CN112087604A - Intelligent monitoring video management and control method based on image recognition - Google Patents
Intelligent monitoring video management and control method based on image recognition Download PDFInfo
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- 238000013527 convolutional neural network Methods 0.000 claims description 4
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client
- H04N21/63—Control signaling related to video distribution between client, server and network components; Network processes for video distribution between server and clients or between remote clients, e.g. transmitting basic layer and enhancement layers over different transmission paths, setting up a peer-to-peer communication via Internet between remote STB's; Communication protocols; Addressing
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Abstract
The invention discloses an intelligent monitoring video control method based on image recognition, and belongs to the technical field of video image recognition. The intelligent monitoring video control method based on image recognition carries out target detection based on the CNN characteristics, carries out characteristic object recognition processing on real-time monitoring video, triggers early warning information and dispatches an early warning work order aiming at different service scene recognition characteristic data, and carries out processing on the early warning work order by safety guarantee personnel. The intelligent monitoring video control method based on image recognition can reduce the incidence rate of safety accidents, improve the discrimination efficiency of abnormal conditions of the monitoring video, reduce the workload of security personnel, further save the enterprise cost and have good popularization and application values.
Description
Technical Field
The invention relates to the technical field of video image recognition, and particularly provides an intelligent monitoring video management and control method based on image recognition.
Background
With the coverage of a monitoring camera and the accumulation of a large amount of video data, the manual inspection mode cannot meet the requirement of wide video monitoring, and the intelligent video monitoring technology utilizing deep learning becomes a new scheme for reading and utilizing video information. The artificial intelligence and deep learning technology can effectively reduce human errors and false alarms, greatly reduce the influence on searching time, and greatly influence industries such as industrial manufacturing, medical treatment, transportation and the like.
At present, the industry commonly adopts a depth Convolution Neural Network (CNN) based feature to perform target detection on video frames in a monitored video, and the specific method comprises the following steps: the method includes the steps that a corresponding preset position is set for a certain single scene, then a monitoring camera is started to cruise, when the camera is located on the preset position, a video stream is captured and transmitted to a server, the server calls a deep learning algorithm to detect, whether abnormity exists or not is judged according to a detection result, if abnormity exists, a pushing alarm is given, and then the camera continues to cruise. The method can overcome the defects of low detection precision and low detection speed of the traditional image technology, but the method also has obvious defects, namely, one camera can only bind one algorithm to process a single scene, and the problems of single corresponding scene and low resource utilization rate exist.
Disclosure of Invention
The technical task of the invention is to provide the intelligent monitoring video control method based on image recognition, which can reduce the occurrence rate of safety accidents, improve the screening efficiency of abnormal conditions of the monitoring video, reduce the workload of security personnel and further save the enterprise cost.
In order to achieve the purpose, the invention provides the following technical scheme:
a monitoring video intelligent control method based on image recognition is characterized by carrying out target detection based on a deep Convolutional Neural Network (CNN) feature, carrying out feature object recognition processing on a real-time monitoring video, recognizing feature data aiming at different service scenes, triggering early warning information and distributing an early warning work order, and processing the early warning work order by safety guarantee personnel.
Preferably, the intelligent management and control method for the monitoring video based on the image recognition specifically comprises the following steps:
s1, accessing the real-time video stream of the monitoring camera by the video management function module, and storing the real-time video stream in a server;
s2, the image recognition function module analyzes the real-time video and calls a corresponding feature model to process the video;
s3, analyzing the detection result through the early warning management function module, if no abnormity exists, directly returning to normal, otherwise triggering early warning to generate early warning information, and carrying out voice reminding;
s4, after the early warning information is generated, the monitoring personnel sends an early warning disposal work order to the safety guarantee personnel;
s5, the safety guarantee personnel use the early warning work order processing APP to receive the early warning processing work order and check the basic information of the early warning processing work order;
and S6, the safety guarantee personnel dispose the early warning event, and close the early warning disposal work order after disposal is finished.
Preferably, in step S1, the video management function module accesses the real-time monitoring video stream based on the RTSP protocol, and performs real-time video presentation, camera lens stretching, and history monitoring image storage.
Preferably, in step S2, the image recognition function module transcodes the real-time monitoring video stream into video frames in base64 format according to the set frame rate, and calls the feature model to process the video to determine whether the specified monitoring target exists.
Preferably, in step S3, the early warning management function module automatically generates early warning information for the abnormal video frames monitored by the image recognition function module.
Preferably, the early warning information comprises early warning occurrence points, early warning occurrence time and early warning related images/videos.
Preferably, in step S4, the work order management module is configured to dispatch an abnormal warning generated by the warning management function module, where the work order management module includes a to-do list, a done list, and a work order query.
