CN114245068A - Behavior supervision method and device, electronic equipment and storage medium - Google Patents
Behavior supervision method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN114245068A CN114245068A CN202111272017.9A CN202111272017A CN114245068A CN 114245068 A CN114245068 A CN 114245068A CN 202111272017 A CN202111272017 A CN 202111272017A CN 114245068 A CN114245068 A CN 114245068A
- Authority
- CN
- China
- Prior art keywords
- target person
- behavior
- voice
- person
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 64
- 230000006399 behavior Effects 0.000 claims description 177
- 238000004590 computer program Methods 0.000 claims description 11
- 206010000117 Abnormal behaviour Diseases 0.000 claims description 8
- 230000003542 behavioural effect Effects 0.000 claims 1
- 239000012141 concentrate Substances 0.000 abstract description 9
- 230000002035 prolonged effect Effects 0.000 abstract description 2
- 230000002159 abnormal effect Effects 0.000 description 12
- 238000010586 diagram Methods 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 210000001747 pupil Anatomy 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 238000012806 monitoring device Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000013145 classification model Methods 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Business, Economics & Management (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Human Computer Interaction (AREA)
- Acoustics & Sound (AREA)
- Emergency Management (AREA)
- Signal Processing (AREA)
- Image Analysis (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a behavior supervision method, a behavior supervision device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining the behavior state of a target person based on an object image of a target person operation object and/or a person voice of the target person; and sending out prompt information based on the behavior state of the target person. According to the method, the device, the electronic equipment and the storage medium, the behavior state of the target person is determined by applying the object image of the target person operation object and/or the person voice of the target person, and the reminding is performed based on the behavior state, so that the automatic behavior supervision of the target person can be realized, the whole-course participation of the supervisor is not needed, the time of the supervisor is saved, the time for the target person to concentrate on work/study is prolonged, and the work/study efficiency and the work/study quality of the target person are improved.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a behavior monitoring method and apparatus, an electronic device, and a storage medium.
Background
The pupils are hard to concentrate on the study for a long time, and often play rubber and turn pens during the writing process, so that the pupils usually need to spend a lot of time to complete the work.
At present, parents usually choose to supervise children to learn in order to enable pupils to complete work better and faster, but the mode not only occupies a great amount of time of the parents, but also enables the pupils to deliberately find parents to chat so as to learn with distraction, and the work completion efficiency and the learning efficiency are not effectively improved.
Disclosure of Invention
The invention provides a behavior supervision method, a behavior supervision device, electronic equipment and a storage medium, which are used for overcoming the defect that the learning efficiency of students cannot be effectively improved in the prior art and improving the working/learning efficiency and the working/learning quality of target personnel.
The invention provides a behavior supervision method, which comprises the following steps:
determining the behavior state of a target person based on an object image of a target person operation object and/or a person voice of the target person;
and sending out prompt information based on the behavior state of the target person.
According to a behavior supervision method provided by the present invention, the determining a behavior state of a target person based on an object image of a target person operation object and/or a person voice of the target person includes:
performing operation object identification on the object image to obtain the content of the current operation object;
and determining the behavior state of the target person based on the current work object content and the last work object content, wherein the last work object content is the work object content before the current work object content.
According to a behavior supervision method provided by the present invention, the determining a behavior state of a target person based on an object image of a target person operation object and/or a person voice of the target person includes:
carrying out voice classification on the personnel voice to obtain a voice classification result of the target personnel;
and determining the behavior state of the target person based on the voice classification result of the target person.
According to the behavior supervision method provided by the invention, the voice classification of the personnel voice to obtain the voice classification result of the target personnel comprises the following steps:
carrying out voice recognition on the personnel voice to obtain a voice recognition text of the personnel voice;
and performing text classification on the voice recognition text to obtain a voice classification result of the target person.
According to a behavior supervision method provided by the present invention, the determining a behavior state of a target person based on an object image of a target person operation object and/or a person voice of the target person includes:
determining the current behavior of the target person based on the object image and/or the person voice and the person image of the target person;
and determining the behavior state of the target person based on the current behavior of the target person.
According to a behavior supervision method provided by the present invention, the determining a behavior state of a target person based on an object image of a target person operation object and/or a person voice of the target person includes:
determining target behaviors of the target person based on the historical object images and the historical person voices;
and determining the behavior state of the target person based on the target behavior of the target person and the object image or the person voice.
