Multi-dimensional direct broadcasting glasses for sports events

Abstract

The invention provides sports event multi-dimensional direct broadcasting glasses which comprise a glasses frame, the glasses frame is made of a light high-strength carbon fiber material, glasses legs are designed to be adjustable in length, and a space for installing all modules is formed in the glasses frame. The glasses frame is internally provided with the following modules: a data acquisition and processing module, a data processing module and a display module, the data analysis module is used for carrying out deep analysis on the competition data, the competition watching habits and the preferences; the display module is used for providing competition data pictures; the ambient light module is used for adjusting the brightness of the display module; the audio module is used for collecting a voice instruction of a user; the interaction control module is used for identifying and executing a voice instruction of a user; the connection and synchronization module is used for synchronizing information with the intelligent equipment; and the battery management module is used for providing power support for each module. According to the invention, more personalized sports event broadcast experience is provided for the user, and valuable event prediction and tactical analysis information are provided.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent devices, and particularly to a multi-dimensional direct broadcast glasses for sports events. Background Art

[0002] With the increasing richness of sports events and the continuous improvement of people's requirements for the viewing experience, traditional viewing methods, such as watching live events through devices like TVs and mobile phones, can no longer meet people's needs for an all-round and immersive viewing experience. Traditional devices can only provide single video and audio information, and viewers cannot obtain more real-time data and multi-dimensional information related to the event, and the interactivity and interest of viewing are relatively low.

[0003] Currently, intelligent glasses technology has been applied in some fields. However, in the scenario of watching sports events, most existing intelligent glasses focus on entertainment functions such as taking pictures and recording videos, and the function development for sports event broadcasting and information presentation is not perfect enough. There is a lack of a device that can provide comprehensive sports event information for viewers in real time and accurately, and is convenient for viewers to freely obtain and operate during the game. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a multi-dimensional direct broadcast glasses for sports events to solve or at least partially solve the above problems existing in the prior art.

[0005] To achieve the above purpose, the present invention provides a multi-dimensional direct broadcast glasses for sports events, including a frame. The frame is made of lightweight and high-strength carbon fiber material. The temple is designed with adjustable length. There is a space inside the frame for installing each module. The following modules are respectively arranged inside the frame:

[0006] Data acquisition and processing module: used to collect and obtain event data from multiple sports platforms and perform data processing on the event data;

[0007] Data analysis module: used to deeply analyze the event data and analyze the viewing habits and preferences of users;

[0008] Display module: used to provide event data pictures, adopting high-resolution holographic projection display technology to present a three-dimensional event picture in front of the user;

[0009] Ambient light module: used to sense the intensity of the surrounding ambient light, so as to adjust the brightness of the display module according to the change of the ambient light intensity;

[0010] Audio module: used to collect the voice commands of users and provide the sound effects of event data for users;

[0011] Interaction control module: used to identify and execute user voice commands;

[0012] Connection and synchronization module: used to support the synchronization of event data and intelligent devices, as well as provide data storage, software update and maintenance services;

[0013] Battery management module: used to provide power support for each module.

[0014] Furthermore, the data processing of the event data specifically includes the following steps:

[0015] S11. Perform preprocessing operations on the collected event data, and the preprocessing operations include format conversion and normalization processing of the event data;

[0016] S12. Based on the preprocessed event data, calculate the total delay of the duration of the collected event data, which is expressed as follows:

[0017]

[0018]

[0019] where, T 总 is the total delay of the duration of the event data, N is the total number of sports platforms, n is the event data collected by the nth sports platform, t 总 is the total duration of the collected event data, T′ 总 is the total delay of the duration of the normalized event data, t max is the assumed maximum total delay of the duration;

[0020] S13. Calculate the resource utilization rate of the data collection and processing module when collecting event data, which is expressed as follows:

[0021]

[0022] where, R n is the resource utilization rate of obtaining the event data of the nth sports platform, c n is the total amount of resources for obtaining the event data of the nth sports platform, is the remaining amount of resources for obtaining the event data of the nth sports platform, and R is the total resource utilization rate of the data collection and processing module;

[0023] S14. Based on steps S12 - S13, combine and optimize the total delay of the duration of the event data and the total resource utilization rate, which is expressed as follows:

[0024] K = μT′ 总 +(1 - μ)(1 - R)

[0025] Among them, K is the optimization result of the total delay and resource utilization of the event data duration, and μ is the weighting coefficient.