Preferably, in step S5, the work order processing APP performs detail checking and work order processing operations on the warning treatment work order distributed by the work order management module.
Preferably, the basic information of the early warning treatment work order includes a camera position, an early warning image/short video and early warning occurrence time.
Preferably, in step S6, the early warning work order processing APP automatically locates the address location of the early warning according to the longitude and latitude coordinates in the details of the early warning work order, and after the map navigation function is selected, the early warning work order processing APP opens the navigation map and highlights the navigation path.
Compared with the prior art, the intelligent monitoring video management and control method based on image recognition has the following outstanding beneficial effects: the intelligent monitoring video control method based on image recognition uses a video stream access mode based on an RTSP (real time streaming protocol), so that cross-manufacturer video access is realized, and an enterprise can conveniently manage monitoring videos; the image recognition algorithm based on deep learning is used for carrying out feature recognition on multiple scenes, and one camera is provided with multiple recognition algorithms, so that one camera is multi-purpose, the utilization rate of enterprise assets is improved, and the investment cost of enterprise equipment is reduced; the early warning management function module can automatically early warning abnormal monitoring videos, does not need monitoring personnel to check the camera videos in real time, and only needs early warning generated by the system automatically to be processed, so that the workload of the monitoring personnel is reduced, and the labor investment cost of enterprises is saved; by using the work order management module, the management closed loop of early warning generation, work order distribution, work order processing and early warning removal is realized, and the safety production operation quality of an enterprise is improved; meanwhile, the system also provides a work order processing APP, enterprise safety guarantee personnel can quickly know early warning information and check, position and process the work order to be processed, the processing efficiency of enterprise safety guarantee events is improved, the safety production operation quality of enterprises is improved, the stable operation of enterprise safety production is guaranteed, and the system has good popularization and application values.
Drawings
Fig. 1 is a flowchart of a monitoring video intelligent management and control method based on image recognition according to the present invention.
Detailed Description
The intelligent management and control method for monitoring video based on image recognition of the present invention will be further described in detail with reference to the accompanying drawings and embodiments.
Examples
As shown in fig. 1, the intelligent management and control method for the monitoring video based on image recognition performs target detection based on the CNN features of the deep convolutional neural network, performs feature object recognition processing on the real-time monitoring video, recognizes feature data for different service scenes, triggers early warning information and dispatches an early warning work order, and safety guarantee personnel process the early warning work order.
Preferably, the intelligent management and control method for the monitoring video based on the image recognition specifically comprises the following steps:
and S1, the video management function module accesses the real-time video stream of the monitoring camera and stores the real-time video stream in the server.
The video management function module is accessed to a real-time monitoring video stream based on the RTSP, and performs real-time video presentation, camera lens stretching and historical monitoring image storage.
The video management function module comprises a camera management function, camera preset point location management, electronic fence management and algorithm binding management, and a user can configure relevant configuration information of the camera as required. By adopting the RTSP standard video stream access mode, the complex operation of cross-manufacturer camera configuration is avoided, and the working efficiency of enterprise monitoring personnel is improved.
And S2, the image recognition function module analyzes the real-time video and calls the corresponding feature model to process the video. The image recognition function module transcodes the real-time monitoring video stream into a video frame in a base64 format according to a set frame frequency, and simultaneously calls a characteristic model to process the video and judges whether a specified monitoring target exists.
The image recognition function module provides a video image automatic recognition algorithm based on deep learning, supports multi-scene algorithm recognition, such as detection objects of people, vehicles, objects and the like, and one camera can be configured with a plurality of algorithms to detect a plurality of characteristic objects, so that one camera is multi-purpose, and the enterprise investment cost is reduced.
And S3, analyzing the detection result through the early warning management function module, if no abnormity exists, directly returning to normal, otherwise, triggering early warning to generate early warning information, and carrying out voice reminding. And the early warning management functional module automatically generates early warning information for the abnormal video frames monitored by the image identification functional module. The early warning information comprises early warning occurrence point positions, early warning occurrence time and early warning related images/videos.
And the early warning management function module judges whether the early warning information needs to be generated according to whether the algorithm identification result is abnormal or not, and comprises the functions of early warning checking, early warning clearing and expected dispatching. By the mode, the enterprise video monitoring personnel do not need to monitor in real time, and only need to check the early warning generated automatically by the system, so that the workload of the enterprise monitoring personnel is reduced, and the working efficiency of the enterprise monitoring personnel is improved.
And S4, after the early warning information is generated, the monitoring personnel sends an early warning disposal work order to the safety guarantee personnel. The work order management module is used for dispatching the abnormal early warning generated by the early warning management function module, wherein the work order management module comprises a to-do list, a done list and work order inquiry.