According to the behavior supervision method provided by the invention, the sending out the prompt information based on the behavior state of the target person comprises the following steps:
and if the times of the target person with abnormal behavior state in the preset time interval exceed a time threshold, and/or the accumulated time of the target person with abnormal behavior state in the preset time interval exceeds a time threshold, sending the prompt message.
The present invention also provides a behavior supervision device, comprising:
the determining module is used for determining the behavior state of the target person based on the object image of the target person operation object and/or the person voice of the target person;
and the prompt module is used for sending out prompt information based on the behavior state of the target person.
The present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the behavior supervision method according to any of the above aspects when executing the program.
The invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the behavior supervision method according to any of the above-mentioned methods.
According to the behavior supervision method, the behavior supervision device, the electronic equipment and the storage medium, the behavior state of the target person is determined by applying the object image of the target person operation object and/or the person voice of the target person, and the reminding is performed based on the behavior state, so that the automatic behavior supervision of the target person can be realized, the whole-process participation of the supervisor is not needed, the time of the supervisor is saved, the time for the target person to concentrate on work/study is prolonged, and the work/study efficiency and the work/study quality of the target person are improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a behavior supervision method provided by the present invention;
FIG. 2 is a flow chart of a behavior state determination method provided by the present invention;
FIG. 3 is a second schematic flow chart of the behavior state determination method provided by the present invention;
FIG. 4 is a flow chart of a speech classification method provided by the present invention;
FIG. 5 is a third schematic flow chart of a behavior state determination method provided by the present invention;
FIG. 6 is a fourth flowchart illustrating a behavior state determination method according to the present invention;
FIG. 7 is a schematic diagram of the behavior surveillance device provided by the present invention;
fig. 8 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a behavior supervision method. Fig. 1 is a schematic flow chart of a behavior supervision method provided by the present invention, and as shown in fig. 1, the method includes:
and step 120, sending out prompt information based on the behavior state of the target person.
Specifically, the target person is a person needing supervision, such as a student, an employee, or the like. The target person work object is an object operated by the target person to complete a given task in production, learning, and the like, for example, the target person is a student, and the work object may be a workbook, and for example, the target person is an employee, and the work object may be a computer document. The object image is an image including a working object of the target person, and the image may be a working object image directly acquired by a camera, a scanner, or other image acquisition devices with a photographing function, or may be a working object image after image preprocessing, which is not specifically limited in this embodiment of the present invention. The voice data may be obtained through sound pickup equipment, where the sound pickup equipment may be a smart phone, a tablet computer, or an intelligent electrical apparatus such as a sound, an intelligent clock, or the like, and the sound pickup equipment may further amplify and reduce noise of the voice data after acquiring the voice data through sound pickup by the microphone array.
In order to supervise work or study of target personnel and improve the time for the target personnel to concentrate on the work or study, the embodiment of the invention determines the behavior state of the target personnel according to the object image of the working object of the target personnel, or the personnel voice of the target personnel, or the object image of the working object of the target personnel and the personnel voice of the target personnel. Here, the behavior state of the target person is used to represent whether the target person is in a normal working state or a learning state, for example, if it is determined that the working object of the target person has not changed according to the object image of the working object of the target person, it may be determined that the target person has dozing, distraction, or the like, and the behavior state of the target person is abnormal, or if it is determined that the target person is speaking in a chat according to the person's voice of the target person, it may be determined that the behavior state of the target person is also abnormal.
When the object image is applied, the current behavior of the target person may be determined according to the corresponding relationship between the sample object image and each candidate behavior and the object image, and then the behavior state of the target person is determined according to the current behavior, or the object image may be subjected to image recognition, and then the behavior state of the target person is determined according to a recognition result, which is not specifically limited in the embodiment of the present invention. When the personnel voice is applied, the personnel voice can be subjected to voice recognition, and then the behavior state of the target personnel is determined according to the recognition result.
After the behavior state of the target person is obtained, if the behavior state of the target person is abnormal, it may be determined that the target person is not currently attending to work or study, a prompt message may be directly sent to the target person to remind the target person to attend to work or study, a prompt message may also be sent to a supervisor of the target person to remind the supervisor to supervise the target person to attend to work or study, the prompt message may not be sent temporarily, and when it is determined that the number of times or the accumulated duration of the target person attending to work or study within a period of time exceeds a certain threshold, the sending of the prompt message is triggered. It is understood that the supervisor of the target person may be a parent if the target person is a student, and a leader if the target person is an employee.
