CN117333997A - Visual early warning method and device based on image acquisition equipment - Google Patents

Visual early warning method and device based on image acquisition equipment Download PDF

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Publication number
CN117333997A
CN117333997A CN202311416518.9A CN202311416518A CN117333997A CN 117333997 A CN117333997 A CN 117333997A CN 202311416518 A CN202311416518 A CN 202311416518A CN 117333997 A CN117333997 A CN 117333997A
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CN
China
Prior art keywords
risk
scene
image
determining
image acquisition
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Pending
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CN202311416518.9A
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Chinese (zh)
Inventor
唐立
唐杰
陈道远
李昱
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Gree Electric Appliances Inc of Zhuhai
Zhuhai Lianyun Technology Co Ltd
Original Assignee
Gree Electric Appliances Inc of Zhuhai
Zhuhai Lianyun Technology Co Ltd
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Application filed by Gree Electric Appliances Inc of Zhuhai, Zhuhai Lianyun Technology Co Ltd filed Critical Gree Electric Appliances Inc of Zhuhai
Priority to CN202311416518.9A priority Critical patent/CN117333997A/en
Publication of CN117333997A publication Critical patent/CN117333997A/en
Pending legal-status Critical Current

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
    • G08B13/19608—Tracking movement of a target, e.g. by detecting an object predefined as a target, using target direction and or velocity to predict its new position
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
    • G08B13/19606—Discriminating between target movement or movement in an area of interest and other non-signicative movements, e.g. target movements induced by camera shake or movements of pets, falling leaves, rotating fan

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Image Analysis (AREA)

Abstract

The invention discloses a visual early warning method and device based on image acquisition equipment. Wherein the method comprises the following steps: receiving an image frame sent by image acquisition equipment, wherein the image frame is an image acquired by the image acquisition equipment when the image change exists in a monitoring range; identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object; when the target object is determined to be a risk object according to the feature information, determining a risk scene according to the running track, wherein the risk object is determined based on a marking result of the historical image frame, and the risk scene is a scene in which the risk object appears; and generating visual early warning information of the risk scene to prompt the existence of the risk scene in the monitoring range. The invention solves the technical problem that the risk early warning information cannot be visually presented due to the fact that the camera is not linked with the intelligent central control in the related technology.

Description

Visual early warning method and device based on image acquisition equipment
Technical Field
The invention relates to the technical field of intelligent monitoring, in particular to a visual early warning method and device based on image acquisition equipment.
Background
At present, cameras are often only capable of monitoring photographed places for a long time, and a large amount of data can be generated during monitoring, so that the data are difficult to store and analyze.
The existing camera algorithm and intelligent central control algorithm are independently operated, so that resource waste can be caused, complex algorithms cannot be deployed on the camera, and real-time updating can limit application of the complex algorithms.
Aiming at the problem that the camera is not linked with the intelligent central control in the related technology, so that risk early warning information cannot be visually presented, no effective solution is proposed at present.
Disclosure of Invention
The embodiment of the invention provides a visual early warning method and a visual early warning device based on image acquisition equipment, which at least solve the technical problem that a camera is not linked with an intelligent central control in the related art, so that risk early warning information cannot be visually presented.
According to an aspect of the embodiment of the present invention, there is provided a visual early warning method based on an image acquisition device, including: receiving an image frame sent by image acquisition equipment, wherein the image frame is an image acquired by the image acquisition equipment when the image change exists in a monitoring range; identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object; when the target object is determined to be a risk object according to the characteristic information, determining a risk scene according to the running track, wherein the risk object is determined based on a marking result of a historical image frame, and the risk scene is a scene in which the risk object appears; and generating visual early warning information of the risk scene to prompt that the risk scene exists in the monitoring range.
Optionally, before receiving the image sent by the image acquisition device, the method further includes: receiving a connection request sent by the image acquisition equipment, and responding to the connection request to establish communication connection with the image acquisition equipment; and sending a monitoring instruction to the image acquisition equipment so that the image acquisition equipment monitors the monitoring range.
Optionally, determining that the target object is a risk object according to the feature information includes: inputting the feature information into a risk determination model, and processing the feature information by using the risk determination model to obtain a risk level corresponding to the feature information, wherein the risk determination model is obtained by using a plurality of sets of training data through machine learning training, and each set of the plurality of sets of training data comprises: sample feature information and a sample risk level corresponding to the sample feature information; and when the risk level is greater than a preset threshold value, determining that the target object is the risk object.
Optionally, the visual early warning method based on the image acquisition device further comprises the following steps: and optimizing the risk determination model by utilizing the characteristic information and the risk grade to obtain the optimized risk determination model.
Optionally, determining a risk scene according to the running track includes: determining the moving range of the target object according to the moving track; and determining the moving range as the risk scene.
Optionally, before determining the risk scene according to the running track when the target object is determined to be a risk object according to the feature information, the method further includes: acquiring sample characteristic information of a plurality of sample objects moving in the monitoring range; carrying out risk grade marking on the plurality of sample objects according to the sample characteristic information to obtain sample risk grade of each of the plurality of sample objects; the plurality of sample objects and the sample risk level for each of the plurality of sample objects are stored.
Optionally, when determining that the target object is a risk object according to the feature information, determining a risk scene according to the running track further includes: when the target object is determined to be a risk object according to the characteristic information, sending a target image frame corresponding to the target object to a terminal device so as to display the target image frame through the terminal device; acquiring a first feedback result of the terminal equipment on the target image frame; and when the feedback result indicates that the target object is the risk object, determining the risk scene according to the running track.
Optionally, when determining that the target object is a risk object according to the feature information, determining a risk scene according to the running track further includes: sending the risk scene to a terminal device so as to display the risk scene through the terminal device; acquiring a second feedback result of the terminal equipment on the risk scene; and when the mark of the risk scene in the second feedback result is non-risk, determining that the risk scene is a non-risk scene.
Optionally, after determining that the risk scene is a non-risk scene, the visual early warning method based on the image acquisition device further includes: and deleting the image frame.
According to another aspect of the embodiment of the present invention, there is also provided a visual early warning device based on an image acquisition apparatus, including: the first receiving unit is used for receiving image frames sent by the image acquisition equipment, wherein the image frames are images acquired by the image acquisition equipment when the image change exists in a monitoring range; the first acquisition unit is used for identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object; the first determining unit is used for determining a risk scene according to the running track when the target object is determined to be a risk object according to the characteristic information, wherein the risk object is determined based on a marking result of a historical image frame, and the risk scene is a scene in which the risk object appears; the generation unit is used for generating visual early warning information of the risk scene so as to prompt that the risk scene exists in the monitoring range.
Optionally, the visual early warning device based on the image acquisition device further comprises: the second receiving unit is used for receiving a connection request sent by the image acquisition equipment before receiving the image sent by the image acquisition equipment and responding to the connection request to establish communication connection with the image acquisition equipment; and the sending unit is used for sending a monitoring instruction to the image acquisition equipment so that the image acquisition equipment monitors the monitoring range.
Optionally, the first determining unit includes: the first obtaining module is configured to input the feature information into a risk determination model, and process the feature information by using the risk determination model to obtain a risk level corresponding to the feature information, where the risk determination model is obtained by using multiple sets of training data through machine learning training, and each set of the multiple sets of training data includes: sample feature information and a sample risk level corresponding to the sample feature information; and the first determining module is used for determining that the target object is the risk object when the risk level is greater than a preset threshold value.
Optionally, the visual early warning device based on the image acquisition device further comprises: and the second acquisition module is used for optimizing the risk determination model by utilizing the characteristic information and the risk grade to obtain the optimized risk determination model.
Optionally, the first determining unit includes: the second determining module is used for determining the moving range of the target object according to the moving track; and the third determining module is used for determining the moving range as the risk scene.
Optionally, the visual early warning device based on the image acquisition device further comprises: the second acquisition unit is used for acquiring sample characteristic information of a plurality of sample objects moving in the monitoring range before determining a risk scene according to the running track when the target object is determined to be a risk object according to the characteristic information; the second determining unit is used for marking the risk grades of the plurality of sample objects according to the sample characteristic information to obtain the sample risk grade of each sample object; and the storage unit is used for storing the plurality of sample objects and the sample risk level of each sample object.
Optionally, the first determining unit further includes: the display module is used for sending the target image frame corresponding to the target object to a terminal device when the target object is determined to be a risk object according to the characteristic information so as to display the target image frame through the terminal device; a third obtaining module, configured to obtain a first feedback result of the terminal device on the target image frame; and the fourth determining module is used for determining the risk scene according to the running track when the feedback result indicates that the target object is the risk object.
Optionally, the visual early warning device based on the image acquisition device further comprises: the display unit is used for sending the risk scene to the terminal equipment after determining the risk scene according to the running track when the target object is determined to be the risk object according to the characteristic information so as to display the risk scene through the terminal equipment; the third acquisition unit is used for acquiring a second feedback result of the terminal equipment on the risk scene; and the second determining unit is used for determining that the risk scene is a non-risk scene when the mark of the risk scene in the second feedback result is a non-risk.
Optionally, the visual early warning device based on the image acquisition device further comprises: and the deleting unit is used for deleting the image frame after the risk scene is determined to be a non-risk scene.
According to another aspect of the embodiment of the invention, a visual early-warning system based on the image acquisition device is further provided, and the visual early-warning system based on the image acquisition device uses any one of the visual early-warning methods based on the image acquisition device.
According to another aspect of the embodiment of the present invention, there is also provided a computer readable storage medium, where the computer readable storage medium includes a stored program, where the program executes any one of the above-mentioned visual early warning method based on an image capturing device.
According to another aspect of the embodiment of the present invention, there is further provided a processor, where the processor is configured to run a program, where any one of the above-mentioned visual early warning methods based on an image capturing device is executed when the program runs.
In the embodiment of the invention, an image frame sent by image acquisition equipment is received, wherein the image frame is an image acquired by the image acquisition equipment when the image change exists in a monitoring range; identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object; when the target object is determined to be a risk object according to the feature information, determining a risk scene according to the running track, wherein the risk object is determined based on a marking result of the historical image frame, and the risk scene is a scene in which the risk object appears; and generating visual early warning information of the risk scene to prompt the existence of the risk scene in the monitoring range. Through the technical scheme, the purposes of linking the camera with the intelligent central control, transmitting the acquired image frames to the intelligent central control by the camera, analyzing the image frames according to the stored judgment logic and performing visual early warning when the analysis result shows that a risk scene exists are achieved, the technical effect of visually displaying the monitored risk scene is achieved, the early warning of risks is more visual, a user can make risk treatment countermeasures in time conveniently, and the technical problem that the camera is not linked with the intelligent central control in the related technology, so that the risk early warning information cannot be visually presented is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a hardware structure block diagram of a mobile terminal of a visual early warning method based on an image acquisition device according to an embodiment of the present invention;
FIG. 2 is a flow chart of an image acquisition device-based visual early warning method according to an embodiment of the invention;
FIG. 3 is a flow chart of an alternative image acquisition device-based visual pre-warning method in accordance with an embodiment of the present invention;
fig. 4 is a schematic diagram of a visual early warning device based on an image acquisition apparatus according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As described in the background art, the related art does not link the camera with the intelligent central control, so that risk early warning information cannot be visually presented. Aiming at the defects, the embodiment of the invention provides a visual early warning method and device based on image acquisition equipment.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
The method embodiments provided in the embodiments of the present invention may be performed in a mobile terminal, a computer terminal or similar computing device. Taking the operation on a mobile terminal as an example, fig. 1 is a hardware structure block diagram of the mobile terminal of a visual early warning method based on an image acquisition device according to an embodiment of the present invention. As shown in fig. 1, a mobile terminal may include one or more (only one is shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 for communication functions and an input-output device 108. It will be appreciated by those skilled in the art that the structure shown in fig. 1 is merely illustrative and not limiting of the structure of the mobile terminal described above. For example, the mobile terminal may also include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to a visual early warning method based on an image capturing device in an embodiment of the present invention, and the processor 102 executes the computer program stored in the memory 104, thereby performing various functional applications and data processing, that is, implementing the method described above. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, which may be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, simply referred to as NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is configured to communicate with the internet wirelessly.
According to an embodiment of the present invention, there is provided a method embodiment of a visual early warning method based on an image capturing device, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different from that herein.
Fig. 2 is a flowchart of a visual early warning method based on an image acquisition device according to an embodiment of the present invention, as shown in fig. 2, the method includes the steps of:
step S202, receiving an image frame sent by the image acquisition device, wherein the image frame is an image acquired by the image acquisition device when the image acquisition device detects that the picture changes in the monitoring range.
Alternatively, the image capturing device includes, but is not limited to, a camera, a scanner, an infrared sensor, and the like, which can capture image information.
Optionally, the image frame refers to an image in the collected monitoring range, where the image frame may be one frame or multiple frames, and in the case that the image frame is multiple frames, the multiple frames of image frames may form a video frame.
In this embodiment, the image capturing apparatus may monitor the monitoring range in real time, and only when the screen change is monitored, the change screen of the monitoring range may be captured, so that the storage space of the image capturing apparatus may be saved.
According to the above embodiment of the present invention, before the step S202, that is, before receiving the image sent by the image capturing device, the method further includes: receiving a connection request sent by image acquisition equipment, and responding to the connection request to establish communication connection with the image acquisition equipment; and sending a monitoring instruction to the image acquisition equipment so that the image acquisition equipment monitors the monitoring range.
In this embodiment, the intelligent central control may receive a connection request sent by the image acquisition device, and respond to the connection request to establish a communication connection with the image acquisition device, so that linkage between the intelligent central control and the image acquisition device may be implemented, and further data transmission, interaction, and the like may be implemented.
After the intelligent central control establishes communication connection with the image acquisition equipment in the mode, a monitoring instruction can be sent to the image acquisition equipment so as to monitor the monitoring range by using the image acquisition equipment, so that effective management of the monitoring range is realized, and the safety of the monitoring range is improved.
The above embodiment of the present invention will be explained with reference to fig. 3, and fig. 3 is a flowchart of an alternative visual early warning method based on an image capturing device according to an embodiment of the present invention. As shown in fig. 3, the above-described embodiment of the present invention is exemplified by taking a camera as an image capturing apparatus. Firstly, a camera arranged in a target monitoring range is linked with an intelligent central control, and communication connection between the camera and the intelligent central control is established; then, in the process of monitoring by the camera, if the video picture is detected to change, if a person suddenly appears in the picture, the camera records the video with the changed picture and transmits the video to the intelligent central control. The change of the video picture can be that no person exists in the original video picture, a person appears in the original video picture suddenly, a new person appears in the picture suddenly, or the action of the person in the original video picture is obviously changed compared with the previous action.
Step S204, the image frames are identified, and feature information and running tracks of the target object in the image frames are obtained, wherein the feature information is used for representing morphological features of the target object.
Optionally, the characteristic information refers to a topographical feature of the target object, which may include, but is not limited to: characteristic information such as clothing, appearance, prominence marks and the like.
Alternatively, the moving track may refer to a moving direction of the target object.
As shown in fig. 3, when the camera monitors that the shot picture changes, the changed picture is transmitted to the intelligent central control for processing, the intelligent central control receives the picture transmitted by the camera, and identifies and marks people and objects in the picture, and records the motion trail of the people and objects.
In step S206, when the target object is determined to be a risk object according to the feature information, a risk scene is determined according to the running track, where the risk object is an object determined based on the marking result of the historical image frame, and the risk scene is a scene in which the risk object appears.
Optionally, the risk object refers to an object that is determined based on a marking result of the historical image frame and is identified as having a certain risk.
For example, whether the target object is a risk object may be determined according to the personal information of the target object recorded in the feature information, for example, the personal information of the target object may be matched with the marked historical image frames to determine whether the target object is a risk object. When the matching result indicates that the personal information of the target object exists in the historical image frame and is marked as a risk object, the target object is determined to be the risk object.
And then determining the moving direction of the risk object according to the moving track of the risk object, and determining a preset area corresponding to the predicted moving direction of the risk object as a risk scene.
According to the above embodiment of the present invention, for how to determine that the target object is a risk object according to the feature information, the method includes: inputting the feature information into a risk determination model to process the feature information by using the risk determination model to obtain a risk level corresponding to the feature information, wherein the risk determination model is obtained by using a plurality of sets of training data through machine learning training, and each set of the plurality of sets of training data comprises: sample feature information and a sample risk level corresponding to the sample feature information; and when the risk level is greater than a preset threshold value, determining the target object as a risk object.
Optionally, the sample feature information refers to feature information of the target object acquired according to the historical image frames.
Optionally, the sample risk level is obtained by dividing the risk level according to multiple sets of feature information, and may include, but is not limited to, a sample risk level such as a trusted risk, a suspected risk, a high risk, and the like.
Optionally, the predetermined threshold is that the determined risk level exceeds a certain range.
For example, a confidence score (percentile) may be based on the user's characteristic information of the target object, which is considered risky when the confidence score is below a certain value (e.g., below 60 points).
In the above embodiment of the present invention, in order to more accurately use the risk determination model to determine the risk level corresponding to the feature information, that is, in order to improve the accuracy of the risk determination model, the visual early warning method based on the image capturing device may further include: and optimizing the risk determination model by utilizing the characteristic information and the risk level to obtain an optimized risk determination model.
The risk determination model can be optimized through a large amount of sample data, so that the risk level determined according to the characteristic information is more accurate.
According to the above embodiment of the present invention, for how to determine a risk scenario according to a running track, the method includes: determining the moving range of the target object according to the moving track; and determining the moving range as a risk scene.
For example, when it is determined that the person in the screen is at risk, the movement track of the person is acquired by the camera, so that the movement range of the person at risk is determined, and the range can be determined to be at risk.
According to the above embodiment of the present invention, before the step S206, that is, before determining that the target object is a risk object according to the feature information, the method further includes: acquiring sample characteristic information of a plurality of sample objects moving in a monitoring range; carrying out risk grade marking on a plurality of sample objects according to the sample characteristic information to obtain sample risk grade of each of the plurality of sample objects; a plurality of sample objects and a sample risk level for each of the plurality of sample objects are stored.
For example, when a person appears in the same scene at a plurality of different times, the person can be considered to be at risk, the feature information can be marked as risk level of the person being a suspected risk person, then help can be requested to the user to further determine whether the person is a risk person, and then the risk level of the person is determined to be a trusted person or a risk person again according to the judgment result of the user.
In addition, the user can mark the sensitive area according to the video picture acquired by the camera in the intelligent central control in advance, can mark the person and the object recorded before the camera, and can mark the person and the object as family personnel, trusted personnel and risk personnel; if a person is present in the user marked area, or a user marked risk or person is present, the risk level may be initially considered a suspected risk person.
According to the above embodiment of the present invention, in the step S206, when determining that the target object is a risk object according to the feature information, determining a risk scene according to the running track further includes: when the target object is determined to be a risk object according to the feature information, sending a target image frame corresponding to the target object to the terminal equipment so as to display the target image frame through the terminal equipment; acquiring a first feedback result of the terminal equipment on the target image frame; and when the feedback result indicates that the target object is a risk object, determining a risk scene according to the running track.
In this embodiment, in order to determine whether the target object is a risk object more accurately, after the target object is primarily determined to be the risk object in the above manner, an image frame of the target object may be sent to a terminal device of a user, and the image frame where the target object is located is presented through the terminal device, and the user determines whether the target object is the risk object again; in this way, before determining the risk scene, it is possible to verify whether the target object is a risk object, thereby improving the accuracy of the judgment.
According to the above embodiment of the present invention, after the step S206, that is, when determining that the target object is a risk object according to the feature information, determining a risk scene according to the running track further includes: the risk scene is sent to the terminal equipment, so that the risk scene is displayed through the terminal equipment; acquiring a second feedback result of the terminal equipment on the risk scene; and when the marks of the risk scenes in the second feedback result are non-risk, determining that the risk scenes are non-risk scenes.
For example, if the intelligent central control directly judges that the data is a risk scene after analyzing the data, the intelligent central control displays the situation to inform a user and stores related data; or after the user judges that the risk scene is judged, the data of the risk scene is recorded and the judging conditions are stored so as to be convenient to view and analyze later and recognize the risk scene.
As shown in fig. 3, after the intelligent central control analyzes the data, if the data is judged to be a risk scene, the processing result is displayed to the user, the user is informed that the scene is a risk scene, if the data is a non-risk scene, the data is informed to the user through a visual interface, and then the user judges.
Step S208, generating visual early warning information of the risk scene to prompt that the risk scene exists in the monitoring range.
Optionally, the visual early warning information includes, but is not limited to: highlighting of video pictures, voice broadcasting reminding and the like.
For example, the intelligent central control can record and display the scene triggering the camera, if the user marks the scene as a risk, the intelligent central control and the camera can record related judgment logic, the intelligent central control can analyze the relevance between the scene and the historical information, for example, a person is found to appear in a plurality of scenes at different times, and the scene is marked to remind the user; meanwhile, the intelligent central control can also collect data of a plurality of cameras, and generate a complete moving track of a specific object so as to be convenient for a user to judge, so that the intelligent central control is suitable for more complex scenes, can visually display the conditions and the data, and is convenient for the user to judge.
According to the embodiment of the invention, after determining that the risk scene is a non-risk scene, the visual early warning method based on the image acquisition device further comprises the following steps: the image frames are deleted.
For example, if the intelligent central control determines that the data is a non-risk scene according to the data, and the user also considers that the data is not at risk after the data is determined, the relevant data can be deleted, so that the storage space is saved.
According to the technical scheme provided by the embodiment of the invention, the data of the camera can be transmitted to the intelligent central control for processing, the customized interaction of the user and the identification and comparison of the object are realized through the intelligent central control, the key data are stored, and the unnecessary data can be deleted in time, so that the storage space is saved.
According to the technical scheme provided by the embodiment of the invention, the image frames sent by the image acquisition equipment are received, wherein the image frames are images acquired by the image acquisition equipment when the image change exists in the monitoring range; identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object; when the target object is determined to be a risk object according to the feature information, determining a risk scene according to the running track, wherein the risk object is determined based on a marking result of the historical image frame, and the risk scene is a scene in which the risk object appears; the method comprises the steps of generating visual early warning information of a risk scene to prompt the existence of the risk scene in a monitoring range, enabling a camera to be linked with an intelligent central controller, enabling the camera to transmit collected image frames to the intelligent central controller, enabling the intelligent central controller to analyze the image frames according to stored judgment logic, and performing visual early warning when an analysis result shows that the risk scene exists, so that the technical effect of visually displaying the monitored risk scene is achieved, enabling early warning of risks to be more visual, and enabling a user to make risk processing countermeasures in time.
Therefore, by the technical scheme provided by the embodiment of the invention, the technical problem that the risk early warning information cannot be visually presented due to the fact that the camera is not linked with the intelligent central control in the related technology is solved.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method described in the embodiments of the present application.
According to an embodiment of the present invention, there is further provided an image capturing device-based visual early warning apparatus for implementing the image capturing device-based visual early warning method, and fig. 4 is a schematic diagram of the image capturing device-based visual early warning apparatus according to an embodiment of the present invention, as shown in fig. 4, where the apparatus includes: the first receiving unit 41, the first acquiring unit 43, the first determining unit 45, the generating unit 47. The visual early warning device based on the image acquisition equipment is described in detail below.
The first receiving unit 41 is configured to receive an image frame sent by the image capturing device, where the image frame is an image captured by the image capturing device when a frame change exists in the monitoring range.
The first obtaining unit 43 is configured to identify an image frame, and obtain feature information and a running track of a target object in the image frame, where the feature information is used to characterize a morphological feature of the target object.
The first determining unit 45 is configured to determine, when it is determined that the target object is a risk object according to the feature information, a risk scene according to the running track, where the risk object is an object determined based on a marking result of the historical image frame, and the risk scene is a scene in which the risk object appears.
The generating unit 47 is configured to generate visual early warning information of the risk scene to prompt that the risk scene exists in the monitoring range.
Here, the first receiving unit 41, the first obtaining unit 43, the first determining unit 45, and the generating unit 47 correspond to steps S202 to S208 in the above embodiments, and the four units are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in the above embodiments.
As can be seen from the above, in the solution described in the foregoing embodiment of the present invention, the first receiving unit may be used to receive an image frame sent by the image capturing device, where the image frame is an image captured by the image capturing device when a frame change exists in a monitoring range; then, a first acquisition unit is utilized to identify the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing the morphological features of the target object; then, when the target object is determined to be a risk object according to the characteristic information, determining a risk scene according to the running track, wherein the risk object is determined based on a marking result of the historical image frame, and the risk scene is a scene in which the risk object appears; finally, the generation unit is utilized to generate visual early warning information of the risk scene so as to prompt the existence of the risk scene in the monitoring range, the camera is linked with the intelligent central control, the camera transmits the acquired image frames to the intelligent central control, the intelligent central control analyzes the image frames according to stored judgment logic, and when the analysis result shows that the risk scene exists, the purpose of visual early warning is achieved, the technical effect of visual display of the monitored risk scene is achieved, the early warning of the risk is more visual, and a user can conveniently and timely make risk processing countermeasures.
Therefore, by the technical scheme provided by the embodiment of the invention, the technical problem that the risk early warning information cannot be visually presented due to the fact that the camera is not linked with the intelligent central control in the related technology is solved.
Optionally, the visual early warning device based on the image acquisition device further comprises: the second receiving unit is used for receiving a connection request sent by the image acquisition equipment before receiving the image sent by the image acquisition equipment and responding to the connection request to establish communication connection with the image acquisition equipment; and the sending unit is used for sending a monitoring instruction to the image acquisition equipment so that the image acquisition equipment monitors the monitoring range.
Optionally, the first determining unit includes: the first obtaining module is used for inputting the feature information into the risk determination model so as to process the feature information by using the risk determination model to obtain a risk level corresponding to the feature information, wherein the risk determination model is obtained by using a plurality of sets of training data through machine learning training, and each set of the plurality of sets of training data comprises: sample feature information and a sample risk level corresponding to the sample feature information; and the first determining module is used for determining that the target object is a risk object when the risk level is greater than a preset threshold value.
Optionally, the visual early warning device based on the image acquisition device further comprises: and the second acquisition module is used for optimizing the risk determination model by utilizing the characteristic information and the risk level to obtain an optimized risk determination model.
Optionally, the first determining unit includes: the second determining module is used for determining the moving range of the target object according to the moving track; and the third determining module is used for determining the moving range as a risk scene.
Optionally, the visual early warning device based on the image acquisition device further comprises: the second acquisition unit is used for acquiring sample characteristic information of a plurality of sample objects moving in the monitoring range before determining a risk scene according to the running track when the target object is determined to be a risk object according to the characteristic information; the second determining unit is used for marking the risk level of the plurality of sample objects according to the sample characteristic information to obtain the sample risk level of each of the plurality of sample objects; and the storage unit is used for storing the plurality of sample objects and the sample risk level of each of the plurality of sample objects.
Optionally, the first determining unit further includes: the display module is used for sending the target image frame corresponding to the target object to the terminal equipment when the target object is determined to be a risk object according to the characteristic information so as to display the target image frame through the terminal equipment; the third acquisition module is used for acquiring a first feedback result of the terminal equipment on the target image frame; and the fourth determining module is used for determining a risk scene according to the running track when the feedback result indicates that the target object is a risk object.
Optionally, the visual early warning device based on the image acquisition device further comprises: the display unit is used for sending the risk scene to the terminal equipment after determining the risk scene according to the running track when determining that the target object is the risk object according to the characteristic information so as to display the risk scene through the terminal equipment; the third acquisition unit is used for acquiring a second feedback result of the terminal equipment on the risk scene; and the second determining unit is used for determining that the risk scene is a non-risk scene when the mark of the risk scene in the second feedback result is a non-risk.
Optionally, the visual early warning device based on the image acquisition device further comprises: and the deleting unit is used for deleting the image frames after determining the risk scene as the non-risk scene.
According to another aspect of the embodiment of the invention, there is further provided an image acquisition device-based visual early warning system, which uses any one of the above-mentioned image acquisition device-based visual early warning methods.
According to another aspect of the embodiment of the present invention, there is further provided a computer readable storage medium, wherein the computer readable storage medium includes a stored program, and the program executes any one of the above visual early warning methods based on an image capturing device.
Alternatively, in the present embodiment, the above-described computer-readable storage medium may be located in any one of a group of computer terminals in a computer network, or in any one of a group of communication devices.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: receiving an image frame sent by image acquisition equipment, wherein the image frame is an image acquired by the image acquisition equipment when the image change exists in a monitoring range; identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object; when the target object is determined to be a risk object according to the feature information, determining a risk scene according to the running track, wherein the risk object is determined based on a marking result of the historical image frame, and the risk scene is a scene in which the risk object appears; and generating visual early warning information of the risk scene to prompt the existence of the risk scene in the monitoring range.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: receiving a connection request sent by image acquisition equipment, and responding to the connection request to establish communication connection with the image acquisition equipment; and sending a monitoring instruction to the image acquisition equipment so that the image acquisition equipment monitors the monitoring range.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: inputting the feature information into a risk determination model to process the feature information by using the risk determination model to obtain a risk level corresponding to the feature information, wherein the risk determination model is obtained by using a plurality of sets of training data through machine learning training, and each set of the plurality of sets of training data comprises: sample feature information and a sample risk level corresponding to the sample feature information; and when the risk level is greater than a preset threshold value, determining the target object as a risk object.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: and optimizing the risk determination model by utilizing the characteristic information and the risk level to obtain an optimized risk determination model.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: determining the moving range of the target object according to the moving track; and determining the moving range as a risk scene.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: acquiring sample characteristic information of a plurality of sample objects moving in a monitoring range; carrying out risk grade marking on a plurality of sample objects according to the sample characteristic information to obtain sample risk grade of each of the plurality of sample objects; a plurality of sample objects and a sample risk level for each of the plurality of sample objects are stored.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: when the target object is determined to be a risk object according to the feature information, sending a target image frame corresponding to the target object to the terminal equipment so as to display the target image frame through the terminal equipment; acquiring a first feedback result of the terminal equipment on the target image frame; and when the feedback result indicates that the target object is a risk object, determining a risk scene according to the running track.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: the risk scene is sent to the terminal equipment, so that the risk scene is displayed through the terminal equipment; acquiring a second feedback result of the terminal equipment on the risk scene; and when the marks of the risk scenes in the second feedback result are non-risk, determining that the risk scenes are non-risk scenes.