[0026] Furthermore, the in-depth analysis of the event data specifically includes the following steps:

[0027] S21. Segment the event data collected and analyze the performance of the teams in past games;

[0028] S22. Analyze the action characteristics of the athletes in the segmented event data, which are expressed as follows:

[0029]

[0030] Among them, M j is the feature vector of the action of athlete j, T is the event data divided into θ segments, t is the event data of the t-th segment, and is the score vector of the action of athlete j in the event data of the t-th segment;

[0031] S23. Combine and analyze the action characteristics of the athletes in each segment of the event data to form a tactical analysis report;

[0032] S24. Combine the performance of the teams in past games with the tactical analysis report to predict the outcome of this game.

[0033] Furthermore, the analysis of the viewing habits and preferences of users specifically includes the following steps:

[0034] S31. Count the types of games watched by the user and calculate the probability of the types of games watched, which is expressed as follows:

[0035]

[0036] Among them, P(u x ) is the probability that user u watches this type of game for the x-th time, u x is the user's x-th viewing of this type of game, and θ u is the tendency parameter of the user to watch this type of game;

[0037] S32. According to the probability of the types of games watched by the user, find similar users and predict the user's preferences for unwatched games based on the similar users, which is expressed as follows:

[0038]

[0039] Among them, R is the preference score for predicting the user's unwatched games, V is the set of users similar to the user, sim(u, c) is the similarity between user u and similar user c, and r cy is the preference value of similar user c for game type y;

[0040] S33. Provide personalized event broadcast content according to the prediction results of the user's preferences for unviewed games.

[0041] Furthermore, the ambient light module uses a high-sensitivity photodiode as the photosensitive element.

[0042] Furthermore, the recognition and execution of the user's voice commands specifically include the following steps:

[0043] S41. Establish a voice command database and input the user's voiceprint characteristics.

[0044] S42. Recognize the voice commands collected by the audio module and determine whether the voiceprint characteristics of the collected voice commands are consistent with the user's voiceprint characteristics.

[0045] S43. Based on step S42, perform preprocessing operations on the voice commands that are consistent with the user's voiceprint characteristics.

[0046] S44. Perform deepening processing on the voice commands after the preprocessing operations, which is expressed as follows:

[0047] m[z] = n[z] - αn[z - 1]

[0048] where m[z] is the function expression of the voice command deepening processing, n[z] is the sampling point, and α is the deepening processing coefficient.

[0049] S45. Compare and match the voice commands after the deepening processing with the voice command database, and execute the relevant command operations for the voice commands that are successfully compared and matched.

[0050] Furthermore, the connection and synchronization module is paired and connected with nearby smart devices through the Bluetooth communication function. After the pairing and connection are successful, the communication between the glasses and the smart devices is encrypted through an encryption algorithm.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] Through the data acquisition and processing module, the present invention reduces the latency of obtaining event data and provides instant data processing. Through the data analysis module, a tactical analysis report is generated for the user to facilitate the user's further understanding of the game. And through the prediction of the user's viewing habits and preferences, personalized event broadcast content is accurately provided for the user. Through the interactive control module, the user's voice commands can be accurately recognized to facilitate the user's relevant operations. Brief Description of the Drawings

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only the preferred embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0054] Figure 1 It is a schematic structural diagram of a system for a multi-dimensional direct broadcast glasses for sports events provided by an embodiment of the present invention. Detailed implementation manners

[0055] The principles and features of the present invention will be described below in conjunction with the accompanying drawings. The listed embodiments are only used to explain the present invention and are not used to limit the scope of the present invention.

[0056] As Figure 1 shown, the present invention provides a schematic structural diagram of a system for a multi-dimensional direct broadcast glasses for sports events.

[0057] This embodiment provides a multi-dimensional direct broadcast glasses for sports events, including a frame. The frame is made of a lightweight and high-strength carbon fiber material. The temple is designed with an adjustable length. A space for installing each module is provided inside the frame. The following modules are respectively provided inside the frame:

[0058] Data acquisition and processing module: used to collect and obtain event data from multiple sports platforms and perform data processing on the event data. Specifically, it includes:

[0059] The data acquisition obtains event data from multiple sports platforms through a wireless / 5G transmission method.