According to the method provided by the embodiment of the invention, the behavior state of the target person is determined by applying the object image of the target person operation object and/or the person voice of the target person, and the reminding is carried out based on the behavior state, so that the automatic behavior supervision of the target person can be realized, the whole-course participation of the supervisor is not needed, the time of the supervisor is saved, the time for the target person to concentrate on work/study is increased, and the work/study efficiency and the work/study quality of the target person are improved.
Based on any of the above embodiments, fig. 2 is a schematic flow chart of a behavior state determination method provided by the present invention, as shown in fig. 2, the method includes:
and step 112, determining the behavior state of the target person based on the current work object content and the last work object content, wherein the last work object content is the work object content before the current work object content.
Specifically, considering that work content or learning content of a target person generally needs to surround a homework object, for example, learning content of a student is generally a homework, embodiments of the present invention determine a behavior state of the target person according to an object image of the target person homework object: firstly, acquiring an object image of an operation object of a target person, identifying the operation object of the object image to obtain the content of the current operation object, then comparing the content of the current operation object with the content of the previous operation object to obtain a comparison result, if the comparison result is changed, indicating that the target person works or learns, and determining that the behavior state of the target person is normal. Here, the previous job target content is a job target content before the current job target content.
Furthermore, the object image of the target person operation object may be acquired at preset time intervals, and for the currently acquired object image, the last acquired object image is the previous object image, and the previous object image is subjected to operation object identification to obtain the previous operation object content. Preferably, the preset time interval may be set to a short duration in order to secure the effect of the behavior supervision.
Based on any of the above embodiments, fig. 3 is a second schematic flow chart of the behavior state determination method provided by the present invention, as shown in fig. 3, the method includes:
and step 114, determining the behavior state of the target person based on the voice classification result of the target person.
Specifically, considering that the work content or the learning content of the target person may be related to voice data, for example, the learning content of a student is reading lessons, the work content of an employee is speaking, and if the target person is talking and chatting, voice data is also sent out, so in order to determine the behavior state of the target person according to the person voice of the target person, in the embodiment of the present invention, after the person voice of the target person is obtained through the sound pickup device, the person voice can be subjected to voice classification, so as to obtain the voice classification result of the target person, and on this basis, the behavior state of the target person can be determined according to the voice classification result of the target person.
Here, the voice classification result is used to represent whether voice content exists in the voice of the person, and if so, also to represent whether the voice content is related to work or learning content, for example, the target person is a student, and if the voice classification result of the target person is a text, that is, the voice content of the voice of the representative person is related to the learning content, it may be determined that the target person is in a normal learning state, that is, the behavior state of the target person is normal, according to the voice classification result.
Based on any of the above embodiments, fig. 4 is a schematic flow chart of the speech classification method provided by the present invention, as shown in fig. 4, the method includes:
and step 1131, performing text classification on the voice recognition text to obtain a voice classification result of the target person.
Specifically, the voice classification result of the target person may be obtained as follows: firstly, voice recognition is carried out on the voice of the target person, so that the voice of the person can be transcribed into a voice recognition text, the text content covered by the voice of the person is obtained, then, the voice recognition text of the voice of the person is subjected to text classification, the voice classification result of the target person is obtained, and therefore whether the voice content of the voice of the person is related to the work or study content or not can be judged. Here, the manner of speech recognition and text classification in the embodiment of the present invention is not particularly limited, and may be implemented by using a speech recognition model and a text classification model, for example.
Based on any of the above embodiments, fig. 5 is a third schematic flow chart of the behavior state determination method provided by the present invention, as shown in fig. 5, the method includes:
and step 116, determining the behavior state of the target person based on the current behavior of the target person.
Specifically, in order to supervise work or learning of the target person and improve the time for the target person to concentrate on the work or the learning, the embodiment of the present invention determines the current behavior of the target person according to the object image of the current target person work object and the person image of the target person, or according to the person voice and the person image of the current target person, or according to the object image of the current target person work object and the person voice and the person image of the target person at the same time, where the current behavior is used for representing the action currently performed by the target person, and on the basis, determines the behavior state of the target person according to the current behavior of the target person. Here, the person image includes an image of the upper body of the target person.
