Online learning quality evaluation method and system

Abstract

The present invention provides an online learning quality assessment method and system, which photographs the student's face to obtain a corresponding facial image, and then determines the student's eye opening and closing state and eye sight direction state based on the facial image, so as to determine the student's concentration state during online learning. The quantitative evaluation results on the student's learning concentration state can be directly obtained from the facial image obtained through a series of image processing calculations, thereby reliably and quantitatively judging the quality state of the student's online learning and facilitating improving the efficiency and quality of online learning.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent education, and in particular to an online learning quality assessment method and system. Background Art

[0002] At present, online learning is achieved by students watching corresponding courses on the screen of the device terminal and interacting with teachers, which can facilitate students to study courses anytime and anywhere in different occasions, thereby improving the convenience and flexibility of students' course learning. However, since the entire process of online learning is achieved by students facing the screen, students cannot always maintain a state of concentration and are prone to distraction during the entire process, which will affect the efficiency and quality of students' online learning. The existing technology cannot effectively and accurately determine which state of students belongs to the state of concentration or distraction, which cannot reliably and quantitatively determine the quality of students' online learning, which is not conducive to improving the efficiency and quality of online learning. Summary of the invention

[0003] In view of the defects of the prior art, the present invention provides an online learning quality assessment method and system, which obtains a facial image of the student by photographing the student, and determines the eye coordinate information of the student based on the facial image, and determines the eye opening and closing state information of the student and the eye viewing screen direction information based on the eye coordinate information, and then determines the concentration state of the student in the current online learning process based on the eye opening and closing state information and the eye viewing screen direction information; it can be seen that the online learning quality assessment method and system obtains a corresponding facial image by photographing the student's face, and then determines the eye opening and closing state and the eye viewing direction state of the student based on the facial image, so as to determine the concentration state of the student in the online learning process, and can directly obtain the quantitative evaluation result of the student's learning concentration state from the facial image obtained through a series of image processing calculations, thereby reliably and quantitatively judging the quality state of the student's online learning and improving the efficiency and quality of online learning.

[0004] The present invention provides an online learning quality assessment method, which is characterized by comprising the following steps:

[0005] Step S1, photographing a student to obtain a facial image of the student, and determining eye coordinate information of the student based on the facial image;

[0006] Step S2, determining the eye opening and closing state information and the screen viewing direction information of the student according to the eye coordinate information;

[0007] Step S3, determining the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing direction information;

[0008] Furthermore, in step S1, photographing the student to obtain the student's facial image, and determining the student's eye coordinate information based on the facial image specifically includes:

[0009] Step S101, adjusting the shooting angle of view and / or shooting focal length of the student so that the facial area of ​​the student is imaged in the central area of ​​the current shooting field of view, thereby obtaining the facial image of the student;

[0010] Step S102, performing background noise reduction filtering, pixel sharpening and pixel binarization processing on the facial image in sequence, so as to obtain a pre-processed facial image;

[0011] Step S103, acquiring the preprocessed facial image, and determining eye coordinate information of the two eyes of the student;

[0012] Further, in step S2, determining the eye opening and closing state information and the eye viewing screen sight direction information of the student according to the eye coordinate information specifically includes:

[0013] Step S201, determining the average eye opening and closing amplitude ER of the student according to the eye coordinate information and the following formula (1):

[0014]

[0015] In the above formula (1), represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the ear. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the bridge of the nose. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student;

[0016] Step S202, determining the angle α between the student's eye viewing line of sight of the screen and a straight line perpendicular to the surface where the screen is located, based on the eye coordinate information and the following formula (2):

[0017]

[0018] In the above formula (2), represents the coordinate value of the center point of the eyeball of the i-th eye of the student in the facial image, (X, Y) represents the preset origin coordinate value, L represents the shooting depth of field corresponding to the shooting, f represents the shooting focal length corresponding to the shooting, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student;

[0019] Further, in step S3, determining the concentration state of the student during the current online learning process according to the eye opening and closing state information and the eye viewing screen sight direction information specifically includes:

[0020] Step S301, determining the student's current online learning concentration evaluation value F according to the eye opening and closing state information, the eye viewing screen sight direction information and the following formula (3):

[0021]

[0022] In the above formula (3), ER represents the average value of the eye opening and closing amplitude of the student during the shooting process, α represents the angle between the student's eye line of sight to the screen and the straight line perpendicular to the surface on which the screen is located, and ER max Indicates the maximum opening and closing amplitude of the student's eyes;

[0023] Step S302, comparing the online learning concentration evaluation value F with a preset concentration threshold, if the online learning concentration evaluation value F is greater than or equal to the preset concentration threshold, it is determined that the student is currently in a state of learning concentration, otherwise, it is determined that the student is not currently in a state of learning concentration.

