WO2020118669A1 - 检测学生专注度的方法、计算机存储介质及计算机设备 - Google Patents
检测学生专注度的方法、计算机存储介质及计算机设备 Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 41
- 239000013598 vector Substances 0.000 claims abstract description 73
- 238000000034 method Methods 0.000 claims abstract description 60
- 238000012360 testing method Methods 0.000 description 21
- 210000003128 head Anatomy 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 238000012937 correction Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 239000011159 matrix material Substances 0.000 description 4
- 230000006399 behavior Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
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- 230000002452 interceptive effect Effects 0.000 description 1
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/70—Multimodal biometrics, e.g. combining information from different biometric modalities
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Definitions
- the invention belongs to the field of student concentration detection, in particular, to a method for detecting student concentration, a computer storage medium and a computer device.
- Method 1 Use the face image of a student whose identity has been determined, and determine whether the student is in a focused state by judging whether the face image is complete. If the detected face image is a complete face, it is determined that the student is in a focused state at the sampling time; otherwise, it is determined that the student is in an unfocused state at the sampling time.
- Method 2 According to different dimensions of learning quality test, build a test question bank and design a concentration test game. Through the students' answers in the game, the concentration of the tested students is evaluated. According to the evaluation results, generate a capacity optimization development report.
- Method one uses whether the complete face can be detected as the sole criterion for determining the student's concentration, ignoring the evaluation of the student's concentration in the context of classroom discussions and teacher assignments, which makes the detection results less objective.
- Method two cannot reflect the real-time concentration of students in the classroom.
- the present invention provides a method, computer storage medium and computer device for detecting student concentration by objective and real-time detection of student concentration.
- a method for detecting student concentration includes:
- the initial concentration of each student is corrected according to the student's posture data of each student, the student's line of sight direction vector, and the position coordinates of the student, so as to obtain the corrected concentration of each student.
- the specific method for correcting the initial concentration of each student according to the student's posture data of each student, the student's line of sight direction vector, and the student's position coordinates includes:
- the initial concentration of the student in a specific state is corrected to concentration.
- the specific state refers to a state in which the direction of the student's line of sight is not directed to the designated reference plane.
- the specific state includes a conversation state or a head down state.
- the specific method of obtaining the students' sight line direction vectors includes:
- the position coordinate of the end point of each student's line of sight direction is determined according to the position coordinate and the line of sight direction of each student, thereby determining the line of sight direction vector of each student; wherein the end point is located on the same plane as the designated reference plane.
- the specific method for obtaining each student's initial concentration according to each student's line-of-sight direction vector includes:
- the initial concentration of each student is determined according to whether the position coordinates of the end point of each student's line-of-sight direction vector are within the designated reference plane.
- the method for acquiring student pose data of each student includes:
- the posture data of the student includes: one of bowing down, lying down, sitting sideways, sitting upright, and turning one's head.
- a computer-readable storage medium characterized in that a program for detecting student concentration is stored on the computer-readable storage medium, and the program for detecting student concentration When the processor executes, it implements the steps of detecting student concentration as described above.
- a computer device includes a memory, a processor, and a program stored on the memory and executable on the processor to detect student concentration, characterized in that When the program for detecting student concentration is executed by the processor, the steps for detecting student concentration are implemented as described above.
- the present invention acquires the student's posture data, student's line-of-sight direction vector and student position coordinates of each student among the multiple students at the detection time, and according to each student's student's posture data, student's line-of-sight direction vector and student position coordinates
- To correct the initial concentration of each student to obtain the corrected concentration of each student you can judge the real-time concentration of the student, and use the results of the students’ classroom behavior tests to modify the results of the concentration test, and the test results can be further Data elimination operations to reduce false positives.
- FIG. 1 is a schematic flowchart of a method for detecting student concentration according to an embodiment of the present invention
- FIG. 2 is a schematic diagram of a student posture image corresponding to student posture data according to an embodiment of the present invention
- FIG. 3 is a view of students according to an embodiment of the present invention Line of sight vector Normalize Schematic diagram of
- FIG. 4 is a schematic diagram of a student in a classroom according to an embodiment of the present invention.