For example, the target person is a student, the behavior of the person image of the target person is recognized, the student is known to hold a pen, the object image is recognized, the obtained content of the current object is compared with the content of the previous object, and if the content of the homework book is not changed, the current behavior of the target person can be determined to be that the pen is held without writing, which indicates that the target person may have the situations of dozing, distraction, intentional false mounting and the like, and the behavior state of the target person can be determined to be abnormal according to the current behavior of the target person; for another example, the behavior recognition is performed on the person image of the target person to know that the student is holding the textbook, and the voice recognition is performed on the person voice to know that the person voice has no voice content, so that the current behavior of the target person can be determined to be reading aloud, and the behavior state of the target person can be determined to be abnormal according to the current behavior of the target person.
Specifically, the current behavior of the target person may be determined only according to the person image of the target person, and then the behavior state of the target person may be determined according to the current behavior of the target person. For example, if the person image of the target person is subjected to behavior recognition and it is known that the target person is currently playing with an article unrelated to work or study, such as an eraser, a toy, a magic cube, etc., the behavior state of the target person can be determined to be abnormal according to the behavior; for another example, if the person image of the target person is subjected to face detection and expression recognition is performed based on the face area, and the target person is known to be dozing, the behavior state of the target person can be determined to be abnormal according to the behavior; for example, if the person image of the target person is detected as sitting posture and the target person is currently lying on a table, the behavior state of the target person may be determined to be abnormal according to the behavior.
Based on any of the above embodiments, fig. 6 is a fourth schematic flow chart of the behavior state determination method provided by the present invention, as shown in fig. 6, the method includes:
and step 118, determining the behavior state of the target person based on the target behavior of the target person and the object image or the person voice.
Specifically, considering that there may be a determination error if the behavior state of the target person is determined only from the object image of the work object of the target person or the person voice of the target person, for example, if the target person is a student, when the learning content of the student is reading aloud, since the student does not need to write a work at this time, the content of the work object does not change, and if the behavior state of the target person is determined only from the object image of the work object, the result will be that the behavior state of the student is abnormal.
For the problem, the embodiment of the present invention collects a piece of data, i.e., a historical object image and a historical person voice, in advance, and determines the target behavior of the target person, i.e., the specific work or learning content of the target person according to the data, and on this basis, the accurate behavior state of the target person can be determined according to the target behavior of the target person, the object image of the current target person operation object or the person voice of the current target person. For example, the target behavior of the target person is determined as writing operation according to the historical object image and the historical person voice, and the behavior state of the target person can be determined only according to the object image of the target person operation object, and the specific process is as follows: and identifying the operation object of the object image of the operation object of the target person, comparing the obtained current operation object content with the previous operation object content, if no change is found, directly determining that the behavior state of the target person is abnormal, and if a change is found, directly determining that the behavior state of the target person is normal.
Here, the specific target behavior pre-determination manner may be to determine the target behavior of the target person according to the correspondence between the sample object image and the sample person voice and each candidate target behavior, and the historical object image and the historical person voice, or to perform image recognition and voice recognition on the historical object image and the historical person voice, and determine the target behavior of the target person according to a recognition result, which is not specifically limited in the embodiment of the present invention.
Based on any of the above embodiments, step 120 includes:
and if the times of the target person with abnormal behavior state in the preset time interval exceed the time threshold, and/or the accumulated time of the target person with abnormal behavior state in the preset time interval exceeds the time threshold, sending a prompt message.
Specifically, considering that the target person takes a short rest and distraction, the fatigue caused by work or learning can be reduced, and instead, the fatigue can have a positive effect on the subsequent work or learning efficiency, for this reason, the embodiment of the present invention counts the behavior state of the target person within a period of time, that is, within a preset period of time, and if it is judged that the number of times that the behavior state of the target person is abnormal within the preset period of time exceeds a number threshold, and/or the accumulated duration that the behavior state of the target person is abnormal within the preset period of time exceeds a duration threshold, the method can start to send out prompt information to remind the target person to concentrate on work or learning, or remind a supervisor of the target person to supervise and prompt the target person to concentrate on work or learning.
Here, the preset time period may be preset according to actual needs, or may be set according to empirical values, and the unit of the preset time period may be day, hour, and the like, which is not specifically limited in the embodiment of the present invention. The time threshold and the duration threshold are both used as comparison parameters to judge whether to trigger the condition of sending the prompt message, and the time threshold and the duration threshold can be preset without specific numerical limitation. Specific ways of sending the prompt message include, but are not limited to, desktop lifting prompt, voice broadcast prompt and indicator light prompt.