The work order management module intelligent supervision platform has the functions of early warning and dispatching work orders, after monitoring video early warning credit is found, monitoring personnel can dispatch early warning processing work orders for enterprise safety guarantee personnel and request the enterprise safety guarantee personnel to process on site, after the safety guarantee personnel arrive at the site, the early warning information is processed, after the processing is finished, the early warning processing work orders can be closed, and meanwhile, after the monitoring personnel approve the processing result of the safety guarantee personnel, the early warning information is cleared, so that the management closed loop of early warning generation, work order dispatching, work order processing and early warning clearing is realized.
And S5, the safety guarantee personnel use the early warning work order processing APP to receive the early warning processing work order and check the basic information of the early warning processing work order. The work order processing APP carries out detail checking and work order processing operation on the early warning processing work orders distributed by the work order management module. The basic information of the early warning treatment work order comprises the position of a camera, an early warning image/short video and early warning occurrence time. The APP is handled to the work order, in view of enterprise safety guarantee personnel arrive on-the-spot after, can't carry the PC computer, and the system provides early warning work order and handles the APP, and enterprise safety guarantee personnel can treat in the APP and do the work order and look over, fix a position, handle the operation, have improved the treatment effeciency of enterprise safety guarantee incident, have improved enterprise safety production operation quality, guarantee enterprise safety production even running.
And S6, the safety guarantee personnel dispose the early warning event, and close the early warning disposal work order after disposal is finished.
And the early warning work order processing APP automatically positions the early warning generation address position according to longitude and latitude coordinates in the early warning work order details, and after a map navigation function is selected, the early warning work order processing APP opens a navigation map and highlights a navigation path.
The above-described embodiments are merely preferred embodiments of the present invention, and general changes and substitutions by those skilled in the art within the technical scope of the present invention are included in the protection scope of the present invention.
Claims (10)
1. A monitoring video intelligent control method based on image recognition is characterized in that: the method carries out target detection based on the CNN characteristics of the deep convolutional neural network, carries out characteristic object identification processing on a real-time monitoring video, identifies characteristic data aiming at different service scenes, triggers early warning information and dispatches an early warning work order, and safety guarantee personnel process the early warning work order.
2. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 1, wherein: the method specifically comprises the following steps:
s1, accessing the real-time video stream of the monitoring camera by the video management function module, and storing the real-time video stream in a server;
s2, the image recognition function module analyzes the real-time video and calls a corresponding feature model to process the video;
s3, analyzing the detection result through the early warning management function module, if no abnormity exists, directly returning to normal, otherwise triggering early warning to generate early warning information, and carrying out voice reminding;
s4, after the early warning information is generated, the monitoring personnel sends an early warning disposal work order to the safety guarantee personnel;
s5, the safety guarantee personnel use the early warning work order processing APP to receive the early warning processing work order and check the basic information of the early warning processing work order;
and S6, the safety guarantee personnel dispose the early warning event, and close the early warning disposal work order after disposal is finished.
3. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 2, wherein: in step S1, the video management function module accesses the real-time monitoring video stream based on the RTSP protocol, and performs real-time video presentation, camera lens stretching, and historical monitoring image storage.
4. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 3, wherein: in step S2, the image recognition function module transcodes the real-time monitoring video stream into a video frame in base64 format according to a set frame rate, and calls a feature model to process the video to determine whether a specified monitoring target exists.
5. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 4, wherein the intelligent management and control method comprises: in step S3, the early warning management function module automatically generates early warning information for the abnormal video frames monitored by the image recognition function module.
6. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 5, wherein: the early warning information comprises early warning occurrence point positions, early warning occurrence time and early warning related images/videos.
7. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 6, wherein: in step S4, the work order management module is used to dispatch the abnormal warning generated by the warning management function module, wherein the work order management module includes a to-do list, an already-done list and a work order query.
8. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 7, wherein: in step S5, the work order processing APP performs detail checking and work order processing operations on the early warning processing work order distributed by the work order management module.
9. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 8, wherein: the basic information of the early warning treatment work order comprises the position of a camera, early warning images/short videos and early warning occurrence time.
10. The intelligent management and control method for monitoring videos based on image recognition as claimed in claim 9, wherein: in step S6, the early warning work order processing APP automatically positions the early warning generation address position according to the longitude and latitude coordinates in the early warning work order details, and after the map navigation function is selected, the early warning work order processing APP opens the navigation map and highlights the navigation path.
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| US20220366379A1 (en) * | 2021-05-14 | 2022-11-17 | Chase Environmental Co., Ltd. | Intelligent monitoring system for waste disposal and method thereof |
| CN115866214A (en) * | 2023-03-02 | 2023-03-28 | 安徽兴博远实信息科技有限公司 | Video accurate management and management system based on artificial intelligence |
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