module, a standardization processing module, a weight confirmation module and a fusion module; The step parameter data acquisition module is used to obtain the standard step parameter data of the intelligent Rubik's Cube restoration corresponding to the unique identification information; The function of the standardization processing module is to perform standardization processing on the rotation step parameter data, the intelligent Rubik's Cube restoration time parameter data, and the intelligent Rubik's Cube operation speed parameter data; The weight confirmation module is used to determine the step weight of the unique identification information according to the step parameter data acquisition module, as well as the time weight and speed weight; The function of the fusion module is to fuse the step weight, time weight and speed weight with the corresponding standardized step parameter data, intelligent Rubik's Cube restoration time parameter data, and intelligent Rubik's Cube operation speed parameter data, and at the same time, the weighted step parameter data, intelligent Rubik's Cube restoration time parameter data, and intelligent Rubik's Cube operation speed parameter data are combined to determine the efficiency evaluation index.

8. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 7, characterized in that: The parameter data acquisition module obtains the standard answer of the smart cube as follows: (1): Complete color block recognition; (2): Construct an intelligent Rubik's Cube reset model; (3): Complete the smart Rubik's Cube reset steps based on machine learning; (4): Complete step parameter verification through geometric constraint verification; (5): Complete the step streamlining process.

9. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 7, characterized in that: The standard method of the rotation step parameter data is to receive the operator's rotation step parameter data and assume that the minimum number of steps is S min , the maximum number of steps is S max , the fewer the steps, the closer the normalized value is to 1, and the higher the efficiency. The standard formula of the rotation step parameter data is: The standard method of the intelligent Rubik's Cube restoration time parameter data is to receive the intelligent Rubik's Cube restoration time parameter data, and set the shortest time in the sample as T min , the maximum time is T max The closer the normalized value is to 1, the higher the efficiency. The standard formula of the intelligent Rubik's Cube restoration time parameter data is: The standard method of the intelligent Rubik's Cube operation speed parameter data is to receive the intelligent Rubik's Cube operation speed parameter data, and set the minimum average step time in the sample to be W min , the maximum is W max The standard formula of the intelligent Rubik's Cube operation speed parameter data is:

10. The method for comparing and analyzing Rubik's Cube operation efficiency in a multiplayer competition mode according to claim 1, characterized in that: The smart Rubik's Cube uses Bluetooth low energy transmission. After the sensor data is processed by the microcontroller, it is transmitted to the terminal through BLE4.0 or above protocols, or the smart Rubik's Cube uses built-in flash memory to store rotation data. The smart Rubik's Cube uses serial number checksum and status hash value to ensure the integrity of data transmission.

Images