CN108924651B - Teaching video intelligent playing system based on training operation recognition - Google Patents
Teaching video intelligent playing system based on training operation recognition Download PDFInfo
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- CN108924651B CN108924651B CN201810690962.2A CN201810690962A CN108924651B CN 108924651 B CN108924651 B CN 108924651B CN 201810690962 A CN201810690962 A CN 201810690962A CN 108924651 B CN108924651 B CN 108924651B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44204—Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44213—Monitoring of end-user related data
- H04N21/44218—Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV program
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44213—Monitoring of end-user related data
- H04N21/44222—Analytics of user selections, e.g. selection of programs or purchase activity
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- General Health & Medical Sciences (AREA)
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- Electrically Operated Instructional Devices (AREA)
Abstract
The invention relates to a teaching video intelligent playing system based on training operation recognition, which consists of five modules. The acquisition module is used for acquiring content information of the teaching video and the time length for watching the teaching video by the user; the identification module is used for identifying the training operation of the user, comparing the training operation of the user with the content information of the teaching video and judging whether the training operation of the user is wrong or not; the teaching module is used for acquiring the specific steps of the user training operation errors and analyzing and displaying the current errors according to the error display mode selected by the user; the analysis module is used for obtaining the user watching concentration degree of the current teaching video according to the duration of the user watching the teaching video, and storing the teaching video and the user watching concentration degree corresponding to the video in a one-to-one correspondence manner; the feedback module uploads the teaching video type and the related information of the corresponding watching concentration degree of the user to a preset server.
Description
Technical Field
The invention particularly relates to a teaching video intelligent playing system based on training operation recognition.
Background
With the rapid development of artificial intelligence theory and technology, various intelligent software layers are developed to solve more complex problems. In order to solve various complicated problems, people need to be more qualified in social work, and people often need to master and use various tool software in solving the complicated and delicate life or work problems. In a new software for people to learn, some people are more used to watch some blog articles, microblog articles, dog searching and asking questions and know articles. There is also a large segment of the population used to learn some tool software by watching video. However, in watching videos, such a trouble or a trouble often occurs, which requires people to look over videos, sometimes the problem that people need to look over videos a lot of times or try a new operation means cannot be solved, but many times, in the process of learning software, the problems that people encounter cannot be solved through the above means, people can learn forward through various social software, and thus the time is very time-consuming. When these problems cannot be solved, people are forced to abandon learning the software, progress space is reduced or environmental development is not adapted. In order to solve the problem, in learning software, the ancestors who already master the software carry out synchronous guidance nearby. In order to solve the problem, video playing software becomes more intelligent and is provided with a social function, and voice interaction or character communication is carried out between people in the live broadcasting process. The method well shortens the time of learning new software for people and improves the learning efficiency. Such as cloud class, mu class, bar, micro blog, beep li and so on. When a user encounters difficulty in learning tool software, the software is required to upload a video recorded with an error or describe voice transmission containing the details of the error by voice or describe text transmission containing the details of the error and then transmit the video to another ancestor which guides the software to learn, wherein the ancestor analyzes the error by naked eyes, analyzes the brain to obtain the reason of the error and then transmits the video or the voice or the text to the software by the software, and the software is fed back to a beginner. When the software of the type is used for processing the problem, the problem is processed in a time-sharing mode, time is consumed for the software, and real-time interaction and immediate feedback cannot be achieved in a true sense. Meanwhile, each piece of information is propagated secondarily, and message loss or artificial receiving failure of part of messages occurs in human description messages, outgoing messages, receiving messages and analyzing messages, so that the time for people to learn the tool software is prolonged, and the efficiency for people to learn the tool software is reduced. The existing learning software does not have the functions of judging the learning software mastery degree of a person through identifying interface operation of the person, analyzing tool software operated by a user, recording a client operation instruction, analyzing the tool software mastered by the client, reminding the user in real time and reminding the user of modifying an error instruction.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide an intelligent teaching video playing system based on training operation recognition to solve the technical defects, aiming at the defects of the existing learning software.
Teaching video intelligence play system based on training operation discernment includes following five modules:
an acquisition module: the system comprises a video acquisition module, a video display module and a video display module, wherein the video acquisition module is used for acquiring content information of a teaching video and the time length of watching the teaching video by a user;
an identification module: the system is used for identifying the training operation of the user on the application software, comparing the training operation of the user with the content information of the teaching video, judging whether the training operation of the user is wrong or not, if so, prompting the user of the operation error and prompting the user to select an error display mode for modification, and if not, not prompting;
a teaching module: the method comprises the specific steps of obtaining user training operation errors, and analyzing and displaying current errors according to an error display mode selected by a user;
an analysis module: the system comprises a video acquisition module, a video storage module, a video processing module and a display module, wherein the video acquisition module is used for acquiring the user watching concentration degree of the current teaching video according to the time length of the user watching the teaching video, and storing the teaching video and the user watching concentration degree corresponding to the video in a one-to-one correspondence manner;
a feedback module: and the system is used for uploading the teaching video and the related information of the watching concentration degree of the corresponding user to a preset server.