[0060] The data processing on the event data specifically includes the following steps:

[0061] S11. Perform preprocessing operations on the collected event data. The preprocessing operations include format conversion and normalization processing of the event data;

[0062] S12. Based on the preprocessed event data, calculate the total delay of the collected event data duration, expressed as follows:

[0063]

[0064] Among them, T 总 is the total delay of the event data duration, N is the total number of sports platforms, n is the event data collected from the nth sports platform, t 总 is the total duration of the collected event data, T′ 总 is the total delay of the normalized event data duration, t maxis the assumed maximum total latency of the duration;

[0065] S13. Calculate the resource utilization rate of the data acquisition and processing module when acquiring event data, which is expressed as follows:

[0066]

[0067] where R n is the resource utilization rate for acquiring event data from the nth sports platform, and c n is the total amount of resources for acquiring event data from the nth sports platform, is the remaining amount of resources for acquiring event data from the nth sports platform, and R is the total resource utilization rate of the data acquisition and processing module;

[0068] S14. Based on steps S12 - S13, combine and optimize the total latency and total resource utilization rate of the event data duration, which is expressed as follows:

[0069] K = μT′ 总 +(1 - μ)(1 - R)

[0070] where K is the optimization result of the total latency and resource utilization rate of the event data duration, and μ is the weighting coefficient.

[0071] Data analysis module: Used to perform in - depth analysis on event data and analyze the viewing habits and preferences of users, specifically including:

[0072] The data analysis module provides personalized event broadcast content according to the viewing habits and preferences of users.

[0073] The in - depth analysis of the event data specifically includes the following steps:

[0074] S21. Segment the acquired event data and analyze the performance of the teams in past games;

[0075] S22. Analyze the action characteristics of the athletes in the segmented event data, which is expressed as follows:

[0076]

[0077] where M j is the feature vector of the action of athlete j, T is the event data divided into T segments, t is the event data of the t - th segment, is the score vector of the action of athlete j in the event data of the t - th segment;

[0078] S23. Combine and analyze the action characteristics of the athletes in each segment of the event data to form a tactical analysis report;

[0079] S24. Combine the performance of the team in past games with the tactical analysis report to predict the outcome of this game, specifically including:

[0080] Predict the outcome of the team's game in this game from multiple dimensions. Assume the following parameters for the team:

[0081] Weight of recent winning rate (X1): The value range is 0 - 1, representing the importance of the recent winning rate in the prediction;

[0082] Weight of recent average goals per game (X2): The value range is 0 - 1, representing the importance of the recent average number of goals per game in the prediction;

[0083] Weight of recent average goals conceded per game (X3): The value range is 0 - 1, representing the importance of the recent average number of goals conceded per game in the prediction;

[0084] Weight of winning rate in confrontations with the opponent team (X4): The value range is 0 - 1, representing the importance of the past winning rate in confrontations with the opponent team in the prediction;

[0085] Recent winning rate (W1): The proportion of the number of winning games in the past X games;

[0086] Recent average goals per game (Y1): The average number of goals per game in the past X games;

[0087] Recent average goals conceded per game (Y2): The average number of goals conceded per game in the past X games;

[0088] Winning rate in confrontations with the opponent team (W2): The proportion of the number of winning games in past confrontations with the opponent;

[0089] Express the above parameters as follows:

[0090] D = X1W1 + X2Y1 + X3Y2 + X4W2.

[0091] Analyze the user's viewing habits and preferences, specifically including the following steps:

[0092] S31. Statistically analyze the types of games watched by the user and calculate the probability of the types of games watched, expressed as follows:

[0093]

[0094]

[0095] Among them, P(u x ) is the probability that user u watches this type of game for the xth time, u x is the xth time user u watches this type of game, a u is the logarithmic distribution of the types of games watched by the user, It is the logarithmic distribution of the tendency parameter for the user to watch this type of game, θ u It is the tendency parameter for the user to watch this type of game, θ u The value may change over time, that is, the types of games watched by the user at different times are inconsistent. For example, the user watched the most type A games last month, and this month it changed to watching type B games. It can be adjusted according to the types of different games watched by the user at different times.