Based on any one of the above embodiments, taking a student as an example, the embodiment of the present invention provides a student learning supervision method, so as to improve the time of the student concentrating on learning and improve the learning efficiency and the learning quality of the student, and the specific flow of the method is as follows:
s1) acquiring the learning state of the student in the current time period;
the current time period is a time period [ the last acquisition time for the student, the current acquisition time for the student ]; the specific duration of the current time period is not limited and can be preset; the specific learning state acquisition mode is not limited, for example, an AI (Artificial Intelligence) camera is used for image acquisition, and learning state recognition is performed based on an image;
the learning state may include learning and non-learning, and the learning state of the student is non-learning, including but not limited to the following cases: the pen is still, no sound is read aloud, the eraser is played, the pen is rotated, the toy is played, the chat is carried out, the content on the workbook is not updated, and the like; the content on the exercise book can be judged by regularly acquiring the content on the exercise book, the acquired results of two adjacent times are compared, and if the content on the exercise book is found to have no obvious change, the content on the exercise book is not updated;
s2) counting the learning state of the student in the current time period as the accumulated non-learning time length;
the current time period is composed of N time points (N ≧ 1, N is a positive integer), when the learning state of the student at the ith time point starts to be non-learning and finishes the state at the jth time point, the non-learning dynamic event occurs in the time period corresponding to the ith time point, and in the non-learning dynamic event, the learning state of the student is that the duration of non-learning is tiJ-i, (i ≦ j ≦ N, i, j both positive integers); summing the durations corresponding to all non-learning dynamic events occurring within the current time period, i.e., t ∑ tiDetermining the learning state of the student in the current time period as the accumulated time t of non-learning;
s3) judging whether the accumulated time length of which the learning state is non-learning meets a first preset condition or not, and if so, sending out prompt information in a preset mode;
judgment example: the first preset condition may be that the occupation ratio of the accumulated time duration in the current time period exceeds an occupation ratio threshold, the learning state of the student is that the accumulated time duration of non-learning is T, the current time period is T, and the occupation ratio of the accumulated time duration in the current time period is γ ═ T/T, when the accumulated time duration satisfies the first preset condition, that is, γ exceeds the occupation ratio threshold, it indicates that the student is not paying attention, and the student needs to be reminded to learn, so as to improve the learning efficiency of the student; the duty ratio threshold is used as a comparison parameter to judge whether a condition for reminding students to learn is triggered, and can be preset. The preset mode includes but is not limited to desktop lifting reminding, voice broadcast reminding and indicator light reminding.
In order to accurately supervise the student to learn seriously, the following steps can be added on the basis of the steps from S1 to S3:
s4) counting the times that the learning state of the student is non-learning in the current time period;
the current time period is composed of N time points (N ≧ 1, N is a positive integer), and when the learning state of the student at the ith time point starts to be non-learning and ends at the jth time point, the count is 1iIndicating that a non-learning dynamic event occurs at a corresponding time period of the ith time point, (i ≦ j ≦ N, and both i and j are positive integers); corresponding 1 to all non-learning dynamic events occurring in the current time periodiPerform cumulative summation, i.e. h ═ Σ 1iDetermining the number h of times that the learning state of the student is non-learning in the current time period;
s5) judging whether the learning state is that the non-learning times meet a second preset condition, if so, sending out prompt information in a preset mode;
judgment example: the second preset condition may be that the occurrence frequency of the times in the current time period exceeds a frequency threshold, the learning state of the student is that the number of times of non-learning is h, the current time period is T, and the ratio of the times in the current time period is α ═ h/T, when the times satisfy the second preset condition, that is, α exceeds the frequency threshold, it indicates that the student is not paying attention, and the student needs to be reminded of paying attention to learning, so as to improve the learning efficiency of the student; the frequency threshold may be preset, and is not limited to a specific value.
The following describes the behavior monitoring device provided by the present invention, and the behavior monitoring device described below and the behavior monitoring method described above may be referred to correspondingly.
Based on any one of the above embodiments, an embodiment of the present invention provides a behavior supervision device. Fig. 7 is a schematic structural diagram of a behavior supervision apparatus provided by the present invention, and as shown in fig. 7, the apparatus includes:
a determination module 710 for determining a behavior state of the target person based on the object image of the target person job object and/or the person voice of the target person;
and the prompt module 720 is configured to send out prompt information based on the behavior state of the target person.
