CN111178336A - Local online identification system learned by computer - Google Patents

Local online identification system learned by computer Download PDF

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Publication number
CN111178336A
CN111178336A CN202010147146.4A CN202010147146A CN111178336A CN 111178336 A CN111178336 A CN 111178336A CN 202010147146 A CN202010147146 A CN 202010147146A CN 111178336 A CN111178336 A CN 111178336A
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module
computer
picture
student
pictures
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廖仕东
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Chongqing University of Science and Technology
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Chongqing University of Science and Technology
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20—Movements or behaviour, e.g. gesture recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G06Q50/205—Education administration or guidance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/172—Classification, e.g. identification
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B5/00—Electrically-operated educational appliances
    • G09B5/06—Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
    • G09B5/065—Combinations of audio and video presentations, e.g. videotapes, videodiscs, television systems

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  • General Physics & Mathematics (AREA)
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  • Human Computer Interaction (AREA)
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Abstract

The invention discloses a local online identification system learned by a computer, which comprises a plurality of computer systems, wherein the computer systems are arranged at a teaching end, a student end and a server end, and the teaching end, the student end and the server end are connected through network equipment; the online education system is loaded in the computer system and comprises a background server, a client and a teacher end; the computer system is provided with an image acquisition device, an image recognition system is arranged in a client of the online education system, and the image recognition system comprises a face recognition module and a portrait recognition extraction module. By arranging the system, the learning background of the student can be changed into a uniform background, so that the teacher can conveniently identify the learning background; after the learning state of the student is identified, the learning state is displayed in the display interface of the teacher in the form of the label, so that the teacher can conveniently and timely remind and adjust the teaching content. And the pressure of network transmission is reduced, and the fluency of the system is improved.