[0024] The present invention also provides an online learning quality assessment system, characterized in that it includes an image capture and processing module, an eye coordinate information determination module, an eye state determination module and a learning concentration state determination module; wherein,

[0025] The image capturing and processing module is used to capture the student to obtain the student's facial image and pre-process the facial image;

[0026] The eye coordinate information determination module is used to determine the eye coordinate information of the student according to the preprocessed facial image;

[0027] The eye state determination module is used to determine the eye opening and closing state information and the eye viewing screen direction information of the student according to the eye coordinate information;

[0028] The learning concentration state determination module is used to determine the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing direction information;

[0029] Furthermore, the image capturing and processing module captures the student to obtain the student's facial image, and preprocesses the facial image, specifically including:

[0030] Adjusting the shooting angle of view and / or shooting focal length of the student so that the facial area of ​​the student is imaged in the central area of ​​the current shooting field of view, thereby obtaining the facial image of the student;

[0031] Then, the facial image is subjected to background noise reduction filtering, pixel sharpening and pixel binarization processing in sequence, so as to obtain a pre-processed facial image;

[0032] as well as,

[0033] The eye coordinate information determination module determines the eye coordinate information of the student according to the preprocessed facial image, specifically including:

[0034] Determining eye coordinate information of two eyes of the student according to the preprocessed facial image;

[0035] Further, the eye state determination module determines the eye opening and closing state information and the eye viewing screen sight direction information of the student according to the eye coordinate information, specifically including:

[0036] According to the eye coordinate information and the following formula (1), the average value ER of the student's eye opening and closing amplitude is determined:

[0037]

[0038] In the above formula (1), represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the ear. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the bridge of the nose. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student;

[0039] as well as,

[0040] According to the eye coordinate information and the following formula (2), the angle α between the student's eye viewing the screen and the straight line perpendicular to the surface where the screen is located is determined:

[0041]

[0042] In the above formula (2), represents the coordinate value of the center point of the eyeball of the i-th eye of the student in the facial image, (X, Y) represents the preset origin coordinate value, L represents the shooting depth of field corresponding to the shooting, f represents the shooting focal length corresponding to the shooting, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student;

[0043] Furthermore, the learning concentration state determination module determines the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing screen sight direction information, specifically including:

[0044] According to the eye opening and closing state information, the eye viewing direction information and the following formula (3), the student's current online learning concentration evaluation value F is determined:

[0045]

[0046] In the above formula (3), ER represents the average value of the eye opening and closing amplitude of the student during the shooting process, α represents the angle between the student's eye line of sight to the screen and the straight line perpendicular to the surface on which the screen is located, and ERmax Indicates the maximum opening and closing amplitude of the student's eyes;

[0047] The online learning concentration evaluation value F is then compared with a preset concentration threshold. If the online learning concentration evaluation value F is greater than or equal to the preset concentration threshold, it is determined that the student is currently in a state of learning concentration; otherwise, it is determined that the student is not currently in a state of learning concentration.

[0048] Compared with the prior art, the online learning quality assessment method and system obtains the student's facial image by photographing the student, and determines the student's eye coordinate information based on the facial image, and determines the student's eye opening and closing state information and the eye's line of sight direction information when viewing the screen based on the eye coordinate information, and then determines the student's concentration state in the current online learning process based on the eye opening and closing state information and the eye's line of sight direction information when viewing the screen; it can be seen that the online learning quality assessment method and system obtains the student's facial image by photographing the student's face, and then determines the student's eye opening and closing state and the eye's line of sight direction state based on the facial image, so as to determine the student's concentration state in the online learning process, and can directly obtain the quantitative evaluation results of the student's learning concentration state from the photographed facial image and after a series of image processing calculations, thereby reliably and quantitatively judging the quality state of the student's online learning and improving the efficiency and quality of online learning.

[0049] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0050] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 This is a flow chart of the online learning quality evaluation method provided by the present invention.

