CN112487851A - Judicial place abnormal behavior monitoring method based on artificial intelligence video identification - Google Patents
Judicial place abnormal behavior monitoring method based on artificial intelligence video identification Download PDFInfo
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- CN112487851A CN112487851A CN201910865283.9A CN201910865283A CN112487851A CN 112487851 A CN112487851 A CN 112487851A CN 201910865283 A CN201910865283 A CN 201910865283A CN 112487851 A CN112487851 A CN 112487851A
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- 206010000117 Abnormal behaviour Diseases 0.000 title claims abstract description 60
- 238000012544 monitoring process Methods 0.000 title claims abstract description 33
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 21
- 238000012806 monitoring device Methods 0.000 claims abstract description 8
- 230000006399 behavior Effects 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 6
- 239000002699 waste material Substances 0.000 abstract description 3
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- 230000005540 biological transmission Effects 0.000 description 3
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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Abstract
The invention is suitable for the technical field of video identification, and provides a judicial place abnormal behavior monitoring method based on artificial intelligence video identification, which adopts a monitoring device to realize monitoring, wherein the monitoring device comprises a collecting camera, an identification server, a terminal and an abnormal behavior model, a target video is collected by the collecting camera and then is transmitted to the identification server, the identification server analyzes the target video through the abnormal behavior model, when a single or a plurality of targets reach a comparison matching similarity threshold value within a set time range, the target video is judged to be an abnormal behavior result, the judgment result and the identification time are output, the target video is collected by the collecting camera, and then the target video is transmitted to the identification server, so that omission and investment of manual monitoring are avoided, and personnel safety is effectively ensured, The place is safe, reduces the waste of manpower, time.
Description
Technical Field
The invention belongs to the technical field of video identification, and particularly relates to a judicial place abnormal behavior monitoring method based on artificial intelligence video identification.
Background
The video identification mainly comprises three links of acquisition and transmission of front-end video information, intermediate video detection and analysis and processing of a rear end. The video identification needs a front-end video acquisition camera to provide clear and stable video signals, and the quality of the video signals directly influences the effect of the video identification.
The abnormal behaviors of prisoners need to be monitored uninterruptedly in judicial places such as prisons and drug-relief centers, the existing monitoring mode generally adopts manual observation, the existing monitoring mode has certain defects, the manual observation efficiency is low, the resource consumption is large, the system construction and operation and maintenance cost is high, the operation safety is not enough, the manpower use is more, and the actual operation is not convenient to carry out.
Disclosure of Invention
The invention provides a judicial place abnormal behavior monitoring method based on artificial intelligence video identification, and aims to solve the problems of low efficiency, high resource consumption, high system construction and operation and maintenance cost, insufficient operation safety and more manpower.
The invention is realized in this way, a judicial place abnormal behavior monitoring method based on artificial intelligence video identification, which adopts a monitoring device to realize monitoring, wherein the monitoring device comprises a collecting camera, an identification server, a terminal and an abnormal behavior model;
the output end of the acquisition camera is connected with the input end of the identification server, the output end of the identification server is connected with the input end of the terminal, and the content of the identification server is provided with an abnormal behavior model for the identification server to compare abnormal behaviors;
the judicial place abnormal behavior monitoring method based on artificial intelligence video identification comprises the following steps:
s1: collecting a target video through the collecting camera, and then transmitting the target video to the identification server;
s2: the identification server analyzes the target video through the abnormal behavior model;
s3: and when the single or multiple targets reach the threshold value of the comparison matching similarity within the set time range, judging that the targets are abnormal behavior results, and outputting a judgment result and an identification timestamp.
Preferably, the present invention further provides that if there is no match in the detection result within the set time range, the determination is made as no.
Preferably, an identification system is arranged in the identification server, and the abnormal behavior model is arranged in the identification system.
The invention also provides that preferably, the abnormal behavior model comprises squat behavior, crouch behavior and altitude touch behavior.
Preferably, the identification server is connected with an alarm module, and when the output of the identification server is a judgment structure of abnormal behavior, the alarm module is started to alarm.
The invention also provides a preferable mode, and the terminal accesses the identification system through a B/S mode.
The invention also provides a preferable mode, and the terminal adopts a touch display screen.
The invention also provides a preferable mode, and the acquisition camera adopts a network camera.
