CN107818312A - A kind of embedded system based on abnormal behaviour identification - Google Patents
A kind of embedded system based on abnormal behaviour identification Download PDFInfo
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- CN107818312A CN107818312A CN201711155914.5A CN201711155914A CN107818312A CN 107818312 A CN107818312 A CN 107818312A CN 201711155914 A CN201711155914 A CN 201711155914A CN 107818312 A CN107818312 A CN 107818312A
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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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0487—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
- G06F3/0488—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
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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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- 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
- G06V20/44—Event detection
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Abstract
The invention discloses a kind of embedded system based on abnormal behaviour identification.It is an object of the invention to provide a kind of embedded system based on abnormal behaviour identification, including monitoring camera, Activity recognition main frame, server（Data center）, comprehensive management platform, it is characterised in that：The monitoring camera is used for collection site video data, and Activity recognition main frame is used to judge the posture of Field Force according to acceleration magnitude, described server（Data center）It is connected with Activity recognition main frame, the data sent according to Activity recognition main frame carry out comprehensive analysis, then draw final sumbission, send comprehensive management platform to and authorize APP.The present invention identifies main frame and front end high definition monitoring camera by the intelligent behavior of plug and play, the round-the-clock early warning to key area suspicious figure and event can be realized, while realizes the identification early warning to controlled area personnel crowd abnormal behaviour and armed, dangerous cutter.
Description
Technical field
The present invention relates to a kind of Activity recognition system, more particularly to a kind of embedded system based on abnormal behaviour identification.
Background technology
The monitoring system of industry simply carries out the detection or tracking of moving target in scene mostly now, to different in scene
The abnormal behaviour of ordinary affair part or people make the fewer of further detection and analysis.The existing abnormality detection based on monitoring system
Method is mainly monitored judgement by the method based on model, and this mode is firstly the need of certain criterion is determined, then from figure
The information such as profile, motion as extracting moving target in sequence, the characteristic information obtained according to these are artificial or using half
The method of supervision defines the model of normal behaviour, generally from graph model enter the state represented by sequential image feature
Row modeling, those mismatch normal behaviour models observations be regarded as it is abnormal, it is not only easy by being manually observed
Error in judgement is caused, can also influence to judge the speed of identification, while also increase human cost；Therefore, existing technology is present
It is poor and easily the problem of erroneous judgement of abnormal behaviour occur foreground image definition.Although current CCTV camera is in business
Oneself is through generally existing in, but does not give full play to the supervisory role of its real-time active, because they are typically will shooting
The output result of machine is recorded, and after abnormal conditions (vehicle in such as parking lot is stolen) occur, security personnel just passes through one
The fact that the result observation of record occurs, but it is often late.In many important public places, emergency processing is provided with
Device, when dangerous accident occurs, emergency reaction, still, current intelligent monitor system can be carried out in a short period of time
It can not be prevented before accident generation：Such as the attack of terrorist, this will result in very serious infringement.If in accident
It can just be prevented before occurring, then can play good effect.
The content of the invention
The purpose of the present invention is overcome the deficiencies in the prior art, there is provided a kind of embedded system based on abnormal behaviour identification
System, not only in illegal invasion, crowd massing, fight, run, fall down etc. alarm is sent when abnormal behaviour occurs, and can be automatic
Identify the dangerous goods such as armed, cutter and send alarm.
To achieve the above object, technical solution of the invention is：A kind of insertion based on abnormal behaviour identification is provided
Formula system, including monitoring camera, Activity recognition main frame, server（Data center）, comprehensive management platform, it is characterised in that：
The monitoring camera is used for collection site video data, and Activity recognition main frame is used for the appearance according to acceleration magnitude to Field Force
State judged, described server（Data center）It is connected with Activity recognition main frame, was transmitted according to Activity recognition main frame
The data come carry out comprehensive analysis, then draw final sumbission, send comprehensive management platform to.
The Activity recognition main frame is connected with monitoring camera, by the image in monitoring camera visual range；Behavior is known
Memory storage in other main frame has the program analyzed behavior, and performs following walk by the actuator of Activity recognition main frame
Suddenly：
The image information that A captures camera, is positioned after pretreatment, analyzes the behavior of people in image, including：Walking,
Direction of travel, stop, the residence time, expression；And carry out identity discriminating；
B is counted demographic data caused by behavioural analysis, and statistical result is preserved and sent to server（In data
The heart）, the server（Data center）Data interaction is carried out by communication module, the monitoring camera and Activity recognition main frame are logical
Cross comprehensive management platform control.