[0053] Figure 2 This is a schematic diagram of the structure of the online learning quality evaluation system provided by the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] See also Figure 1 , is a flow chart of an online learning quality evaluation method provided by an embodiment of the present invention. The online learning quality evaluation method comprises the following steps:

[0056] Step S1, photographing a student to obtain a facial image of the student, and determining eye coordinate information of the student based on the facial image;

[0057] Step S2, determining the eye opening and closing state information and the screen viewing direction information of the student according to the eye coordinate information;

[0058] Step S3, determining the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing direction information of the eye.

[0059] The beneficial effects of the above technical solution are as follows: the online learning quality assessment method obtains the corresponding facial image by photographing the student's face, and then determines the student's eye opening and closing state and the eye sight direction state based on the facial image, so as to determine the student's concentration state during the online learning process. The quantitative evaluation results of the student's learning concentration state can be directly obtained from the facial image obtained by photographing and after a series of image processing calculations, thereby reliably and quantitatively judging the quality status of the student's online learning and improving the efficiency and quality of online learning.

[0060] Preferably, in step S1, photographing the student to obtain the student's facial image, and determining the student's eye coordinate information based on the facial image specifically includes:

[0061] Step S101, adjusting the shooting angle of view and / or shooting focal length of the student so that the facial area of ​​the student is imaged in the central area of ​​the current shooting field of view, thereby obtaining the facial image of the student;

[0062] Step S102, performing background noise reduction filtering processing, pixel sharpening processing and pixel binarization processing on the facial image in sequence, so as to obtain a pre-processed facial image;

[0063] Step S103, acquiring the preprocessed facial image, and determining eye coordinate information of the two eyes of the student.

[0064] The beneficial effects of the above technical solution are: by adjusting the shooting angle and / or shooting focal length, it can ensure that the student's facial area can be completely imaged in the corresponding shooting field of view, thereby avoiding incomplete shooting and shooting distortion; in addition, performing background noise reduction filtering, pixel sharpening and pixel binarization processing on the facial image in sequence can effectively reduce the noise component in the image and improve the resolution of the image pixels, thereby ensuring the calculation accuracy and reliability of the eye coordinate information.

[0065] Preferably, in step S2, determining the eye opening and closing state information and the eye viewing screen sight direction information of the student according to the eye coordinate information specifically includes:

[0066] Step S201, according to the eye coordinate information and the following formula (1), determine the average value ER of the student's eye opening and closing amplitude:

[0067]

[0068] In the above formula (1), represents the coordinate value of the corner of the eye of the i-th eye of the student near the ear in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour of the i-th eye of the student in the facial image and the upper eyelid, represents the coordinate value of the intersection point between the tangent line of the eyeball contour of the i-th eye of the student in the facial image and the upper eyelid, represents the coordinate value of the corner of the eye of the i-th eye of the student near the bridge of the nose in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour of the i-th eye of the student in the facial image and the lower eyelid, represents the coordinate value of the intersection point between the tangent line of the eyeball contour part with the shortest distance to the bridge of the nose and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image. When i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student;

[0069] Step S202, according to the eye coordinate information and the following formula (2), determine the angle α between the student's eye viewing line of sight of the screen and a straight line perpendicular to the surface where the screen is located:

[0070]

[0071] In the above formula (2), represents the coordinate value of the center point of the eyeball of the i-th eye of the student in the facial image, (X, Y) represents the preset origin coordinate value, L represents the shooting depth of field corresponding to the shooting, f represents the shooting focal length corresponding to the shooting, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student.

[0072] The beneficial effect of the above technical solution is: the average value of the student's eye opening and closing amplitude and the angle between the student's eye line of sight when viewing the screen and a straight line perpendicular to the surface on which the screen is located are calculated respectively by the above formulas (1) and (2), so as to maximize the reflection of the real-time state of the student's eye viewing during online learning, thereby providing accurate and reliable data support for the subsequent determination of the student's learning concentration state, wherein the average value of the eye opening and closing amplitude can be obtained by randomly selecting a plurality of eye part images, and for each eye part image, calculating the area size of the area enclosed by the upper eyelid and the lower eyelid in the eye part image, and the area size is the eye opening and closing amplitude value corresponding to the eye part image, and the eye opening and closing amplitude values ​​corresponding to the plurality of randomly selected eye part images are averaged to obtain the corresponding average value of the eye opening and closing amplitude.