- Figure 5 is a student according to an embodiment of the invention versus Of the student’s sitting posture data are schematic diagrams of reclining;
- FIG. 6 is a line chart of a student's concentration status during a detection period according to an embodiment of the present invention.
- first, second, etc. are for descriptive purposes only, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated.
- the features defined with “first” and “second” may include at least one of the features either explicitly or implicitly.
- “plurality” means at least two, such as two, three, etc., unless otherwise specifically limited.
- FIG. 1 is a schematic flowchart of a method for detecting student concentration according to an embodiment of the present invention.
- the first embodiment of the present invention discloses a method for detecting student concentration, the method includes the steps of:
- the embodiment of the present invention obtains the student's student's posture data, the student's line of sight direction vector and the student's position coordinates at the detection time, judges the student's initial concentration through the student's line of sight direction vector, and then according to the student's posture data and the student's line of sight direction in the classroom Vector and student position coordinates, and then correct the initial degree of each student, so that the test results are more objective and accurate.
- FIG. 2 is a schematic diagram of a student posture image corresponding to student posture data according to an embodiment of the present invention.
- the student posture data M includes bowing, lying down, sitting sideways, sitting sideways, and turning the head.
- a method for acquiring student pose data of each student includes:
- the information is collected in advance to train the posture model through a deep neural network. Thousands of pictures are collected for each type of student posture data, and these marked pictures are used to train the posture model. During actual detection, the collected image of the student's posture is input into the trained posture model, and the posture model calculates and outputs student posture data corresponding to the student's posture image.
- a method for acquiring a student's line-of-sight direction vector includes:
- the direction of each student's line of sight is determined according to each student's face image. Specifically, in this embodiment, the face orientation of each student is detected by detecting the face image of each student, and the face orientation of the student is the line of sight of each student, that is, the direction of the line of sight vector of the student .
- the position coordinates of the end point of each student's line of sight direction are determined according to the position coordinates of each student and the line of sight direction, thereby determining the line of sight direction vector of each student.
- the end point is located on the same plane as the designated reference plane. Specifically, taking the position coordinates of the student as a starting point, it extends along the direction of the student's line of sight, and the point that intersects the plane on the same plane as the designated reference plane is the end point of the direction vector of the line of sight.
- the designated reference plane is a plane area with boundary restrictions.
- the designated reference plane may be a plane area bordered by the boundary of the blackboard or a plane area bordered by the boundary of the projection screen.
- the student's line-of-sight direction vector intersects the plane whose specified reference plane is on the same plane.
- the position coordinates of students in the class are fixed. You can determine the position of each student by collecting images in the class, and select a reference point to determine the position coordinates of all students. In other embodiments, the position coordinates of all students can be determined by two images obtained by two cameras with different positions. The present invention does not limit this, and other methods that can find the position coordinates of students can be used for this In an embodiment of the invention.
- a specific method for obtaining each student's initial concentration according to each student's line-of-sight direction vector includes:
- the initial concentration of each student is determined according to whether the position coordinates of the end point of each student's line-of-sight direction vector are within the designated reference plane.
- the student can be Line of sight vector Normalize Specifically, assuming the reference point X 0 in space, the formula 1 is used for students Line of sight vector Standardize.
- X 0 can select the average value of the position coordinates of all students.
- FIG. 3 is a view of students according to an embodiment of the present invention Line of sight vector Normalize Schematic. After normalizing the line-of-sight direction vector by combining student position coordinates and reference point information, all students can judge whether the end point position of the line-of-sight direction vector is within the specified reference plane by the same criterion.
- a specific method for correcting the initial concentration of each student according to the student's posture data, the student's line-of-sight direction vector, and the student's position coordinates of each student include:
- the initial concentration of the student in a specific state is corrected to concentration.
- the initial concentration data also includes some detection results with the possibility of misjudgment. For example, when the teacher arranges classwork, students need to write down their heads. At this time, the students' eyes are focused on the textbooks, but the students are in a state of concentration. According to the initial concentration test result, the student's concentration will be misjudged as unfocused. This situation needs to be eliminated and the initial concentration of the students corrected.
- the specific state refers to a state where the direction of the student's line of sight is not directed to the designated reference plane.
- the specific gesture includes a conversation state or a head down state.
- FIG. 4 is a schematic diagram of a student in a classroom according to an embodiment of the present invention.