Compared with the prior art, the invention has the beneficial effects that: according to the judicial place abnormal behavior monitoring method based on artificial intelligence video identification, the target video is acquired through the acquisition camera, then the target video is transmitted to the identification server, then the identification server analyzes the target video through the abnormal behavior model, when a single target or a plurality of targets reach the threshold value of comparison matching similarity within a set time range, the target video is judged to be an abnormal behavior result, and a judgment result and an identification timestamp are output, so that the abnormal behavior can be judged efficiently, careless omission and investment of only manual monitoring are avoided, the safety of personnel and places are effectively ensured, and the waste of manpower and time is reduced.
Drawings
Fig. 1 is a schematic overall structure diagram of a judicial place abnormal behavior monitoring method based on artificial intelligence video identification according to the present invention.
In the figure: 1-collecting a camera, 2-identifying a server, 3-a terminal, 4-an abnormal behavior identifying model and 5-an identifying system.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, the present invention provides a technical solution: a judicial place abnormal behavior monitoring method based on artificial intelligence video identification is characterized in that a monitoring device is adopted for monitoring, the monitoring device comprises an acquisition camera 1, an identification server 2, a terminal 3 and an abnormal behavior model 5, the output end of the acquisition camera 1 is connected with the input end of the identification server 2, the output end of the identification server 2 is connected with the input end of the terminal 3, the identification server 2 is internally provided with the abnormal behavior model 5 for comparing abnormal behaviors of the identification server, the identification server 2 is internally provided with an identification system 4, the identification system 4 is internally provided with the abnormal behavior model 5, the abnormal behavior model 5 comprises a squat behavior, a land falling behavior and a groping behavior, the identification server 2 is connected with an alarm module, when the output of the identification server is a judging structure of the abnormal behaviors, the alarm module is started and alarms, the terminal 3 accesses the identification system 4 in a B/S mode, terminal 3 adopts the touch-control display screen, and the collection camera 1 adopts the network camera.
The collecting camera 11 is used for collecting target videos and then transmits the target videos to the recognition server 2 through a network, the recognition server 2 analyzes the target videos through an abnormal behavior model, the comparison probability of behaviors of squatting, falling down and groping is recognized, when a single or a plurality of targets reach a comparison matching similarity threshold value within a set time range, an abnormal behavior result and a recognition timestamp are output, when a detection result is not matched within the set time range, the recognition result is judged to be absent, a solid-state driver used for storing the recognition system 4 and the abnormal behavior model 5 is arranged in the recognition server 2, the collecting camera 11 is connected with the recognition server through a network cable, and therefore network information transmission can be carried out, transmission efficiency is high, and network delay is small.
The recognition system 4 is installed in the recognition server 2 through a micro-service architecture, which is a new technology for deploying applications and services in the cloud, and in the micro-service architecture, only required functions need to be added in a specific certain service without affecting the architecture of the whole process.
The B/S structure is a network structure mode after WEB is started, and a WEB browser is the most main application software of a client. The mode unifies the client, centralizes the core part of the system function realization to the server, and simplifies the development, maintenance and use of the system. The client only needs to install a browser, and the server installs the database. And the browser performs data interaction with the database.
Solid state drives are commonly referred to as Solid state drives, which are hard drives made from arrays of Solid state electronic memory chips, which are known as Solid capacitors in taiwan english. The SSD is composed of a control unit and a storage unit. The specification, definition, function and use method of the interface of the solid state disk are completely the same as those of a common hard disk, and the appearance and size of the product are also completely consistent with those of the common hard disk. The method is widely applied to the fields of military affairs, vehicle-mounted, industrial control, video monitoring, network terminals, electric power, medical treatment, aviation, navigation equipment and the like.
The user can access the recognition system 4 through the touch display screen of the terminal 3, and the judgment result of the recognition server 2 on the behavior of the target is summarized and presented through the touch display screen.
In summary, the monitoring method of the present invention includes the following steps:
s1: the target video is captured by the capture camera 1 and then transmitted to the recognition server 2.
S2: the recognition server 2 analyzes the target video through the abnormal behavior model 5.
S3: and when the single or multiple targets reach the threshold value of the comparison matching similarity within the set time range, judging that the targets are abnormal behavior results and outputting a judgment result and an identification timestamp, and when the detection result is not matched within the set time range, judging that the identification result is not matched.
The invention relates to a judicial place abnormal behavior monitoring method based on artificial intelligence video identification, which comprises the steps of collecting a target video through a collecting camera 11, transmitting the target video to an identification server 2 through a network, analyzing the target video through an abnormal behavior model by the identification server 2, identifying the comparison probability of squat, flip and groping behaviors, outputting an abnormal behavior result and an identification timestamp when a single or a plurality of targets reach a comparison matching similarity threshold value within a set time range, and judging whether the identification result is absent when the detection result is not matched within the set time range.