Further, the specific method for comparing the training operation of the user with the content information of the teaching video by the identification module is to extract instruction data of the training operation of the user on the application software, compare and analyze the instruction data of the training operation of the user with the operation instruction data in the content information of the teaching video, if the comparison deviation exceeds a preset difference value, prompt the current user that the operation is wrong, and if the comparison deviation does not exceed the preset difference value, do not prompt.
Further, the error display mode comprises the steps of playing a video slow motion by the teaching module, generating and correcting by the teaching module, generating a teaching and actual operation effect comparison diagram by the teaching module and generating a text description by the teaching module.
Further, the specific method for obtaining the watching concentration degree of the user by the analysis module is as follows: the method comprises the steps that in the process of obtaining the duration of watching a teaching video by a user, an obtaining module identifies the watching time of the user for opening the teaching video and recording the staying on a video playing interface, identifies all times of cutting out the video playing interface by the user in the process and records the total cutting out time, and an analyzing module obtains the net watching time ratio of the user for watching the current teaching video according to the watching time and the cutting out time, so that the watching concentration degree of the user is obtained.
Furthermore, the preset server can sort and filter the teaching videos according to the watching of the user.
Further, the user concentration degree is divided into five indexes: very attentive, more attentive, general, less attentive, and very inattentive.
The invention has the beneficial effects that: firstly, other software needing to be loaded is extremely few, and the frequency of loading social software is reduced; secondly, the teaching video intelligent playing system based on training operation recognition is developed only through software programming like common learning software, and meanwhile, playing source video playing and online searching for software needed by a user can be carried out, wherein the intelligent online playing learning software can monitor user interface operation to obtain relevant videos which are spontaneously searched for by the invisible requirements of the user and provide the videos for the user; thirdly, the teaching video intelligent playing system based on the training operation recognition has the function of recognizing the training operation steps, can recognize the training operation of the user by means of the existing interface operation recognition technology, meanwhile, adopts the existing cloud computing algorithm to calculate and collect the state of watching each video by the client, compares the recognized training operation with the operation steps in the reference video, and immediately reminds the user and corrects if errors are found.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a teaching video intelligent playing system based on training operation recognition according to the present invention.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The invention aims to solve the technical problem of providing a teaching video intelligent playing system based on training operation recognition, wherein the system structure diagram is shown in figure 1 and comprises the following five modules:
an acquisition module: the system comprises a video acquisition module, a video display module and a video display module, wherein the video acquisition module is used for acquiring content information of a teaching video and the time length of watching the teaching video by a user;
an identification module: the system is used for identifying the training operation of the user on the application software, comparing the training operation of the user with the content information of the teaching video, judging whether the training operation of the user is wrong or not, if so, prompting the user of the operation error and prompting the user to select an error display mode for modification, and if not, not prompting;
a teaching module: the method comprises the specific steps of obtaining user training operation errors, and analyzing and displaying current errors according to an error display mode selected by a user;
an analysis module: the system comprises a video acquisition module, a video storage module, a video processing module and a display module, wherein the video acquisition module is used for acquiring the user watching concentration degree of the current teaching video according to the time length of the user watching the teaching video, and storing the teaching video and the user watching concentration degree corresponding to the video in a one-to-one correspondence manner;
a feedback module: and the system is used for uploading the teaching video and the related information of the watching concentration degree of the corresponding user to a preset server.