- the position coordinates of all students in the classroom form a matrix X t ;
- the initial concentration of all students in the class constitutes a matrix Y t ;
- the specific state is a conversation state, and by traversing all students, it is determined that the students in the conversation state account for the first proportion of the total number of students. If the first ratio exceeds the preset threshold, it is considered that there is interactive communication between students who meet a certain proportion of requirements at this time, and it can be reasonably concluded that the teacher arranged a group discussion activity. Therefore, the initial concentration of the students in conversation at time t needs to be corrected. Specifically, the initial concentration of the student in the conversation state at time t is corrected to concentration, and the corrected concentration is obtained.
- the conversation state is defined as that the sitting posture data of the student and its neighbors are all sitting sideways, and the direction of the sight direction vector of the student after the specification is the direction of the sight direction vector of the neighboring student from the student to the neighbor student.
- Figure 5 is a student according to an embodiment of the invention versus Of the students’ sitting posture data are schematic diagrams of reclining.
- the following pseudo-code can be used to calculate the number of students in a conversation state.
- the number of students in a conversation state among all students can be calculated as 2 ⁇ count1. Among them, when n is an odd number, the students in the mth column do not judge the conversation state. then If the first ratio is greater than the preset threshold, the concentration of the talking student is corrected to focus to obtain the modified concentration, the concentration of the remaining students is unchanged, and the modified concentration of the remaining students is still the initial concentration. Where 0 ⁇ first ratio ⁇ 1, the value range of the first ratio can be set according to actual needs.
- the concentration of the student in the conversation state is corrected to concentration, thereby obtaining the modified concentration.
- the concentration of the remaining students remains unchanged, and the revised concentration of the remaining students is still the initial concentration.
- the value range of the first ratio can be set according to actual needs.
- the method of judging whether the student is in a conversation state can also adopt other implementations, for example, as long as the student's sitting posture data of one of the neighboring students is sitting sideways and the student's normalized sight direction vector The direction of the line-of-sight direction vector after the specification of the neighboring student is directed by the student to the neighboring student. It is determined that the student is in a conversation state; of course, there may be other implementations, which are not limited by the present invention.
- the student may also need to write down because the teacher has assigned classwork, so the initial concentration of the student who is in the focused state who is writing down is determined to be unfocused. Therefore, as another embodiment of the present invention, the specific state is the head-down state.
- the students in the head-down state account for the first proportion of the total number of students. If the first ratio exceeds the preset threshold, it is considered that there is a head-down behavior of students meeting a certain ratio at this time, it can be reasonably inferred that the teacher arranged classwork, so the students in the head-down state detected at the detection time t
- the initial concentration of should be corrected to concentration, to obtain the modified concentration.
- the following pseudo-codes can be used to calculate the number of students who are in a head-down state.
- the concentration of the students in the head-down state is corrected to concentration, and the concentration of the remaining students remains unchanged.
- the revised concentration of the remaining students is still the initial concentration.
- the value range of the first ratio can be set according to actual needs.
- the present invention acquires the student's posture data, student's line-of-sight direction vector and student position coordinates of each student among the multiple students at the detection time, and according to each student's student's posture data, student's line-of-sight direction vector and student position coordinates To correct the initial concentration of each student to obtain the corrected concentration of each student, you can judge the student's real-time concentration, and use the results of the students' classroom behavior detection to modify the results of the concentration detection, which can improve the accuracy of the detection results Sex.
- This embodiment discloses a method for obtaining the concentration rate of the students in the detection period.
- the method of this embodiment is based on the method of detecting the concentration of students at time t in Embodiment 1 to obtain the students within a detection period Correction concentration.
- One of the testing cycles includes multiple testing moments, the students at each testing moment The degree of concentration is obtained using the method of Embodiment 1.
- FIG. 6 is a line chart of a student’s concentration state during a detection period according to an embodiment of the present invention.
- 7 is a line chart of the concentration rate of the students in the math class during the detection period according to the embodiment of the present invention.
- a detection cycle includes 19 detection moments, 0 indicates that the student is in a non-focused state, and 1 indicates that the student is in a focused state.
- a test cycle can be based on a class, by calculating students The concentration rate of each class in a day can get the change of the concentration rate of the students during the day.