The invention aims to solve the problems of abnormal behavior monitoring and early warning in complex environments of judicial places by using an artificial intelligence technology, wherein the abnormal behavior comprises the following steps: the intelligent monitoring system is suitable for timely finding and alarming abnormal behaviors in various judicial places such as prisons and drug-relief centers and the like, avoids careless omission and investment only depending on manual monitoring, effectively ensures the safety of personnel and places, and reduces the waste of manpower and time.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. A judicial place abnormal behavior monitoring method based on artificial intelligence video identification is characterized in that a monitoring device is adopted to realize monitoring, and the method comprises the following steps: the monitoring device comprises a collecting camera (1), an identification server (2), a terminal (3) and an abnormal behavior model (5);
the output end of the acquisition camera (1) is connected with the input end of the identification server (2), the output end of the identification server (2) is connected with the input end of the terminal (3), and the identification server (2) is internally provided with an abnormal behavior model (5) for comparing abnormal behaviors;
the judicial place abnormal behavior monitoring method based on artificial intelligence video identification comprises the following steps:
s1: collecting a target video through the collecting camera (1) and then transmitting the target video to the recognition server (2);
s2: the recognition server (2) analyzes the target video through the abnormal behavior model (5);
s3: and when the single or multiple targets reach the threshold value of the comparison matching similarity within the set time range, judging that the targets are abnormal behavior results, and outputting a judgment result and an identification timestamp.
2. The judicial place abnormal behavior monitoring method based on artificial intelligence video identification as claimed in claim 1, wherein: and judging whether the identification result is negative when the detection result is not matched within the set time range.
3. The judicial place abnormal behavior monitoring method based on artificial intelligence video identification as claimed in claim 1, wherein: and a recognition system (4) is arranged in the recognition server (2), and the abnormal behavior model (5) is arranged in the recognition system (4).
4. The judicial place abnormal behavior monitoring method based on artificial intelligence video identification as claimed in claim 1, wherein: the abnormal behavior model (5) comprises squat behavior, flip behavior and jump behavior.
5. The judicial place abnormal behavior monitoring method based on artificial intelligence video identification as claimed in claim 1, wherein: the identification server (2) is connected with an alarm module, and when the output of the identification server is a judgment structure of abnormal behaviors, the alarm module is started to give an alarm.
6. The judicial place abnormal behavior monitoring method based on artificial intelligence video identification as claimed in claim 3, wherein: the terminal (3) accesses the identification system (4) in a B/S manner.
7. The judicial place abnormal behavior monitoring method based on artificial intelligence video identification as claimed in claim 1, wherein: the terminal (3) adopts a touch display screen.
8. The judicial place abnormal behavior monitoring method based on artificial intelligence video identification as claimed in claim 1, wherein: the acquisition camera (1) adopts a network camera.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910865283.9A CN112487851A (en) | 2019-09-12 | 2019-09-12 | Judicial place abnormal behavior monitoring method based on artificial intelligence video identification |
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| CN201910865283.9A CN112487851A (en) | 2019-09-12 | 2019-09-12 | Judicial place abnormal behavior monitoring method based on artificial intelligence video identification |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113065500A (en) * | 2021-04-15 | 2021-07-02 | 电子科技大学 | Abnormal behavior control system for special actions |
| CN113473085A (en) * | 2021-07-01 | 2021-10-01 | 成都市达岸信息技术有限公司 | Video monitoring identification system based on artificial intelligence technology |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201315654Y (en) * | 2008-08-25 | 2009-09-23 | 云南正卓信息技术有限公司 | Special SkyEyes** intelligent monitoring system for prison |
| CN108900801A (en) * | 2018-06-29 | 2018-11-27 | 深圳市九洲电器有限公司 | A kind of video monitoring method based on artificial intelligence, system and Cloud Server |
-
2019
- 2019-09-12 CN CN201910865283.9A patent/CN112487851A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201315654Y (en) * | 2008-08-25 | 2009-09-23 | 云南正卓信息技术有限公司 | Special SkyEyes** intelligent monitoring system for prison |
| CN108900801A (en) * | 2018-06-29 | 2018-11-27 | 深圳市九洲电器有限公司 | A kind of video monitoring method based on artificial intelligence, system and Cloud Server |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113065500A (en) * | 2021-04-15 | 2021-07-02 | 电子科技大学 | Abnormal behavior control system for special actions |
| CN113473085A (en) * | 2021-07-01 | 2021-10-01 | 成都市达岸信息技术有限公司 | Video monitoring identification system based on artificial intelligence technology |
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