The teaching video intelligent playing system based on training operation recognition specifically comprises the following steps:
step S1, opening the teaching video intelligent playing system based on training operation identification, and starting the system to be in a work preparation stage;
step S2, when the user opens the software teaching video with different playing sources, the obtaining module obtains the content information of the teaching video currently playing, and identifies and obtains the training operation of the current user on the computer;
step S3, the identification module compares and analyzes the instruction data of the user training operation with the operation instruction data in the content information of the acquired teaching video, if the comparison deviation exceeds a preset difference value, the identification module prompts the current user that the operation is wrong, and if the comparison deviation does not exceed the preset difference value, the identification module does not prompt;
step S4, when the user receives the reminding notice of the identification module, the user can choose to play with video slow motion, display the correction step, generate the comparison graph of the teaching and actual operation effect or carry out the description of the text;
step S5, in the process of obtaining the duration of watching the teaching video by the user, the obtaining module identifies that the user opens the teaching video and records the watching time staying in the video playing interface, identifies all times of cutting out the video playing interface by the user in the process and records the total cutting out time, and the analyzing module obtains the watching concentration degree of the user watching the current teaching video according to the watching time and the cutting out time;
and S6, uploading the watching concentration degree of the teaching video and the user corresponding to the video to a preset server by a feedback module, and sequencing, screening and the like the teaching video in the preset server according to the concentration degree.
The user concentration degree is divided into five indexes: the intelligent teaching video playing system is characterized in that the intelligent teaching video playing system is very concentrated, more concentrated, general, less concentrated and very less concentrated, the user watches the concentration degree index as shown in the table I, the result is obtained through statistical analysis of the user watching concentration degree based on the teaching video intelligent playing system recognized by training operation, the result is fed back to a merchant, and the merchant can carry out customized editing work on the video in the server according to the user watching concentration degree index.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (4)
1. Teaching video intelligence play system based on training operation discernment, its characterized in that includes following five modules:
an acquisition module: the system comprises a video acquisition module, a video display module and a video display module, wherein the video acquisition module is used for acquiring content information of a teaching video and the time length of watching the teaching video by a user;
an identification module: the teaching video processing device is used for identifying the training operation of a user on application software, extracting instruction data of the training operation of the user on the application software, comparing and analyzing the instruction data of the training operation of the user and the operation instruction data in the acquired content information of the teaching video, prompting the user of an operation error and selecting an error display mode for modification if the comparison deviation exceeds a preset difference, and not prompting if the comparison deviation does not exceed the preset difference;
a teaching module: the method comprises the specific steps of obtaining user training operation errors, and analyzing and displaying current errors according to an error display mode selected by a user;
an analysis module: the system comprises a video acquisition module, a video storage module, a video processing module and a display module, wherein the video acquisition module is used for acquiring the user watching concentration degree of the current teaching video according to the time length of the user watching the teaching video, and storing the teaching video and the user watching concentration degree corresponding to the video in a one-to-one correspondence manner; the specific method for obtaining the watching concentration degree of the user by the analysis module is as follows: the method comprises the steps that in the process of obtaining the duration of watching a teaching video by a user, an obtaining module identifies the watching time of the user for opening the teaching video and recording the staying on a video playing interface, identifies all times of cutting out the video playing interface by the user in the process and records the total cutting out time, and an analyzing module obtains the net watching time ratio of the user for watching the current teaching video according to the watching time and the cutting out time so as to obtain the watching concentration degree of the user;
a feedback module: and the system is used for uploading the teaching video and the related information of the watching concentration degree of the corresponding user to a preset server.
2. The intelligent teaching video playing system based on training operation recognition as claimed in claim 1, wherein the error display mode includes that the teaching module performs video slow motion playing, the teaching module generates correction steps, the teaching module generates teaching and practice effect comparison diagrams, and the teaching module generates text description.
3. The teaching video intelligent playing system based on training operation recognition as claimed in claim 1, wherein the preset server performs sorting and screening work on teaching videos according to user watching.
4. The teaching video intelligent playing system based on training operation recognition of claim 1, wherein the user concentration degree is divided into five indexes: very attentive, more attentive, general, less attentive, and very inattentive.
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Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110248235B (en) * | 2019-06-26 | 2022-06-17 | 深圳市轱辘车联数据技术有限公司 | Software teaching method, device, terminal equipment and medium |
| CN110830475A (en) * | 2019-11-11 | 2020-02-21 | *** | Video challenge APP |
| CN110990649A (en) * | 2019-12-05 | 2020-04-10 | 福州市第二医院（福建省福州中西医结合医院、福州市职业病医院） | Cardiopulmonary resuscitation interactive training system based on gesture recognition technology |
| CN112801052B (en) * | 2021-04-01 | 2021-08-31 | 北京百家视联科技有限公司 | User concentration degree detection method and user concentration degree detection system |
| CN115394153A (en) * | 2021-05-25 | 2022-11-25 | 上海博泰悦臻网络技术服务有限公司 | Teaching method and device, electronic equipment and computer readable storage medium |
| CN117037558B (en) * | 2023-08-11 | 2024-05-14 | 武汉蓝海科创技术有限公司 | Interactive learning training assessment system for maintenance process of large-scale complex equipment |
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