CN112329642A - Supervised learning detection method, system, electronic device and medium - Google Patents

Supervised learning detection method, system, electronic device and medium Download PDF

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CN112329642A
CN112329642A CN202011232138.6A CN202011232138A CN112329642A CN 112329642 A CN112329642 A CN 112329642A CN 202011232138 A CN202011232138 A CN 202011232138A CN 112329642 A CN112329642 A CN 112329642A
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eyes
camera
book
position coordinates
eye
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CN112329642B (en
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杨宇孛
聂磊
蒋曼
牟文余
余瑶
郭莉滨
姚富光
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Chongqing University of Education
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Abstract

The invention provides a supervised learning detection method, a system, electronic equipment and a medium, wherein the method comprises the following steps: the desk lamp is provided with a first camera and a second camera, first image information of books on a desk is obtained through the first camera, and second image information of eyes of students is obtained through the second camera; determining the height of the eyes from the book and the moving area of the eyes according to the position coordinates of the book and the position coordinates of the eyes; when the height exceeds a preset height threshold value, or when the activity area exceeds a preset area threshold value, the desk lamp gives out a prompt. Carry on the camera through the desk lamp, carry out image acquisition towards books direction and student's eyes direction respectively, acquire the position coordinate of books and the position coordinate of eyes, and then confirm eyes apart from the height of books and the activity region of eyes, when highly surpassing predetermined high threshold value, perhaps, when the activity region surpassed predetermined regional threshold value, the desk lamp sent the warning.