The device provided by the embodiment of the invention determines the behavior state of the target person by applying the object image of the target person operation object and/or the person voice of the target person, and reminds based on the behavior state, so that the automatic behavior supervision of the target person can be realized, the whole process participation of the supervisor is not needed, the time of the supervisor is saved, the time for the target person to concentrate on work/study is improved, and the work/study efficiency and the work/study quality of the target person are improved.
Based on any of the above embodiments, the determining module 710 includes:
the operation object identification unit is used for carrying out operation object identification on the object image to obtain the content of the current operation object;
and a first behavior state determination unit configured to determine a behavior state of the target person based on the current work object content and a previous work object content, the previous work object content being a work object content before the current work object content.
Based on any of the above embodiments, the determining module 710 includes:
the voice classification unit is used for performing voice classification on the voice of the personnel to obtain a voice classification result of the target personnel;
and the second behavior state determining unit is used for determining the behavior state of the target person based on the voice classification result of the target person.
Based on any one of the above embodiments, the speech classification unit includes:
the voice recognition unit is used for carrying out voice recognition on the personnel voice to obtain a voice recognition text of the personnel voice;
and the text classification unit is used for performing text classification on the voice recognition text to obtain a voice classification result of the target person.
Based on any of the above embodiments, the determining module 710 includes:
the current behavior determining unit is used for determining the current behavior of the target person based on the object image and/or the person voice and the person image of the target person;
and the third behavior state determination unit is used for determining the behavior state of the target person based on the current behavior of the target person.
Based on any of the above embodiments, the determining module 710 includes:
a target behavior determination unit for determining a target behavior of the target person based on the history object image and the history person voice;
and the fourth behavior state determination unit is used for determining the behavior state of the target person based on the target behavior of the target person and the object image or the person voice.
Based on any of the above embodiments, the prompt module 720 includes:
and if the times of the target person with abnormal behavior state in the preset time interval exceed the time threshold, and/or the accumulated time of the target person with abnormal behavior state in the preset time interval exceeds the time threshold, sending a prompt message.
Fig. 8 illustrates a physical structure diagram of an electronic device, and as shown in fig. 8, the electronic device may include: a processor (processor)810, a communication Interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication Interface 820 and the memory 830 communicate with each other via the communication bus 840. Processor 810 may call logic instructions in memory 830 to perform a behavior supervision method comprising: determining the behavior state of the target person based on the object image of the target person operation object and/or the person voice of the target person; and sending out prompt information based on the behavior state of the target person.
In addition, the logic instructions in the memory 830 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being storable on a non-transitory computer-readable storage medium, the computer program, when executed by a processor, being capable of executing the behavior supervision method provided by the above methods, the method comprising: determining the behavior state of the target person based on the object image of the target person operation object and/or the person voice of the target person; and sending out prompt information based on the behavior state of the target person.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program, which when executed by a processor, implements a behavior supervision method provided by the above methods, the method comprising: determining the behavior state of the target person based on the object image of the target person operation object and/or the person voice of the target person; and sending out prompt information based on the behavior state of the target person.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of behavioral supervision, comprising:
determining the behavior state of a target person based on an object image of a target person operation object and/or a person voice of the target person;
and sending out prompt information based on the behavior state of the target person.
2. A behavior supervision method according to claim 1, characterized in that the determining of the behavior state of the target person based on the object image of the target person work object and/or the person voice of the target person comprises:
performing operation object identification on the object image to obtain the content of the current operation object;
and determining the behavior state of the target person based on the current work object content and the last work object content, wherein the last work object content is the work object content before the current work object content.
3. A behavior supervision method according to claim 1, characterized in that the determining of the behavior state of the target person based on the object image of the target person work object and/or the person voice of the target person comprises:
carrying out voice classification on the personnel voice to obtain a voice classification result of the target personnel;
and determining the behavior state of the target person based on the voice classification result of the target person.
4. The behavior supervision method according to claim 3, wherein the performing voice classification on the human voice to obtain the voice classification result of the target human comprises:
carrying out voice recognition on the personnel voice to obtain a voice recognition text of the personnel voice;
and performing text classification on the voice recognition text to obtain a voice classification result of the target person.