- This embodiment discloses a method for obtaining the concentration rate of the entire class of students in the detection cycle.
- the method of this embodiment is based on the method of detecting the concentration of students at time t in Embodiment 1, and obtains the corrected concentration of I t of all students in a class in a detection cycle.
- One of the detection cycles includes multiple detection moments, and the corrected concentration of I t of all students in the class at each detection moment is obtained using the method of Embodiment 1.
- This embodiment discloses a method for obtaining the concentration rate of the students in the detection period.
- the method of this embodiment is based on the method of detecting the concentration of students at time t in Embodiment 1 to obtain the students within a detection period Concentration.
- One of the testing cycles includes the testing time, the students at each testing time The degree of concentration is obtained using the method of Embodiment 1.
- the change curve of the class concentration rate can be obtained.
- the present invention also provides another embodiment, that is, to provide a computer-readable storage medium that stores a program for detecting student concentration, and the program for detecting student concentration can be processed by at least one To execute the following steps:
- S200 obtains each student's initial concentration according to each student's line of sight direction vector
- S300 corrects each student's initial concentration according to the student's posture data of each student, the student's line of sight direction vector, and the student's position coordinates, so as to obtain the corrected concentration of each student.
- a fifth embodiment of the present invention provides a computer device.
- the computer device may be a computer device such as a notebook computer.
- the computer device includes a memory, a processor, and a program that is stored on the memory and can be run on the processor to detect student concentration.
- the memory includes at least one type of readable storage medium, which is used to store an operating system and various application software installed on the computer device, such as program codes for detecting student concentration.
- the memory can also be used to temporarily store various types of data that have been or will be output.
- the processor may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip.
- the processor 22 is generally used to control the overall operation of the mobile terminal 2.
- the processor 22 is used to run program codes or process data stored in the memory, for example, to run the program for detecting student concentration.
- the program for detecting student concentration is used to detect student concentration.
- the program for detecting student concentration is executed by the processor, the following steps are implemented:
- S200 obtains each student's initial concentration according to each student's line of sight direction vector
- S300 corrects each student's initial concentration according to the student's posture data of each student, the student's line of sight direction vector, and the student's position coordinates, so as to obtain the corrected concentration of each student.