[0096] S32. According to the probability of the game types watched by the user, find similar users, and predict the user's preference for unwatched games based on the similar users, which is expressed as follows:

[0097]

[0098] Among them, R is the preference score for the user to predict unwatched games, V is the set of users similar to the user, sim(u, c) is the similarity between user u and similar user c, and r cy is the preference value of similar user c for game type y;

[0099] S33. According to the prediction result of the user's preference for unwatched games, provide personalized event broadcast content for the user.

[0100] Display module: It is used to provide event data pictures, and adopts high-resolution holographic projection display technology to present a three-dimensional event picture in front of the user. Specifically, it includes:

[0101] The display module supports wide color gamut display, with bright colors and high contrast, and can provide a 3D visual effect, making the user feel as if they are on the stadium.

[0102] Ambient light module: It is used to sense the intensity of the surrounding ambient light, and thus adjust the brightness of the display module according to the change of the ambient light intensity. Specifically, it includes:

[0103] The ambient light module uses a high-sensitivity photodiode as a photosensitive element, and can automatically adjust the brightness of the display module according to the change of the ambient light, ensuring that the user can obtain a clear and comfortable viewing experience under different light conditions.

[0104] Audio module: It is used to collect the user's voice commands and provide the sound effects of event data for the user. Specifically, it includes:

[0105] The audio module includes a stereo speaker and a microphone. The stereo speaker uses a high-quality audio driver chip and can provide clear and full sound effects; the microphone is used to collect the user's voice commands to realize the function of voice interaction.

[0106] Interaction control module: used to identify and execute user voice commands, specifically including the following steps:

[0107] S41. Establish a voice command database and input the user's voice characteristics;

[0108] S42. Identify the voice commands collected by the audio module and determine whether the voice characteristics of the collected voice commands are consistent with the user's voice characteristics;

[0109] S43. Based on step S42, perform preprocessing operations on the voice commands that are consistent with the user's voice characteristics;

[0110] S44. Perform deepening processing on the voice commands after the preprocessing operations, expressed as follows:

[0111] m[z] = n[z] - an[z - 1]

[0112] where m[z] is the function expression of the voice command deepening processing, n[z] is the sampling point, and α is the coefficient of the deepening processing;

[0113] Perform deepening processing on the voice commands after the preprocessing operations, making the voice and enunciation of the voice commands clearer, so that it is easier to compare and match with the voice command database.

[0114] S45. Compare and match the deepened voice commands with the voice command database, and execute the relevant command operations for the successfully compared and matched voice commands.

[0115] Connection and synchronization module: used to support the synchronization of event data and intelligent devices, and provide data storage, software update and maintenance services, specifically including:

[0116] The connection and synchronization module is paired and connected with nearby intelligent devices through the Bluetooth communication function. After the pairing connection is successful, the communication between the glasses and the intelligent devices is encrypted through an encryption algorithm to ensure the security of data transmission.

[0117] Battery management module: used to provide power support for each module, specifically including:

[0118] The battery management module uses a lithium polymer battery with high energy density and is electrically connected to the data acquisition and processing module, data analysis module, display module, ambient light module, audio module, interaction control module, and connection and synchronization module respectively to provide long-term power support for each module.

[0119] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A multi-dimensional direct broadcast glasses for sports events, characterized in that, It includes a frame. The frame is made of lightweight and high-strength carbon fiber material. The temple is designed with adjustable length. There is a space inside the frame for installing various modules. The following modules are respectively arranged inside the frame: Data acquisition and processing module: It is used to collect event data from multiple sports platforms and perform data processing on the event data; Data analysis module: It is used to deeply analyze the event data and analyze the user's viewing habits and preferences; Display module: It is used to provide event data pictures. Adopting high-resolution holographic projection display technology, it presents a three-dimensional event picture in front of the user; Ambient light module: It is used to sense the intensity of the surrounding ambient light, so as to adjust the brightness of the display module according to the change of the ambient light intensity; Audio module: It is used to collect the user's voice commands and provide the sound effects of event data for the user; Interaction control module: It is used to identify and execute the user's voice commands; Connection and synchronization module: It is used to support the synchronization of event data with smart devices, and provide data storage, software update and maintenance services; Battery management module: It is used to provide power support for each module.