Description

Supervised learning detection method, system, electronic device and medium
Technical Field
The present invention relates to the field of electronic technologies, and in particular, to a supervised learning detection method, system, electronic device, and medium.
Background
With the development of information technology and communication technology, distance education is popularized, so that common students can obtain high-quality education resources, however, the problems that the students are inconvenient to supervise learning and the learning efficiency are low generally exist in education or learning performed through a remote platform and the information technology.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a supervised learning detection method, system, electronic device and medium, which are used to solve the problem in the prior art that the learning of students is inconvenient to supervise.
To achieve the above and other related objects, the present invention provides a supervised learning detection method, including:
the method comprises the steps that a first camera and a second camera are arranged on a desk lamp, first image information of books on the desk is obtained through the first camera, and second image information of eyes of students is obtained through the second camera, wherein the first image information comprises position coordinates of the books, and the second image information comprises the position coordinates of the eyes;
determining the height of the eyes from the book and the moving area of the eyes according to the position coordinates of the book and the position coordinates of the eyes;
when the height exceeds a preset height threshold value, or when the activity area exceeds a preset area threshold value, the desk lamp gives out a prompt.
Optionally, the first camera is arranged above the second camera, the first camera is arranged towards the book, and the second camera is arranged towards the eyes.
Optionally, the step of acquiring first image information of a book on a desk through a first camera includes:
acquiring a book image, marking a book in the book image, and acquiring a first data set and a first training set;
and inputting the first training set into a neural network for training to obtain a first training model, and performing target recognition on the book image through the first training model to obtain the position coordinates of the book.
Optionally, the step of acquiring second image information of the eyes of the student through a second camera includes;
acquiring an eye image, labeling eyes in the eye image, and acquiring a second data set and a second training set;
and inputting the second training set into a neural network for training to obtain a second training model, and performing target recognition on the eye image through the second training model to obtain the position coordinates of the eyes.
Optionally, the position coordinates of the eyes are weighted to obtain a coordinate mean value, and the centers of the eyes are determined.
Optionally, the active region of the eye is determined by the center of the eye, the focal point of the eye and the position coordinates of the book, and the mathematical expression for determining the active region of the eye is as follows:
F＝K*(∑xi,∑yi,∑zi)+(x1,y1,z1)
K＝L/z0
wherein F is the eye's active area, K is the scale factor, Σ xiIs a set of x-coordinates, Σ y, in the position coordinates of the bookiIs a set of y coordinates, Σ z, in the position coordinates of the bookiIs the set of z coordinates in the position coordinates of the book, (x)1,y1,z1) Is the coordinate of the center of the eye, L is the distance of the center of the eye from the focal point of the eye, z0Is an eyeHeight between the center of the eye and the book in the z-coordinate axis.
Optionally, the step of sending out the reminder by the desk lamp includes: the desk lamp sends out a reminding message and prompts students, and the desk lamp transmits the reminding message to a server or a terminal.
A supervised learning detection system comprising:
the light source module is used for providing a light source;
collection module, collection module includes: the device comprises a first camera and a second camera, wherein the first camera is used for acquiring first image information of books on a desk, and the second camera is used for acquiring second image information of eyes of students, wherein the first image information comprises position coordinates of the books, and the second image information comprises the position coordinates of the eyes;
the recognition module is used for determining the height of the eyes from the book and the movement area of the eyes according to the position coordinates of the book and the position coordinates of the eyes;
and the reminding module is used for sending out a reminding when the height exceeds a preset height threshold value or when the activity area exceeds a preset area threshold value.
An electronic device, comprising: one or more processors; and one or more machine readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform one or more of the methods described.
One or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform one or more of the described methods.
As described above, the supervised learning detection method, system, electronic device and medium of the present invention have the following beneficial effects: .
Carry on the camera through the desk lamp, carry out image acquisition towards books direction and student's eyes direction respectively, acquire the position coordinate of books and the position coordinate of eyes, and then confirm eyes apart from the height of books and the activity region of eyes, when avoiding the student to study on the desk, produce harm to eyesight closely, through monitoring the activity region to student's eyes, when the activity region exceedes predetermined regional threshold value, remind, avoid the student to study the energy not concentrated, the lower problem of learning efficiency, can adapt to remote education application scene.
Drawings
Fig. 1 is a schematic diagram of a supervised learning detection method in an embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating a first camera acquiring a book image according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a second camera acquiring an eye image according to an embodiment of the present invention.
Fig. 4 is a schematic diagram showing the active region of the eye in an embodiment of the present invention.
Fig. 5 is a schematic diagram of eye movement according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a supervised learning detection system in an embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.
It should be noted that the drawings provided in the present embodiment are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated. The structures, proportions, sizes, and other dimensions shown in the drawings and described in the specification are for understanding and reading the present disclosure, and are not intended to limit the scope of the present disclosure, which is defined in the claims, and are not essential to the art, and any structural modifications, changes in proportions, or adjustments in size, which do not affect the efficacy and attainment of the same are intended to fall within the scope of the present disclosure. In addition, the terms "upper", "lower", "left", "right", "middle" and "one" used in the present specification are for clarity of description, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the terms is not to be construed as a scope of the present invention.
Referring to fig. 1 to 5, the present invention provides a supervised learning detection method, including:
s1: the method comprises the steps that a first camera and a second camera are arranged on a desk lamp, first image information of books on a desk is obtained through the first camera, and second image information of eyes of a student is obtained through the second camera, wherein the first image information comprises position coordinates of the books, the second image information comprises the position coordinates of the eyes, for example, a two-dimensional plane where the desk is located can be defined as an xoy coordinate plane, the connecting line direction of the first camera and the second camera can be defined as the z-axis direction, the first camera and the second camera are respectively arranged at two positions on the z-axis, image collection is carried out towards the book direction and the eyes of the student respectively, and the first image information and the second image information are obtained;
s2: determining the height of the eyes from the book and the moving area of the eyes according to the position coordinates of the book and the position coordinates of the eyes;
s3: when the height exceeds a preset height threshold value, or when the activity area exceeds a preset area threshold value, the desk lamp gives out a prompt. Carry on the camera through the desk lamp, carry out image acquisition towards books direction and student's eyes direction respectively, acquire the position coordinate of books and the position coordinate of eyes, and then confirm eyes apart from the height of books and the activity region of eyes, when avoiding the student to study on the desk, produce harm to eyesight closely, through monitoring the activity region to student's eyes, when the activity region exceedes predetermined regional threshold value, remind, avoid the student to study the energy not concentrated, the lower problem of learning efficiency, can adapt to remote education application scene.
Referring to fig. 2 and 3, the first camera is disposed above the second camera, the first camera is disposed toward the book, and the second camera is disposed toward the eyes. For example, the first camera 1 is arranged at z1Position and facing book 3 for image acquisition to obtain first image information, and second camera 2 is arranged in z2Position and image acquisition towards the eye 4, second image information is acquired.
In some embodiments, the step of performing target recognition by supervised learning to obtain the position coordinates of the book in the book image and the position coordinates of the eye in the eye image may include, for example, obtaining the first image information of the book on the desk through the first camera includes:
acquiring a book image, marking a book in the book image, and acquiring a first data set and a first training set;
and inputting the first training set into a neural network for training to obtain a first training model, and performing target recognition on the book image through the first training model to obtain the position coordinates of the book.
The step of acquiring second image information of the eyes of the student through a second camera comprises the following steps;
acquiring an eye image, labeling eyes in the eye image, and acquiring a second data set and a second training set;
and inputting the second training set into a neural network for training to obtain a second training model, and performing target recognition on the eye image through the second training model to obtain the position coordinates of the eyes.
In order to increase the calculation speed, the position coordinates of the eyes may be removed from the calculation process for equivalence, for example, the center point of the eyes is obtained and is equivalent to the position coordinates of the eyes, the set of the position coordinates of the eyes is obtained through target identification, the position coordinates of the eyes are weighted to obtain the coordinate mean value, and the center of the eyes is determined.
Referring to fig. 4 and 5, when the center of the eye rotates from the first point 51 to the second point 52, the visual field range of the eye and the position coordinates of the book 3 can be obtained according to the focal point 6 of the eye, and the active area 5 of the eye can be further obtained through the spatial geometrical relationship, the active area of the eye is determined by the center of the eye, the focal point of the eye and the position coordinates of the book, and the mathematical expression for determining the active area of the eye is as follows:
F＝K*(∑xi,∑yi,∑zi)+(x1,y1,z1)
K＝L/z0
wherein F is the eye's active area, K is the scale factor, Σ xiIs a set of x-coordinates, Σ y, in the position coordinates of the bookiIs a set of y coordinates, Σ z, in the position coordinates of the bookiIs the set of z coordinates in the position coordinates of the book, (x)1,y1,z1) Is the coordinate of the center of the eye, L is the distance of the center of the eye from the focal point of the eye, z0The height between the center of the eye and the book on the z-coordinate axis.
In some implementations, the step of sending the reminder by the desk lamp includes: the desk lamp sends out a reminding message and prompts students, and the desk lamp transmits the reminding message to a server or a terminal.
A supervised learning detection system comprising:
the light source module is used for providing a light source;
collection module, collection module includes: the device comprises a first camera and a second camera, wherein the first camera is used for acquiring first image information of books on a desk, and the second camera is used for acquiring second image information of eyes of students, wherein the first image information comprises position coordinates of the books, and the second image information comprises the position coordinates of the eyes;
the recognition module is used for determining the height of the eyes from the book and the movement area of the eyes according to the position coordinates of the book and the position coordinates of the eyes;
and the reminding module is used for sending out a reminding when the height exceeds a preset height threshold value or when the activity area exceeds a preset area threshold value.
An embodiment of the present invention provides an apparatus, including: one or more processors; and one or more machine readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform one or more of the methods described. The invention is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
Embodiments of the invention also provide one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform one or more of the methods described herein. The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.

Claims (10)

1. A supervised learning detection method is characterized by comprising the following steps:
the method comprises the steps that a first camera and a second camera are arranged on a desk lamp, first image information of books on the desk is obtained through the first camera, and second image information of eyes of students is obtained through the second camera, wherein the first image information comprises position coordinates of the books, and the second image information comprises the position coordinates of the eyes;
determining the height of the eyes from the book and the moving area of the eyes according to the position coordinates of the book and the position coordinates of the eyes;
when the height exceeds a preset height threshold value, or when the activity area exceeds a preset area threshold value, the desk lamp gives out a prompt.
2. The supervised learning detection method of claim 1, wherein the first camera is disposed above the second camera, the first camera is disposed toward a book, and the second camera is disposed toward an eye.
3. The supervised learning detection method of claim 1, wherein the step of acquiring first image information of a book on a desk through a first camera comprises:
acquiring a book image, marking a book in the book image, and acquiring a first data set and a first training set;
and inputting the first training set into a neural network for training to obtain a first training model, and performing target recognition on the book image through the first training model to obtain the position coordinates of the book.
4. The supervised learning detection method of claim 1, wherein the step of acquiring second image information of the eyes of the student through a second camera comprises;
acquiring an eye image, labeling eyes in the eye image, and acquiring a second data set and a second training set;
and inputting the second training set into a neural network for training to obtain a second training model, and performing target recognition on the eye image through the second training model to obtain the position coordinates of the eyes.
5. The supervised learning detection method of claim 1 or 4, wherein the position coordinates of the eyes are weighted to obtain a coordinate mean value, and the center of the eyes is determined.
6. The supervised learning detection method of claim 5, wherein the active region of the eye is determined by the center of the eye, the focal point of the eye and the position coordinates of the book, and the mathematical expression for determining the active region of the eye is as follows:
F＝K*(∑xi,∑yi,∑zi)+(x1,y1,z1)
K＝L/z0
wherein F is the eye's active area, K is the scale factor, Σ xiIs a set of x-coordinates, Σ y, in the position coordinates of the bookiIs a set of y coordinates, Σ z, in the position coordinates of the bookiIs the set of z coordinates in the position coordinates of the book, (x)1,y1,z1) Is the coordinate of the center of the eye, L is the distance of the center of the eye from the focal point of the eye, z0The height between the center of the eye and the book on the z-coordinate axis.
7. The supervised learning detection method of claim 1, wherein the step of sending out a reminder by a desk lamp comprises: the desk lamp sends out a reminding message and prompts students, and the desk lamp transmits the reminding message to a server or a terminal.
8. A supervised learning detection system, comprising:
the light source module is used for providing a light source;
collection module, collection module includes: the device comprises a first camera and a second camera, wherein the first camera is used for acquiring first image information of books on a desk, and the second camera is used for acquiring second image information of eyes of students, wherein the first image information comprises position coordinates of the books, and the second image information comprises the position coordinates of the eyes;
the recognition module is used for determining the height of the eyes from the book and the movement area of the eyes according to the position coordinates of the book and the position coordinates of the eyes;
and the reminding module is used for sending out a reminding when the height exceeds a preset height threshold value or when the activity area exceeds a preset area threshold value.
9. An electronic device, comprising:
one or more processors; and
one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method recited by one or more of claims 1-7.
10. One or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform the method recited by one or more of claims 1-7.
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