5. A behavior supervision method according to claim 1, characterized in that the determining of the behavior state of the target person based on the object image of the target person work object and/or the person voice of the target person comprises:
determining the current behavior of the target person based on the object image and/or the person voice and the person image of the target person;
and determining the behavior state of the target person based on the current behavior of the target person.
6. A behavior supervision method according to any of claims 1-5, characterized in that the determining of the target person's behavior state based on the target person's job object's object image and/or the target person's person voice comprises:
determining target behaviors of the target person based on the historical object images and the historical person voices;
and determining the behavior state of the target person based on the target behavior of the target person and the object image or the person voice.
7. The behavior supervision method according to any one of claims 1 to 5, wherein the issuing of the prompt message based on the behavior state of the target person includes:
and if the times of the target person with abnormal behavior state in the preset time interval exceed a time threshold, and/or the accumulated time of the target person with abnormal behavior state in the preset time interval exceeds a time threshold, sending the prompt message.
8. A behavior supervision device, comprising:
the determining module is used for determining the behavior state of the target person based on the object image of the target person operation object and/or the person voice of the target person;
and the prompt module is used for sending out prompt information based on the behavior state of the target person.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the behaviour supervision method according to any one of claims 1 to 7 when executing the program.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the steps of the behavior supervision method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111272017.9A CN114245068A (en) | 2021-10-29 | 2021-10-29 | Behavior supervision method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111272017.9A CN114245068A (en) | 2021-10-29 | 2021-10-29 | Behavior supervision method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114245068A true CN114245068A (en) | 2022-03-25 |
Family
ID=80743462
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111272017.9A Pending CN114245068A (en) | 2021-10-29 | 2021-10-29 | Behavior supervision method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114245068A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115573851A (en) * | 2022-08-22 | 2023-01-06 | 华能澜沧江水电股份有限公司 | Hydropower equipment safety monitoring method based on Oncall early warning system |
-
2021
- 2021-10-29 CN CN202111272017.9A patent/CN114245068A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115573851A (en) * | 2022-08-22 | 2023-01-06 | 华能澜沧江水电股份有限公司 | Hydropower equipment safety monitoring method based on Oncall early warning system |
| CN115573851B (en) * | 2022-08-22 | 2024-04-26 | 华能澜沧江水电股份有限公司 | Water and electricity equipment safety monitoring method based on Oncall early warning system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sayigh et al. | Facts about signature whistles of bottlenose dolphins, Tursiops truncatus | |
| CN107104887B (en) | A kind of instant message based reminding method, device and its user terminal | |
| CN110024015B (en) | Interactive video teaching method and system | |
| KR20010074705A (en) | Automated language assessment using speech recognition modeling | |
| CN110097283B (en) | Teaching management system and method based on face recognition | |
| CN110533333B (en) | Teaching evaluation method and device | |
| CN111046819A (en) | Behavior recognition processing method and device | |
| Martín-Morató et al. | What is the ground truth? reliability of multi-annotator data for audio tagging | |
| CN109670395A (en) | A kind of student's focus monitoring method based on artificial intelligence | |
| CN115358897B (en) | Student management method, system, terminal and storage medium based on electronic student identity card | |
| CN114298497A (en) | Evaluation method and device for classroom teaching quality of teacher | |
| CN114245068A (en) | Behavior supervision method and device, electronic equipment and storage medium | |
| CN112949546A (en) | Off-duty detection method and device based on artificial intelligence perception of station service state | |
| CN114299617A (en) | Teaching interaction condition identification method, device, equipment and storage medium | |
| CN111901627A (en) | Video processing method and device, storage medium and electronic equipment | |
| CN114445052A (en) | Intelligent education student attendance big data statistical method and system based on block chain | |
| CN111915111A (en) | Online classroom interaction quality evaluation method and device and terminal equipment | |
| CN114021962A (en) | Teaching evaluation method, evaluation device and related equipment and storage medium | |
| CN109933687B (en) | Information processing method and device and electronic equipment | |
| CN106557914B (en) | Alarm clock reminding method and device | |
| CN114724229B (en) | Learning state detection system and method for online education platform | |
| CN111667128A (en) | Teaching quality assessment method, device and system | |
| CN114926758A (en) | Method for analyzing classroom student participation | |
| CN111027358A (en) | Dictation and reading method based on writing progress and electronic equipment | |
| CN114493952A (en) | Education software data processing system and method based on big data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |