CN112906552A - Inspection method and device based on computer vision and electronic equipment - Google Patents
Inspection method and device based on computer vision and electronic equipment Download PDFInfo
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Abstract
The invention relates to the technical field of computers, in particular to a routing inspection method, a routing inspection device and electronic equipment based on computer vision, wherein the routing inspection method comprises the following steps: acquiring camera point location information and an intelligent rule of a camera; reading a video stream according to the camera point location information; loading a video stream processing model corresponding to the intelligent rule, and carrying out image detection on the video stream based on the video stream processing model; and obtaining effective routing inspection information based on the image detection result. The method and the system can realize unified management on the model, reduce labor cost, and can configure the intelligent rules in a unified way through the configuration page, thereby more effectively screening out the required inspection information and giving early warning to the staff in time.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a routing inspection method and device based on computer vision and electronic equipment.
Background
In the practical application of the current government field, various visual components are required to be combined to perform behavior analysis such as target detection and the like with a field camera, but as the number of routing inspection components is large after the routing inspection components are refined, the models are difficult to manage in a unified manner, and a large amount of labor cost is required to be consumed to guarantee operation and maintenance; the number of the field cameras is too large, each camera needs to be configured with a set of independent intelligent rules, a general configuration interface is lacked, and unified management cannot be realized; the visual component detects a plurality of pieces of useless information and lacks proper rules for filtering the information, thereby interfering with the inspection result of the site.
Disclosure of Invention
The invention provides a routing inspection method, a device and electronic equipment based on computer vision, which are used for more effectively screening out required routing inspection information and timely giving an early warning to workers.
An embodiment of the present specification provides a routing inspection method based on computer vision, including:
acquiring camera point location information and an intelligent rule of a camera;
reading a video stream according to the camera point location information;
loading a video stream processing model corresponding to the intelligent rule, and carrying out image detection on the video stream based on the video stream processing model;
and obtaining effective routing inspection information based on the image detection result.
Preferably, the method further comprises the following steps:
drawing the result of the image detection to the image to obtain a latest image;
and displaying the latest image on a display page.
Preferably, the image detection on the video stream based on the video stream processing model includes:
performing target detection on the image in the video stream based on a target monitoring model, wherein the target detection comprises human body tracking, workcard detection, ground rubbish detection, appearance detection, behavior detection and screen state detection;
analyzing and predicting the real-time people flow quantity in the video flow based on a people flow prediction model;
performing face recognition on the personnel in the video stream based on a face recognition model;
the video stream processing model comprises a target monitoring model, a people stream prediction model and a face recognition model.
Preferably, the performing face recognition on the person in the video stream based on the face recognition model includes:
matching the human body detection box with the faces of the persons in the video stream based on a Hungarian algorithm;
calculating the overlapping rate of the matched human body detection frame and the human face;
and calculating the distance between the matched human body detection frame and the human face.
Preferably, the obtaining of the effective inspection information based on the result of the image detection includes:
filtering the detection result by a preset frame number, and performing duplicate removal on the filtered detection result;
and carrying out personnel information fusion on the images in the video stream to obtain effective routing inspection information.
Preferably, the person information includes: worker's cards, hair, human face, clothing, post.
The embodiment of this specification still provides an inspection device based on computer vision, its characterized in that includes:
the information acquisition module is used for acquiring the point location information of the camera and the intelligent rule of the camera;
the video stream reading module reads a video stream according to the camera point location information;
the image detection module loads a video stream processing model corresponding to the intelligent rule and carries out image detection on the video stream based on the video stream processing model;
and the result acquisition module is used for acquiring effective routing inspection information based on the image detection result.
Preferably, the method further comprises the following steps:
drawing the result of the image detection to the image to obtain a latest image;
and displaying the latest image on a display page.
Preferably, the image detection on the video stream based on the video stream processing model includes:
performing target detection on the image in the video stream based on a target monitoring model, wherein the target detection comprises human body tracking, workcard detection, ground rubbish detection, appearance detection, behavior detection and screen state detection;
analyzing and predicting the real-time people flow quantity in the video flow based on a people flow prediction model;
performing face recognition on the personnel in the video stream based on a face recognition model;
the video stream processing model comprises a target monitoring model, a people stream prediction model and a face recognition model.
Preferably, the performing face recognition on the person in the video stream based on the face recognition model includes:
matching the human body detection box with the faces of the persons in the video stream based on a Hungarian algorithm;
calculating the overlapping rate of the matched human body detection frame and the human face;
and calculating the distance between the matched human body detection frame and the human face.
Preferably, the obtaining of the effective inspection information based on the result of the image detection includes:
filtering the detection result by a preset frame number, and performing duplicate removal on the filtered detection result;
and carrying out personnel information fusion on the images in the video stream to obtain effective routing inspection information.
Preferably, the person information includes: worker's cards, hair, human face, clothing, post.
An electronic device, wherein the electronic device comprises:
a processor and a memory storing computer executable instructions that, when executed, cause the processor to perform the method of any of the above.
A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of the above.
The beneficial effects are that:
the method and the system can realize unified management on the model, reduce labor cost, and can configure the intelligent rules in a unified way through the configuration page, thereby more effectively screening out the required inspection information and giving early warning to the staff in time.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic diagram illustrating a computer vision-based polling method according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an inspection device based on computer vision according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.
Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.
In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.
The diagrams depicted in the figures are exemplary only, and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order depicted. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Referring to fig. 1, a schematic diagram of a computer vision-based polling method provided for an embodiment of the present specification includes:
s101: acquiring camera point location information and an intelligent rule of a camera;
in a preferred embodiment of the present invention, the point location information of the camera, the video stream information, and the intelligent rule on the camera are configured through the configuration page of the platform, and then the application program obtains the point location information of the camera and the intelligent rule configured on the camera by reading the configuration information.
S102: reading a video stream according to the camera point location information;
in a preferred embodiment of the present invention, the application program obtains the corresponding video stream through the point location information of the camera, and further reads the image in the video stream.
S103: loading a video stream processing model corresponding to the intelligent rule, and carrying out image detection on the video stream based on the video stream processing model;
in the preferred embodiment of the present invention, the corresponding video stream processing model is loaded according to the intelligent rule, for example, when the target detection is needed, the target detection model is loaded; when people flow prediction is needed, loading a people flow prediction model; and when the face recognition is required, loading the face recognition model.
The target monitoring model carries out target detection on the images in the video stream, wherein the target detection comprises human body tracking, worker brand detection, ground rubbish detection, appearance detection, behavior detection and screen state detection; the people flow prediction model is used for analyzing and predicting the real-time people flow quantity in the video flow so as to obtain the condition of the people flow quantity in a certain time period, and the face recognition model is used for carrying out face recognition on people in the video flow and can be used for recognizing staff of a company or people in other fields.
S104: and obtaining effective routing inspection information based on the image detection result.
In a preferred embodiment of the invention, information filtering and duplicate removal are carried out on the image detection result, information precision is realized, errors are reduced, then final inspection information is obtained, and if violation of personnel in the monitoring area exists in the inspection information or the flow of the personnel is too large, an alarm is given to inform a manager to carry out corresponding management, personnel evacuation and the like.
Further, still include:
drawing the result of the image detection to the image to obtain a latest image;
and displaying the latest image on a display page.
In the preferred embodiment of the invention, the result of the image detection is drawn to the image for detection in the video stream, and then the image is displayed on an application program display page, so that the accident or the working state of personnel in the monitoring area can be intuitively reflected.
Further, the image detection of the video stream based on the video stream processing model includes:
performing target detection on the image in the video stream based on a target monitoring model, wherein the target detection comprises human body tracking, workcard detection, ground rubbish detection, appearance detection, behavior detection and screen state detection;
analyzing and predicting the real-time people flow quantity in the video flow based on a people flow prediction model;
performing face recognition on the personnel in the video stream based on a face recognition model;
the video stream processing model comprises a target monitoring model, a people stream prediction model and a face recognition model.
In a preferred embodiment of the present invention, model functions to be configured are configured in an application program through a platform interface, each model function is composed of a weight file and a configuration file, the functions corresponding to the model are realized by uploading the weight file and the configuration file corresponding to the model, and the configuration information includes, but is not limited to, a model name, a detection result picture size, a confidence level, a region overlapping threshold value, and a prediction result tag name. The target detection model can realize human body tracking, workmanship board detection, ground garbage detection, appearance detection, behavior detection, screen state detection and the like, the people flow prediction model can realize people flow in a monitoring area detected within a certain time, and the face recognition module can recognize faces within a certain time.
Further, the performing face recognition on the person in the video stream based on the face recognition model includes:
matching the human body detection box with the faces of the persons in the video stream based on a Hungarian algorithm;
calculating the overlapping rate of the matched human body detection frame and the human face;
and calculating the distance between the matched human body detection frame and the human face.
In the preferred embodiment of the invention, a Hungarian algorithm is adopted to match the human body detection box with the human faces of the personnel in the video stream, the overlapping rate and the distance between the human body detection box and the human faces are calculated, the matching degree is confirmed according to the calculation result, and the matching effect is improved.
Further, the obtaining of the effective inspection information based on the result of the image detection includes:
filtering the detection result by a preset frame number, and performing duplicate removal on the filtered detection result;
and carrying out personnel information fusion on the images in the video stream to obtain effective routing inspection information.
In a preferred embodiment of the invention, a processing mechanism with 3 frames per second is arranged to filter the detection result to obtain the filtered detection result, then the overlapped detection result is removed, the detection result is further refined, and then personnel information fusion is carried out, such as a worker card, hair, clothing and the like, can be carried out, so that which personnel the violation detection belongs to is judged, and whether the staff is on duty or not can be judged and displayed to a foreground system in real time; and whether the people flow information exceeds a certain number of people can be judged, if so, violation is caused, and an alarm is given to inform workers of dredging the site.
Further, the personnel information includes: worker's cards, hair, human face, clothing, post.
The method and the system can realize unified management on the model, reduce labor cost, and can configure the intelligent rules in a unified way through the configuration page, thereby more effectively screening out the required inspection information and giving early warning to the staff in time.
Fig. 2 is a schematic structural diagram of an inspection device based on computer vision according to an embodiment of the present disclosure, including:
the information acquisition module 201 is used for acquiring point location information of the camera and intelligent rules of the camera;
in a preferred embodiment of the present invention, the point location information of the camera, the video stream information, and the intelligent rule on the camera are configured through the configuration page of the platform, and then the application program obtains the point location information of the camera and the intelligent rule configured on the camera by reading the configuration information.
The video stream reading module 202 reads a video stream according to the camera point location information;
in a preferred embodiment of the present invention, the application program obtains the corresponding video stream through the point location information of the camera, and further reads the image in the video stream.
The image detection module 203 loads a video stream processing model corresponding to the intelligent rule and performs image detection on the video stream based on the video stream processing model;
in the preferred embodiment of the present invention, the corresponding video stream processing model is loaded according to the intelligent rule, for example, when the target detection is needed, the target detection model is loaded; when people flow prediction is needed, loading a people flow prediction model; and when the face recognition is required, loading the face recognition model.
The target monitoring model carries out target detection on the images in the video stream, wherein the target detection comprises human body tracking, worker brand detection, ground rubbish detection, appearance detection, behavior detection and screen state detection; the people flow prediction model is used for analyzing and predicting the real-time people flow quantity in the video flow so as to obtain the condition of the people flow quantity in a certain time period, and the face recognition model is used for carrying out face recognition on people in the video flow and can be used for recognizing staff of a company or people in other fields.
And the result acquisition module 204 is used for acquiring effective routing inspection information based on the image detection result.
In a preferred embodiment of the invention, information filtering and duplicate removal are carried out on the image detection result, information precision is realized, errors are reduced, then final inspection information is obtained, and if violation of personnel in the monitoring area exists in the inspection information or the flow of the personnel is too large, an alarm is given to inform a manager to carry out corresponding management, personnel evacuation and the like.
Further, still include:
drawing the result of the image detection to the image to obtain a latest image;
and displaying the latest image on a display page.
Further, the image detection of the video stream based on the video stream processing model includes:
performing target detection on the image in the video stream based on a target monitoring model, wherein the target detection comprises human body tracking, workcard detection, ground rubbish detection, appearance detection, behavior detection and screen state detection;
analyzing and predicting the real-time people flow quantity in the video flow based on a people flow prediction model;
performing face recognition on the personnel in the video stream based on a face recognition model;
the video stream processing model comprises a target monitoring model, a people stream prediction model and a face recognition model.
Further, the performing face recognition on the person in the video stream based on the face recognition model includes:
matching the human body detection box with the faces of the persons in the video stream based on a Hungarian algorithm;
calculating the overlapping rate of the matched human body detection frame and the human face;
and calculating the distance between the matched human body detection frame and the human face.
Further, the obtaining of the effective inspection information based on the result of the image detection includes:
filtering the detection result by a preset frame number, and performing duplicate removal on the filtered detection result;
and carrying out personnel information fusion on the images in the video stream to obtain effective routing inspection information.
Further, the personnel information includes: worker's cards, hair, human face, clothing, post.
The method and the system can realize unified management on the model, reduce labor cost, and can configure the intelligent rules in a unified way through the configuration page, thereby more effectively screening out the required inspection information and giving early warning to the staff in time.
Based on the same inventive concept, the embodiment of the specification further provides the electronic equipment.
In the following, embodiments of the electronic device of the present invention are described, which may be regarded as specific physical implementations for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.
Fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present specification. An electronic device 300 according to this embodiment of the invention is described below with reference to fig. 3. The electronic device 300 shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 3, electronic device 300 is embodied in the form of a general purpose computing device. The components of electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one memory unit 320, a bus 330 connecting different device components (including the memory unit 320 and the processing unit 310), a display unit 340, and the like.
Wherein the storage unit stores program code executable by the processing unit 310 to cause the processing unit 310 to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned processing method section of the present specification. For example, the processing unit 310 may perform the steps as shown in fig. 1.
The storage unit 320 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)3201 and/or a cache storage unit 3202, and may further include a read only memory unit (ROM) 3203.
The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating device, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 300, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 300 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 350. Also, the electronic device 300 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 360. Network adapter 360 may communicate with other modules of electronic device 300 via bus 330. It should be appreciated that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID devices, tape drives, and data backup storage devices, to name a few.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to implement the above-described method of the invention, namely: such as the method shown in fig. 1.
Fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present disclosure.
A computer program implementing the method shown in fig. 1 may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor device, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution apparatus, device, or apparatus. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A routing inspection method based on computer vision is characterized by comprising the following steps:
acquiring camera point location information and an intelligent rule of a camera;
reading a video stream according to the camera point location information;
loading a video stream processing model corresponding to the intelligent rule, and carrying out image detection on the video stream based on the video stream processing model;
and obtaining effective routing inspection information based on the image detection result.
2. The inspection method based on computer vision according to claim 1, characterized by further comprising:
drawing the result of the image detection to the image to obtain a latest image;
and displaying the latest image on a display page.
3. The computer vision based inspection method according to claim 1, wherein the image detection of the video stream based on the video stream processing model includes:
performing target detection on the image in the video stream based on a target monitoring model, wherein the target detection comprises human body tracking, workcard detection, ground rubbish detection, appearance detection, behavior detection and screen state detection;
analyzing and predicting the real-time people flow quantity in the video flow based on a people flow prediction model;
performing face recognition on the personnel in the video stream based on a face recognition model;
the video stream processing model comprises a target monitoring model, a people stream prediction model and a face recognition model.
4. The inspection method based on computer vision according to claim 3, wherein the face recognition of the person in the video stream based on the face recognition model comprises:
matching the human body detection box with the faces of the persons in the video stream based on a Hungarian algorithm;
calculating the overlapping rate of the matched human body detection frame and the human face;
and calculating the distance between the matched human body detection frame and the human face.
5. The inspection method based on computer vision according to claim 1, wherein the obtaining of the effective inspection information based on the result of the image detection comprises:
filtering the detection result by a preset frame number, and performing duplicate removal on the filtered detection result;
and carrying out personnel information fusion on the images in the video stream to obtain effective routing inspection information.
6. The inspection method based on computer vision according to claim 5, characterized in that the personnel information includes: worker's cards, hair, human face, clothing, post.
7. The utility model provides an inspection device based on computer vision which characterized in that includes:
the information acquisition module is used for acquiring the point location information of the camera and the intelligent rule of the camera;
the video stream reading module reads a video stream according to the camera point location information;
the image detection module loads a video stream processing model corresponding to the intelligent rule and carries out image detection on the video stream based on the video stream processing model;
and the result acquisition module is used for acquiring effective routing inspection information based on the image detection result.
8. The inspection device based on computer vision of claim 7, further comprising:
drawing the result of the image detection to the image to obtain a latest image;
and displaying the latest image on a display page.
9. An electronic device, wherein the electronic device comprises:
a processor and a memory storing computer-executable instructions that, when executed, cause the processor to perform the method of any of claims 1-6.
10. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 1-6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114582037A (en) * | 2022-02-28 | 2022-06-03 | 成都商汤科技有限公司 | Inspection method and device, electronic equipment and computer readable storage medium |
| CN116915946A (en) * | 2023-06-20 | 2023-10-20 | 河北华网计算机技术有限公司 | Intelligent monitoring method, system, equipment and medium based on machine vision |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160314351A1 (en) * | 2015-04-27 | 2016-10-27 | Xerox Corporation | Extending generic business process management with computer vision capabilities |
| CN109803112A (en) * | 2017-11-16 | 2019-05-24 | 中兴通讯股份有限公司 | Video analysis management method based on big data, apparatus and system, storage medium |
| CN110223413A (en) * | 2019-06-12 | 2019-09-10 | 深圳铂石空间科技有限公司 | Intelligent polling method, device, computer storage medium and electronic equipment |
| CN110717403A (en) * | 2019-09-16 | 2020-01-21 | 国网江西省电力有限公司电力科学研究院 | Face multi-target tracking method |
| CN110895881A (en) * | 2019-12-17 | 2020-03-20 | 成都通甲优博科技有限责任公司 | Traffic data processing method, device and storage medium |
| CN111970490A (en) * | 2020-08-06 | 2020-11-20 | 万翼科技有限公司 | User flow monitoring method and related equipment |
| CN112132041A (en) * | 2020-09-24 | 2020-12-25 | 天津锋物科技有限公司 | Community patrol analysis method and system based on computer vision |
| CN112257569A (en) * | 2020-10-21 | 2021-01-22 | 青海城市云大数据技术有限公司 | Target detection and identification method based on real-time video stream |
-
2021
- 2021-02-07 CN CN202110179617.4A patent/CN112906552A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160314351A1 (en) * | 2015-04-27 | 2016-10-27 | Xerox Corporation | Extending generic business process management with computer vision capabilities |
| CN109803112A (en) * | 2017-11-16 | 2019-05-24 | 中兴通讯股份有限公司 | Video analysis management method based on big data, apparatus and system, storage medium |
| CN110223413A (en) * | 2019-06-12 | 2019-09-10 | 深圳铂石空间科技有限公司 | Intelligent polling method, device, computer storage medium and electronic equipment |
| CN110717403A (en) * | 2019-09-16 | 2020-01-21 | 国网江西省电力有限公司电力科学研究院 | Face multi-target tracking method |
| CN110895881A (en) * | 2019-12-17 | 2020-03-20 | 成都通甲优博科技有限责任公司 | Traffic data processing method, device and storage medium |
| CN111970490A (en) * | 2020-08-06 | 2020-11-20 | 万翼科技有限公司 | User flow monitoring method and related equipment |
| CN112132041A (en) * | 2020-09-24 | 2020-12-25 | 天津锋物科技有限公司 | Community patrol analysis method and system based on computer vision |
| CN112257569A (en) * | 2020-10-21 | 2021-01-22 | 青海城市云大数据技术有限公司 | Target detection and identification method based on real-time video stream |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114582037A (en) * | 2022-02-28 | 2022-06-03 | 成都商汤科技有限公司 | Inspection method and device, electronic equipment and computer readable storage medium |
| CN116915946A (en) * | 2023-06-20 | 2023-10-20 | 河北华网计算机技术有限公司 | Intelligent monitoring method, system, equipment and medium based on machine vision |
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