[0073] Preferably, in step S3, determining the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing screen sight direction information specifically includes:

[0074] Step S301, according to the eye opening and closing state information, the eye viewing direction information and the following formula (3), determine the student's current online learning concentration evaluation value F:

[0075]

[0076] In the above formula (3), ER represents the average value of the student's eye opening and closing amplitude during this shooting process, α represents the angle between the student's eye line of sight to the screen and the straight line perpendicular to the surface on which the screen is located, and ER max Indicates the maximum opening and closing amplitude of the student's eyes;

[0077] Step S302, comparing the online learning concentration evaluation value F with a preset concentration threshold, if the online learning concentration evaluation value F is greater than or equal to the preset concentration threshold, it is determined that the student is currently in a state of learning concentration, otherwise, it is determined that the student is not currently in a state of learning concentration.

[0078] The beneficial effect of the above technical solution is: the student's current online learning concentration evaluation value is calculated by the above formula (3), which can objectively and comprehensively convert the real-time state of the student's eye viewing during the online learning process into a quantitative form of online learning concentration evaluation value, thereby reliably and quantitatively judging the quality status of the student's online learning and helping to improve the efficiency and quality of online learning.

[0079] See also Figure 2 , is a schematic diagram of the structure of an online learning quality evaluation system provided by an embodiment of the present invention. The online learning quality evaluation system includes an image capture and processing module, an eye coordinate information determination module, an eye state determination module, and a learning concentration state determination module; wherein,

[0080] The image capturing and processing module is used to capture the student to obtain the student's facial image and pre-process the facial image;

[0081] The eye coordinate information determination module is used to determine the eye coordinate information of the student according to the preprocessed facial image;

[0082] The eye state determination module is used to determine the eye opening and closing state information and the eye viewing screen direction information of the student according to the eye coordinate information;

[0083] The learning concentration state determination module is used to determine the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing direction information of the eye viewing the screen.

[0084] The beneficial effects of the above technical solution are: the online learning quality assessment system obtains the corresponding facial image by photographing the student's face, and then determines the student's eye opening and closing state and the eye gaze direction state based on the facial image, so as to determine the student's concentration state during the online learning process. The quantitative evaluation results of the student's learning concentration state can be directly obtained from the facial image obtained by shooting and after a series of image processing calculations, thereby reliably and quantitatively judging the quality status of the student's online learning and improving the efficiency and quality of online learning.

[0085] Preferably, the image capturing and processing module captures the student to obtain the student's facial image, and preprocesses the facial image, specifically including:

[0086] Adjusting the shooting angle of view and / or shooting focal length of the student so that the facial area of ​​the student is imaged in the central area of ​​the current shooting field of view, thereby obtaining the facial image of the student;

[0087] Then, the facial image is subjected to background noise reduction filtering, pixel sharpening and pixel binarization processing in sequence, so as to obtain a pre-processed facial image;

[0088] as well as,

[0089] The eye coordinate information determination module determines the eye coordinate information of the student according to the preprocessed facial image, specifically including:

[0090] According to the preprocessed facial image, eye coordinate information of the two eyes of the student is determined.

[0091] The beneficial effects of the above technical solution are: by adjusting the shooting angle and / or shooting focal length, it can ensure that the student's facial area can be completely imaged in the corresponding shooting field of view, thereby avoiding incomplete shooting and shooting distortion; in addition, performing background noise reduction filtering, pixel sharpening and pixel binarization processing on the facial image in sequence can effectively reduce the noise component in the image and improve the resolution of the image pixels, thereby ensuring the calculation accuracy and reliability of the eye coordinate information.

[0092] Preferably, the eye state determination module determines the eye opening and closing state information and the screen viewing direction information of the student according to the eye coordinate information, specifically including:

[0093] According to the eye coordinate information and the following formula (1), the average value ER of the student's eye opening and closing amplitude is determined:

[0094]

[0095] In the above formula (1), represents the coordinate value of the corner of the eye of the i-th eye of the student near the ear in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour of the i-th eye of the student in the facial image and the upper eyelid, represents the coordinate value of the intersection point between the tangent line of the eyeball contour of the i-th eye of the student in the facial image and the upper eyelid, represents the coordinate value of the corner of the eye of the i-th eye of the student near the bridge of the nose in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour of the i-th eye of the student in the facial image and the lower eyelid, represents the coordinate value of the intersection point between the tangent line of the eyeball contour part with the shortest distance to the bridge of the nose and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image. When i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student;

[0096] as well as,

[0097] According to the eye coordinate information and the following formula (2), the angle α between the student's eye viewing the screen and the straight line perpendicular to the surface where the screen is located is determined:

[0098]

[0099] In the above formula (2), represents the coordinate value of the center point of the eyeball of the i-th eye of the student in the facial image, (X, Y) represents the preset origin coordinate value, L represents the shooting depth of field corresponding to the shooting, f represents the shooting focal length corresponding to the shooting, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student.