2. The multi-dimensional direct broadcast glasses for sports events according to claim 1, characterized in that, The data processing of the event data specifically includes the following steps: S11. Perform preprocessing operations on the collected event data. The preprocessing operations include format conversion and normalization processing of the event data; S12. Based on the preprocessed event data, calculate the total delay of the collected event data duration, expressed as follows: Among them, T 总 is the total delay of the event data duration, N is the total number of sports platforms, n is the event data collected by the nth sports platform, and t 总 is the total duration of collecting event data, T′ 总 is the total delay of the event data duration after normalization processing, and t max is the assumed maximum total delay of the duration; S13. Calculate the resource utilization rate of the data acquisition and processing module when collecting event data, expressed as follows: Among them, R n is the resource utilization rate for obtaining the event data of the nth sports platform, and c n is the total amount of resources for obtaining the event data of the nth sports platform. is the remaining amount of resources for obtaining the event data of the nth sports platform, and R is the total resource utilization rate of the data collection and processing module; S14. Based on steps S12 - S13, combine and optimize the total delay and total resource utilization rate of the event data duration, expressed as follows: K = μT' 总 +(1 - μ)(1 - R) Where, K is the optimization result of the total delay and resource utilization rate of the event data duration, and μ is the weighting coefficient.

3. The multi-dimensional direct broadcast glasses for sports events according to claim 1, characterized in that, The in-depth analysis of the event data specifically includes the following steps: S21. Segment the collected event data and analyze the performance of the team in past games; S22. Analyze the action characteristics of the athletes in the segmented event data, expressed as follows: Among them, M j is the feature vector of the action of athlete j, T is the division of the event data into T segments, and t is the event data of the t-th segment. is the score vector of the action of athlete j in the event data of the t-th segment; S23. Combine and analyze the action characteristics of the athletes in each segment of the event data to form a tactical analysis report; S24. Combine the performance of the team in past games with the tactical analysis report to predict the outcome of this game.

4. A multi-dimensional direct broadcast glasses for sports events according to claim 1, characterized in that, The analysis of the user's viewing habits and preferences specifically includes the following steps: S31. Count the types of games watched by the user and calculate the probability of the types of games watched, expressed as follows: Among them, P(u x ) is the probability that user u watches this type of game for the x-th time, u x is the x-th time that the user watches this type of game, and θ u is the tendency parameter for the user to watch this type of game; S32. According to the probability of the types of games watched by the user, find similar users and predict the user's preferences for unwatched games based on the similar users, expressed as follows: Wherein, R is the predicted preference score of the user for the unviewed game, V is the set of users similar to the user, sim(u, c) is the similarity between user u and similar user c, and r cy is the preference value of the similar user c for the game type y; S33. According to the prediction result of the user's preferences for unwatched games, provide personalized event broadcast content for the user.

5. A multi-dimensional direct broadcast glasses for sports events according to claim 1, characterized in that, The ambient light module uses a highly sensitive photodiode as the photosensitive element.

6. The multi-dimensional direct broadcast glasses for sports events according to claim 1, characterized in that, The identification and execution of the user's voice commands specifically includes the following steps: S41. Establish a voice command database and input the user's voiceprint characteristics; S42. Recognize the voice command collected by the audio module, and determine whether the timbre feature of the collected voice command is consistent with the user's timbre feature; S43. Based on step S42, perform a preprocessing operation on the voice command that is consistent with the user's timbre feature; S44. Deepen the processed voice command, which is expressed as follows: m[z] = n[z] - αn[z - 1] where m[z] is the function expression for deepening the voice command, n[z] is the sampling point, and α is the coefficient for deepening the processing; S45. Compare and match the deepened voice command with the voice command database, and execute the relevant command operations for the voice command with a successful comparison and match.

7. A multi-dimensional direct broadcast glasses for sports events according to claim 1, characterized in that, The connection and synchronization module is paired and connected with a nearby intelligent device through the Bluetooth communication function. After the pairing and connection are successful, the communication between the glasses and the intelligent device is encrypted through an encryption algorithm.

Images