- FIG. 1 does not constitute a limitation on the computer device 2, and the computer device may further include other necessary components, or combine certain components, or arrange different components.
- the methods in the above embodiments can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware, but in many cases the former is better Implementation.
- the technical solutions of the present invention can be embodied in the form of software products in essence or part of contributions to the existing technology, and the computer software products are stored in a storage medium (such as ROM/RAM, magnetic disk,
- the CD-ROM includes several instructions to enable a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the method described in each embodiment of the present invention.
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Claims (20)
- 一种检测学生专注度的方法,其中,包括:获取多个学生中每个学生的学生姿态数据、学生视线方向向量及学生位置坐标;根据每个学生的视线方向向量获得每个学生的初始专注度;根据每个学生的学生姿态数据、学生视线方向向量及学生位置坐标对每个学生的初始专注度进行修正,以获得每个学生的修正专注度。
- 根据权利要求1所述的方法,其中,根据每个学生的学生姿态数据、学生视线方向向量及学生位置坐标对每个学生的初始专注度进行修正的具体方法包括:根据每个学生的学生姿态数据、学生视线方向向量及学生位置坐标判断每个学生是否处于特定状态;获取处于特定状态的学生的数量与所有学生的数量的第一比值;在所述第一比值大于预设阈值的情况下将处于特定状态的学生的初始专注度修正为专注。
- 根据权利要求2所述的方法,其中,所述特定状态指的是学生的视线方向未指向指定参照面的状态。
- 根据权利要求3所述的检测方法,其中,所述特定状态包括交谈状态或低头状态。
- 根据权利要求1所述的方法,其特征在于,其中,所述获取学生视线方向向量的具体方法包括:获取每个学生的人脸图像;根据每个学生的人脸图像确定每个学生的视线方向;根据每个学生的位置坐标和视线方向确定每个学生的视线方向的终点的位置坐标,从而确定每个学生的视线方向向量;其中,所述终点位于与指定参照面处于同一平面的平面上。
- 根据权利要求5所述的方法,其中,所述根据每个学生的视线方向向量获得每个学生的初始专注度的具体方法包括:根据每个学生的视线方向向量的终点的位置坐标是否位于所述指定参照面内来确定每个学生的初始专注度。
- 根据权利要求1所述的方法,其中,所述每个学生的学生姿态数据的获取方法包括:获取每个学生的身姿图像;将获取的每个学生的身姿图像输入到训练好的身姿模型,以得到每个学生的姿态数据。
- 根据权利要求7所述的方法,其中,所述学生的姿态数据包括:低头、趴倒、侧身斜坐、立身端坐及扭头中的一种。
- 一种计算机可读存储介质,其中,所述计算机可读存储介质上存储有检测学生专注度的程序,所述检测学生专注度的的程序被处理器执行时实现:获取多个学生中每个学生的学生姿态数据、学生视线方向向量及学生位置坐标;根据每个学生的视线方向向量获得每个学生的初始专注度;根据每个学生的学生姿态数据、学生视线方向向量及学生位置坐标对每个学生的初始专注度进行修正,以获得每个学生的修正专注度。
- 根据权利要求9所述的计算机可读存储介质,其中,所述检测学生专注度的的程序被处理器执行时,还实现:根据每个学生的学生姿态数据、学生视线方向向量及学生位置坐标判断每个学生是否处于特定状态;获取处于特定状态的学生的数量与所有学生的数量的第一比值;在所述第一比值大于预设阈值的情况下将处于特定状态的学生的初始专注度修正为专注。
- 根据权利要求10所述的计算机可读存储介质,其中,所述特定状态指的是学生的视线方向未指向指定参照面的状态。
- 根据权利要求11所述的计算机可读存储介质,其中,所述特定状态包括交谈状态或低头状态。
- 根据权利要求1所述的计算机可读存储介质,其中,所述检测学生专注度的的程序被处理器执行时,还实现:获取每个学生的人脸图像;根据每个学生的人脸图像确定每个学生的视线方向;根据每个学生的位置坐标和视线方向确定每个学生的视线方向的终点的位置坐标,从而确定每个学生的视线方向向量;其中,所述终点位于与指定参照面处于同一平面的平面上。
- 根据权利要求13所述的方法,其中,所述检测学生专注度的的程序被处理器执行时,还实现:根据每个学生的视线方向向量的终点的位置坐标是否位于所述指定参照面内来确定每个学生的初始专注度。
- 一种计算机设备,其中,所述计算机设备包括存储器、处理器及存储在存储器上并可在处理器上运行的检测学生专注度的程序,所述检测学生专注度的程序被处理器执行时实现:获取多个学生中每个学生的学生姿态数据、学生视线方向向量及学生位置坐标;根据每个学生的视线方向向量获得每个学生的初始专注度;根据每个学生的学生姿态数据、学生视线方向向量及学生位置坐标对每个学生的初始专注度进行修正,以获得每个学生的修正专注度。
- 根据权利要求15所述的计算机设备,其中,所述检测学生专注度的程序被处理器执行时,还实现:根据每个学生的学生姿态数据、学生视线方向向量及学生位置坐标判断每个学生是否处于特定状态;获取处于特定状态的学生的数量与所有学生的数量的第一比值;在所述第一比值大于预设阈值的情况下将处于特定状态的学生的初始专注度修正为专注。
- 根据权利要求16所述的计算机设备,其中,所述特定状态指的是学生的视线方向未指向指定参照面的状态。
- 根据权利要求17所述的计算机设备,其中,所述特定状态包括交谈状态或低头状态。
- 根据权利要求15所述的计算机设备,其中,所述检测学生专注度的程序被处理器执行时,还实现:获取每个学生的人脸图像;根据每个学生的人脸图像确定每个学生的视线方向;根据每个学生的位置坐标和视线方向确定每个学生的视线方向的终点的位置坐标,从而确定每个学生的视线方向向量;其中,所述终点位于与指定参照面处于同一平面的平面上。
- 根据权利要求19所述的计算机设备,其中,所述检测学生专注度的程序被处理器执行时,还实现:根据每个学生的视线方向向量的终点的位置坐标是否位于所述指定参照面内来确定每个学生的初始专注度。
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