[0100] The beneficial effect of the above technical solution is: the average value of the student's eye opening and closing amplitude and the angle between the student's eye line of sight when viewing the screen and a straight line perpendicular to the surface on which the screen is located are calculated respectively by the above formulas (1) and (2), so as to maximize the reflection of the real-time state of the student's eye viewing during online learning, thereby providing accurate and reliable data support for the subsequent determination of the student's learning concentration state, wherein the average value of the eye opening and closing amplitude can be obtained by randomly selecting a plurality of eye part images, and for each eye part image, calculating the area size of the area enclosed by the upper eyelid and the lower eyelid in the eye part image, and the area size is the eye opening and closing amplitude value corresponding to the eye part image, and the eye opening and closing amplitude values ​​corresponding to the plurality of randomly selected eye part images are averaged to obtain the corresponding average value of the eye opening and closing amplitude.

[0101] Preferably, the learning concentration state determination module determines the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing screen sight direction information, specifically including:

[0102] According to the eye opening and closing state information, the eye viewing direction information and the following formula (3), the student's current online learning concentration evaluation value F is determined:

[0103]

[0104] In the above formula (3), ER represents the average value of the student's eye opening and closing amplitude during this shooting process, α represents the angle between the student's eye line of sight to the screen and the straight line perpendicular to the surface on which the screen is located, and ER max Indicates the maximum opening and closing amplitude of the student's eyes;

[0105] The online learning concentration evaluation value F is then compared with a preset concentration threshold. If the online learning concentration evaluation value F is greater than or equal to the preset concentration threshold, it is determined that the student is currently in a state of learning concentration; otherwise, it is determined that the student is not currently in a state of learning concentration.

[0106] The beneficial effect of the above technical solution is: the student's current online learning concentration evaluation value is calculated by the above formula (3), which can objectively and comprehensively convert the real-time state of the student's eye viewing during the online learning process into a quantitative form of online learning concentration evaluation value, thereby reliably and quantitatively judging the quality status of the student's online learning and helping to improve the efficiency and quality of online learning. From the contents of the above embodiments, it can be seen that the online learning quality assessment method and system obtains the student's facial image by photographing the student, and determines the student's eye coordinate information based on the facial image, and determines the student's eye opening and closing state information and the eye viewing screen line of sight direction information based on the eye coordinate information, and then determines the student's concentration state in the current online learning process based on the eye opening and closing state information and the eye viewing screen line of sight direction information; it can be seen that the online learning quality assessment method and system obtains the student's face by photographing the corresponding facial image, and then determines the student's eye opening and closing state and the eye line of sight direction state based on the facial image, so as to determine the student's concentration state in the online learning process, and it can directly obtain the quantitative evaluation results of the student's learning concentration state from the facial image obtained through a series of image processing calculations, thereby reliably and quantitatively judging the quality state of the student's online learning and improving the efficiency and quality of online learning.

[0107] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. Online learning quality assessment methods, It is characterized in that It includes the following steps: Step S1, photographing a student to obtain a facial image of the student, and determining eye coordinate information of the student based on the facial image; Step S2, determining the eye opening and closing state information and the screen viewing direction information of the student according to the eye coordinate information; Step S3, determining the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing direction information; Wherein, in the step S2, determining the eye opening and closing state information and the eye viewing screen sight direction information of the student according to the eye coordinate information specifically includes: Step S201, determining the average eye opening and closing amplitude ER of the student according to the eye coordinate information and the following formula (1): In the above formula (1), represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the ear. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the bridge of the nose. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student; Step S202, determining the angle α between the student's eye viewing line of sight of the screen and a straight line perpendicular to the surface where the screen is located, based on the eye coordinate information and the following formula (2): In the above formula (2), represents the coordinate value of the center point of the eyeball of the i-th eye of the student in the facial image, (X, Y) represents the preset origin coordinate value, L represents the shooting depth of field corresponding to the shooting, f represents the shooting focal length corresponding to the shooting, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student.