Optionally, in the present embodiment, the computer readable storage medium is configured to store program code for performing the steps of: the image frames are deleted.
According to another aspect of the embodiment of the present invention, there is further provided a processor, where the processor is configured to run a program, where the program executes any one of the above-mentioned visual early warning methods based on an image capturing device.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform 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 Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims (10)

1. The visual early warning method based on the image acquisition equipment is characterized by comprising the following steps of:
receiving an image frame sent by image acquisition equipment, wherein the image frame is an image acquired by the image acquisition equipment when the image change exists in a monitoring range;
identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object;
when the target object is determined to be a risk object according to the characteristic information, determining a risk scene according to the running track, wherein the risk object is determined based on a marking result of a historical image frame, and the risk scene is a scene in which the risk object appears;
and generating visual early warning information of the risk scene to prompt that the risk scene exists in the monitoring range.
2. The image capturing device-based visual pre-warning method of claim 1, further comprising, prior to receiving the image transmitted by the image capturing device:
receiving a connection request sent by the image acquisition equipment, and responding to the connection request to establish communication connection with the image acquisition equipment;
and sending a monitoring instruction to the image acquisition equipment so that the image acquisition equipment monitors the monitoring range.
3. The visual early warning method based on the image acquisition device according to claim 1, wherein determining that the target object is a risk object according to the feature information comprises:
inputting the feature information into a risk determination model, and processing the feature information by using the risk determination model to obtain a risk level corresponding to the feature information, wherein the risk determination model is obtained by using a plurality of sets of training data through machine learning training, and each set of the plurality of sets of training data comprises: sample feature information and a sample risk level corresponding to the sample feature information;
and when the risk level is greater than a preset threshold value, determining that the target object is the risk object.
4. The visual early warning method based on the image acquisition device according to claim 3, further comprising:
and optimizing the risk determination model by utilizing the characteristic information and the risk grade to obtain the optimized risk determination model.
5. The visual early warning method based on the image acquisition device according to claim 1, wherein determining a risk scene according to the running track comprises:
determining the moving range of the target object according to the moving track;
and determining the moving range as the risk scene.
6. The visual early warning method based on an image acquisition device according to claim 1, wherein when determining that the target object is a risk object according to the feature information, before determining a risk scene according to the running track, further comprises:
acquiring sample characteristic information of a plurality of sample objects moving in the monitoring range;
carrying out risk grade marking on the plurality of sample objects according to the sample characteristic information to obtain sample risk grade of each of the plurality of sample objects;
the plurality of sample objects and the sample risk level for each of the plurality of sample objects are stored.
7. The visual early warning method based on an image acquisition device according to claim 1, wherein when determining that the target object is a risk object according to the feature information, determining a risk scene according to the running track, further comprises:
when the target object is determined to be a risk object according to the characteristic information, sending a target image frame corresponding to the target object to a terminal device so as to display the target image frame through the terminal device;
acquiring a first feedback result of the terminal equipment on the target image frame;
and when the feedback result indicates that the target object is the risk object, determining the risk scene according to the running track.
8. The visual early warning method based on an image acquisition device according to claim 1, wherein when determining that the target object is a risk object according to the feature information, after determining a risk scene according to the moving track, further comprises:
sending the risk scene to a terminal device so as to display the risk scene through the terminal device;
acquiring a second feedback result of the terminal equipment on the risk scene;
And when the mark of the risk scene in the second feedback result is non-risk, determining that the risk scene is a non-risk scene.
9. The visual early warning method based on an image acquisition device according to claim 8, further comprising, after determining that the risk scene is a non-risk scene: and deleting the image frame.
10. Visual early warning device based on image acquisition equipment, characterized by comprising:
the first receiving unit is used for receiving image frames sent by the image acquisition equipment, wherein the image frames are images acquired by the image acquisition equipment when the image change exists in a monitoring range;
the first acquisition unit is used for identifying the image frame to obtain feature information and a running track of a target object in the image frame, wherein the feature information is used for representing morphological features of the target object;
the first determining unit is used for determining a risk scene according to the running track when the target object is determined to be a risk object according to the characteristic information, wherein the risk object is determined based on a marking result of a historical image frame, and the risk scene is a scene in which the risk object appears;
The generation unit is used for generating visual early warning information of the risk scene so as to prompt that the risk scene exists in the monitoring range.
CN202311416518.9A 2023-10-27 2023-10-27 Visual early warning method and device based on image acquisition equipment Pending CN117333997A (en)

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