Description

Local online identification system learned by computer
Technical Field
The invention relates to the field of computer teaching, in particular to a local online identification system learned by a computer.
Background
The computer is commonly called as computer, is a modern electronic computing machine for high-speed computation, can perform numerical computation and logic computation, and also has the function of storage and memory. The intelligent electronic device can be operated according to a program, and can automatically process mass data at a high speed. A computer that is composed of a hardware system and a software system and does not have any software installed is called a bare metal. The computer can be divided into a super computer, an industrial control computer, a network computer, a personal computer and an embedded computer, and more advanced computers comprise a biological computer, a photon computer, a quantum computer and the like.
With the continuous development of networks, computers are widely applied and become a part of our lives, particularly the rise of the internet of things, and the application and distribution of the computers are greatly improved. Increasingly, the networking of entity content, especially activities that are primarily directed to information transfer, is dependent on network and computer applications.
Education, as a foundation for the strong nation, has a wide range of needs. Traditional education is the face-to-face propagation and learning of knowledge by teachers. Specific scenes are needed, and a great amount of time cost and traffic cost are spent in the process of gathering teachers and students. The network facilities are adopted for teaching, so that a large amount of commuting time can not be saved, and occupation and cost of a learning field are reduced. However, learning is an activity with strong opinion, and when the attention of the student is focused and the student is on-line on time, the learning efficiency and effect are affected.
The online learning can be realized only when the students can not study seriously, teachers can not timely obtain the reaction of the learning states of the students, the learning conditions of the students can not be adjusted in a targeted manner, the teaching efficiency of the whole teaching is reduced, and meanwhile, if videos are adopted to transmit the learning states of the students, a large amount of bandwidth can be occupied. And the background of each student is different, so that the difficulty of teacher identification is greatly increased, and the teaching efficiency and the learning efficiency of online learning are seriously influenced.
Disclosure of Invention
The invention aims to: aiming at the existing problems, the local online identification system for learning by using the computer is provided, and the learning background of the student can be changed into a uniform background through the system, so that the teacher can conveniently identify the background; simultaneously, through setting up local quick identification system, discern the back with student's learning state, show in mr's display interface through the form of label, the mr of being convenient for carries out timely warning and the adjustment of lecture content.
The technical scheme adopted by the invention is as follows:
a local online identification system using computer learning comprises a plurality of computer systems, wherein the computer systems are arranged at a teaching end, a student end and a server end, and the teaching end, the student end and the server end are connected through network equipment; the online education system is loaded in the computer system and comprises a background server, a client and a teacher end; the background server is loaded at the server end, the client end is loaded at the student end, and the teacher end is loaded at the teaching end; the background server, the client and the teacher end are connected through network signals; the computer system is provided with an image acquisition device, an image recognition system is arranged in a client of the online education system, and the image recognition system comprises a face recognition module and a portrait recognition extraction module.
Furthermore, the invention also discloses a preferable mechanism of the local online identification system for learning by using the computer, wherein the client of the online education system comprises an image acquisition module, and the image acquisition module is used for calling an image acquisition device to acquire a video for the student to learn; the client of the online education system comprises a video segmentation module, the image acquisition module transmits acquired videos to the video segmentation module, and the video segmentation module segments videos learned by students into one-frame pictures.
Furthermore, the client of the online education system comprises a picture sampling module, and the video segmentation module sends the segmented pictures to the picture sampling module; the picture sampling module intermittently extracts pictures from the middle of the pictures, and the picture sampling density is 2-10 pieces/second; and the image sampling module sends the acquired image to the image identification and extraction module.
Further, the portrait recognition and extraction module extracts the whole portrait, forms a picture with editable background and sends the picture to the facial recognition module.
Further, the face recognition module comprises a preset module, a personal verification module, a learning state recognition module and a marking module; the presetting module is used for acquiring facial data of students during initial login and forming facial benchmark data.
Further, the principal verification module compares the picture sent by the picture sampling module with the face reference data to determine whether the picture is the principal and sends the result to the marking module; then the learning state identification module identifies the learning state of the student, and then sends the identification result to the marking module, and the marking module adopts colors or special marks to mark whether the student is the student and the learning state on the portrait.
Furthermore, the face recognition module sends the marked pictures to a background server through network connection equipment, a picture synthesizer is arranged in the background server, and the picture synthesizer synthesizes the received multiple student pictures in the same background to form a picture; and sends the picture to the teacher's end.
Further, the teacher end is provided with a framing module, the framing module synthesizes pictures sent by the server into a video stream, a virtual frame is generated between no two pictures, a smooth video is formed, and the video is played through the teacher end.
Further, the computer system comprises a host, wherein the host is connected to the Internet through a network connection device; the host is connected with a microphone and a loudspeaker through a wired or wireless device; the host is connected with a display device for displaying pictures.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. by arranging the system, the learning background of the student can be changed into a uniform background, so that the teacher can conveniently identify the learning background;
2. through setting up local quick identification system, discern the back with student's learning state, show in mr's display interface through the form of label, the mr of being convenient for carries out timely warning and the adjustment of lecture content.
Drawings
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a block diagram of the computer architecture of the present invention;
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1-2, a preferred embodiment of a local online identification system learned by a computer according to the present invention includes a plurality of computer systems, each of the computer systems including a host connected to the internet via a network connection device; the host is connected with a microphone and a loudspeaker through a wired or wireless device; the host is connected with a display device for displaying pictures. The computer system comprises a desktop computer, a notebook computer, a tablet computer, a mobile phone and other personal or server-side computing equipment. The computer system is arranged at a teaching end, a student end and a server end, and the teaching end, the student end and the server end are connected through network equipment.
The online education system is loaded in the computer system and comprises a background server, a client and a teacher end; the background server is loaded at the server end, the client end is loaded at the student end, and the teacher end is loaded at the teaching end; the background server, the client and the teacher end are connected through network signals.
The teaching end and the student end of the computer system are both provided with image acquisition devices, and the image acquisition devices are used for acquiring video images. The client side of the online education system is provided with an image recognition system, and the image recognition system comprises a face recognition module and a portrait recognition and extraction module.
The client of the online education system comprises an image acquisition module, wherein the image acquisition module is used for calling an image acquisition device to acquire a video for students to learn; the client of the online education system comprises a video segmentation module, the image acquisition module transmits acquired videos to the video segmentation module, and the video segmentation module segments videos learned by students into one-frame pictures.
The client of the online education system comprises a picture sampling module, and the video segmentation module sends the segmented pictures to the picture sampling module; the picture sampling module intermittently extracts pictures from the middle of the pictures, and the picture sampling density is 5 pieces/second; and the image sampling module sends the acquired image to the image identification and extraction module.
The portrait recognition and extraction module extracts the whole portrait, forms a picture with editable background and sends the picture to the face recognition module.
The face recognition module comprises a preset module, a personal verification module, a learning state recognition module and a marking module; the presetting module is used for acquiring facial data of students during initial login and forming facial benchmark data.
The identity verification module compares the picture sent by the picture sampling module with the face reference data to determine whether the identity is the identity and sends the result to the marking module; then the learning state identification module identifies the learning state of the student, and then sends the identification result to the marking module, and the marking module adopts colors or special marks to mark whether the student is the student and the learning state on the portrait.
The face recognition module sends the marked pictures to a background server through network connection equipment, a picture synthesizer is arranged in the background server, and the picture synthesizer synthesizes the received multiple student pictures in the same background to form a picture; and sends the picture to the teacher's end.
The teacher end is provided with a framing module which synthesizes the pictures sent by the server into a video stream, and generates a virtual frame between two pictures to form a smooth video which is played by the teacher end.
In the specific operation process, firstly, when logging in, the image acquisition module calls the image acquisition device to acquire facial information of students, and facial reference data are formed through the preset module.
The image acquisition module calls the image acquisition device to acquire videos learned by students, the image acquisition module sends the acquired videos to the video segmentation module, and the video segmentation module segments the videos learned by the students into one-frame and one-frame pictures.
The video segmentation module sends the segmented picture to the picture sampling module; the picture sampling module intermittently extracts pictures from the middle of the pictures, and the picture sampling density is 5 pieces/second; and the image sampling module sends the acquired image to the image identification and extraction module. The portrait recognition and extraction module extracts the whole portrait to form a picture with editable background and sends the picture to the personal verification module of the facial recognition module.
The identity verification module compares the picture sent by the picture sampling module with the face reference data to determine whether the identity is the identity, and sends the result to the marking module; then the learning state identification module identifies the learning state of the student, the learning state can be divided into a plurality of levels, such as conscientious, concentration, distraction, vague and the like, and then the identification result is sent to the marking module. The marking module marks whether the person is the identity and the representation of the learning state on the portrait by adopting colors or special marks.
The face recognition module sends the marked pictures to a background server through network connection equipment, a picture synthesizer is arranged in the background server, and the picture synthesizer synthesizes the received multiple student pictures in the same background to form a picture; and sends the picture to the teacher's end. The teacher end is provided with a framing module which synthesizes the pictures sent by the server into a video stream, and generates a virtual frame between two pictures to form a smooth video which is played by the teacher end.
Therefore, by arranging the system, the learning background of the student can be changed into a uniform background, so that the teacher can conveniently identify the learning background; through setting up local quick identification system, discern the back with student's learning state, show in mr's display interface through the form of label, the mr of being convenient for carries out timely warning and the adjustment of lecture content. And the pressure of network transmission is reduced, and the fluency of the system is improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (9)

1. A local online identification system learned by a computer, comprising: the system comprises a plurality of computer systems, wherein the computer systems are arranged at a teaching end, a student end and a server end, and the teaching end, the student end and the server end are connected through network equipment; the online education system is loaded in the computer system and comprises a background server, a client and a teacher end; the background server is loaded at the server end, the client end is loaded at the student end, and the teacher end is loaded at the teaching end; the background server, the client and the teacher end are connected through network signals; the computer system is provided with an image acquisition device, an image recognition system is arranged in a client of the online education system, and the image recognition system comprises a face recognition module and a portrait recognition extraction module.
2. The local online recognition system learned by a computer according to claim 1, wherein: the client of the online education system comprises an image acquisition module, wherein the image acquisition module is used for calling an image acquisition device to acquire a video for students to learn; the client of the online education system comprises a video segmentation module, the image acquisition module transmits acquired videos to the video segmentation module, and the video segmentation module segments videos learned by students into one-frame pictures.
3. A local online recognition system learned by a computer as set forth in claim 2, wherein: the client of the online education system comprises a picture sampling module, and the video segmentation module sends the segmented pictures to the picture sampling module; the picture sampling module intermittently extracts pictures from the middle of the pictures, and the picture sampling density is 2-10 pieces/second; and the image sampling module sends the acquired image to the image identification and extraction module.
4. A local online recognition system learned by a computer as set forth in claim 3, wherein: the portrait recognition and extraction module extracts the whole portrait, forms a picture with editable background and sends the picture to the face recognition module.
5. The local online recognition system learned by a computer according to claim 4, wherein: the face recognition module comprises a preset module, a personal verification module, a learning state recognition module and a marking module; the presetting module is used for acquiring facial data of students during initial login and forming facial benchmark data.
6. The local online recognition system learned by a computer according to claim 5, wherein: the identity verification module compares the picture sent by the picture sampling module with the face reference data to determine whether the identity is the identity and sends the result to the marking module; then the learning state identification module identifies the learning state of the student, and then sends the identification result to the marking module, and the marking module adopts colors or special marks to mark whether the student is the student and the learning state on the portrait.
7. The local online recognition system learned by a computer according to claim 6, wherein: the face recognition module sends the marked pictures to a background server through network connection equipment, a picture synthesizer is arranged in the background server, and the picture synthesizer synthesizes the received multiple student pictures in the same background to form a picture; and sends the picture to the teacher's end.
8. The local online recognition system learned by a computer according to claim 7, wherein: the teacher end is provided with a framing module which synthesizes the pictures sent by the server into a video stream, and generates a virtual frame between two pictures to form a smooth video which is played by the teacher end.
9. The local online recognition system learned by a computer according to claim 8, wherein: the computer system comprises a host, wherein the host is connected to the Internet through a network connection device; the host is connected with a microphone and a loudspeaker through a wired or wireless device; the host is connected with a display device for displaying pictures.
CN202010147146.4A 2020-03-05 2020-03-05 Local online identification system learned by computer Withdrawn CN111178336A (en)

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CN202010147146.4A CN111178336A (en) 2020-03-05 2020-03-05 Local online identification system learned by computer

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Application Number Priority Date Filing Date Title
CN202010147146.4A CN111178336A (en) 2020-03-05 2020-03-05 Local online identification system learned by computer

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Application publication date: 20200519