2. The online learning quality evaluation method according to claim 1, Features: In the step S1, photographing the student to obtain the student's facial image, and determining the student's eye coordinate information according to the facial image specifically includes: Step S101, adjusting the shooting angle of view and / or shooting focal length of the student so that the facial area of ​​the student is imaged in the central area of ​​the current shooting field of view, thereby obtaining the facial image of the student; Step S102, performing background noise reduction filtering, pixel sharpening and pixel binarization processing on the facial image in sequence, so as to obtain a pre-processed facial image; Step S103, acquiring the preprocessed facial image, and determining eye coordinate information of the two eyes of the student.

3. The online learning quality evaluation method according to claim 1, Features: In step S3, determining the concentration state of the student during the current online learning process according to the eye opening and closing state information and the eye viewing screen sight direction information specifically includes: Step S301, determining the student's current online learning concentration evaluation value F according to the eye opening and closing state information, the eye viewing screen sight direction information and the following formula (3): In the above formula (3), ER represents the average value of the eye opening and closing amplitude of the student during the shooting process, α represents the angle between the student's eye line of sight to the screen and the straight line perpendicular to the surface on which the screen is located, and ER max Indicates the maximum opening and closing amplitude of the student's eyes; Step S302, comparing the online learning concentration evaluation value F with a preset concentration threshold, if the online learning concentration evaluation value F is greater than or equal to the preset concentration threshold, it is determined that the student is currently in a state of learning concentration, otherwise, it is determined that the student is not currently in a state of learning concentration.

4. Online learning quality evaluation system, It is characterized in that It includes an image capture and processing module, an eye coordinate information determination module, an eye state determination module and a learning concentration state determination module; wherein, The image capturing and processing module is used to capture the student to obtain the student's facial image and pre-process the facial image; The eye coordinate information determination module is used to determine the eye coordinate information of the student according to the preprocessed facial image; The eye state determination module is used to determine the eye opening and closing state information and the eye viewing screen direction information of the student according to the eye coordinate information; The learning concentration state determination module is used to determine the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing direction information; The eye state determination module determines the eye opening and closing state information and the screen viewing direction information of the student according to the eye coordinate information, specifically including: determining the average eye opening and closing amplitude ER of the student according to the eye coordinate information and the following formula (1): In the above formula (1), represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the ear. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the upper eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the corner of the eye of the i-th eye of the student in the facial image, which is close to the bridge of the nose. represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the ear and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, represents the coordinate value of the intersection point between the tangent line of the eyeball contour portion with the shortest distance to the bridge of the nose and the lower eyelid on the eyeball contour of the i-th eye of the student in the facial image, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student; and, According to the eye coordinate information and the following formula (2), the angle α between the student's eye viewing the screen and the straight line perpendicular to the surface where the screen is located is determined: In the above formula (2), represents the coordinate value of the center point of the eyeball of the i-th eye of the student in the facial image, (X, Y) represents the preset origin coordinate value, L represents the shooting depth of field corresponding to the shooting, f represents the shooting focal length corresponding to the shooting, when i=1, the first eye represents the left eye of the student, and when i=2, the second eye represents the right eye of the student.

5. The online learning quality assessment system as claimed in claim 4, Features: The image capturing and processing module captures the student to obtain the student's facial image, and preprocesses the facial image, specifically including: Adjusting the shooting angle of view and / or shooting focal length of the student so that the facial area of ​​the student is imaged in the central area of ​​the current shooting field of view, thereby obtaining the facial image of the student; Then, the facial image is subjected to background noise reduction filtering, pixel sharpening and pixel binarization processing in sequence, so as to obtain a pre-processed facial image; as well as, The eye coordinate information determination module determines the eye coordinate information of the student according to the preprocessed facial image, specifically including: The eye coordinate information of the two eyes of the student is determined according to the preprocessed facial image.

6. The online learning quality assessment system as claimed in claim 5, Features: The learning concentration state determination module determines the concentration state of the student in the current online learning process according to the eye opening and closing state information and the eye viewing screen sight direction information, specifically including: According to the eye opening and closing state information, the eye viewing direction information and the following formula (3), the student's current online learning concentration evaluation value F is determined: In the above formula (3), ER represents the average value of the eye opening and closing amplitude of the student during the shooting process, α represents the angle between the student's eye line of sight to the screen and the straight line perpendicular to the surface on which the screen is located, and ER max Indicates the maximum opening and closing amplitude of the student's eyes; The online learning concentration evaluation value F is then compared with a preset concentration threshold. If the online learning concentration evaluation value F is greater than or equal to the preset concentration threshold, it is determined that the student is currently in a state of learning concentration; otherwise, it is determined that the student is not currently in a state of learning concentration.

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