The comprehensive management platform includes the touch-screen of man-machine interaction, is also stored with the memory of the comprehensive management platform
The program of man-machine interaction, performed by the actuator of comprehensive management platform：It is real in response to the instruction of the man-machine interaction on touch-screen
The now broadcasting to Activity recognition content host, the control to camera and with server carry out data interaction；Also include and row
For identification main frame connection internet video module, described internet video module be responsible for interaction data compression, decompression and
Verification.
The Activity recognition main frame recognition result performs preset strategy；It is described that preset strategy is performed according to the recognition result
The step of include：Judge whether the recognition result meets default abnormal behaviour condition；If the recognition result meets default different
Chang Hangwei conditions, emphasis monitoring is carried out to pedestrian corresponding to the recognition result, while generate alarm.
The Activity recognition main frame is the intelligent behavior identification main frame of plug and play.
The monitoring camera is front end high definition monitoring camera.
The beneficial effects of the invention are as follows:
Region monitoring instruction：Region monitoring instruction intelligent algorithm, can effectively it be known with the rate of false alarm and rate of failing to report being almost equal to zero
Other illegal invasion behavior, while realizing the real-time early warning to region intrusion behavior, personnel in sensitizing range can be hovered and stayed
Monitored in real time Deng behavior, realize expelling or arresting in advance to a suspect.
Abnormal behaviour identifies：Abnormal behaviour identifies intelligent algorithm, can such as be fought, fallen down, squatted down, gathered with automatic detection
Collection, depart from the multiclass abnormal behaviours such as troop;The danger of the multiclass such as cutter, suspicious liquid can effectively be identified by deep learning algorithm
Article;Can be with more than 98% rate that accurately identifies, the very first time finds a suspect's abnormal behaviour and dangerous goods, allows law enforcement people
Member can make emergency reaction in the very first time.
Brief description of the drawings
Fig. 1 is the structured flowchart of the present invention.
Fig. 2 is the workflow schematic diagram of the present invention.
In figure：1-monitoring camera, 2-Activity recognition main frame, 3-server（Data center）, 4-integrated pipe pats
Platform.
Embodiment
The present invention and its embodiment are described in further detail below in conjunction with the accompanying drawings.
Referring to Fig. 1-2, the present invention includes monitoring camera 1, Activity recognition main frame 2, server（Data center）3rd, it is comprehensive
Management platform 4, it is characterised in that：The monitoring camera is used for collection site video data, and Activity recognition main frame is used for basis
Acceleration magnitude judged the posture of Field Force, described server（Data center）3 are connected with Activity recognition main frame 2
Connect, the data sent according to Activity recognition main frame carry out comprehensive analysis, then draw final sumbission, send integrated management to
Platform 4.
The Activity recognition main frame 2 is connected with monitoring camera 1, by the image in monitoring camera visual range；Behavior
Memory storage in identification main frame 2 has a program analyzed behavior, and by the actuator of Activity recognition main frame perform with
Lower step：The image information that A captures camera, is positioned after pretreatment, analyzes the behavior of people in image, including：OK
Walk, direction of travel, stop, the residence time, expression；And carry out identity discriminating；B carries out demographic data caused by behavioural analysis
Statistics, and statistical result is preserved and sent to server（Data center）3, the server（Data center）Pass through communication module
Data interaction is carried out, the monitoring camera 1 and Activity recognition main frame 2 are controlled by comprehensive management platform.
The comprehensive management platform 4 includes the touch-screen of man-machine interaction, is also stored on the memory of the comprehensive management platform
There is the program of man-machine interaction, performed by the actuator of comprehensive management platform：In response to the instruction of the man-machine interaction on touch-screen,
Realize the broadcasting to Activity recognition content host, the control to camera and carry out data interaction with server；Also include with
The internet video module of Activity recognition main frame connection, described internet video module are responsible for the compression of interaction data, decompression
And verification.
The recognition result of Activity recognition main frame 2 performs preset strategy；It is described that default plan is performed according to the recognition result
Slightly the step of, includes：Judge whether the recognition result meets default abnormal behaviour condition；If the recognition result meets default
Abnormal behaviour condition, emphasis monitoring is carried out to pedestrian corresponding to the recognition result, while generate alarm.
The Activity recognition main frame 2 is the intelligent behavior identification main frame of plug and play.
The monitoring camera 1 is front end high definition monitoring camera.
Its detailed process of the invention is by the way that an embedded abnormal behaviour is identified main frame access monitoring network, by abiding by
The video communication agreement for keeping monitoring camera obtains certain image/video monitored all the way, is then inserted into formula Activity recognition main frame to this
Road video is analyzed, and is such as directed to certain road video, people or car is locked first, then to people or a period of car（As having within 1 second
25 note images, then we analyze 1 second or 3 seconds）Consecutive movement locus is analyzed, and system is predefined to fight, runs, departing from
Troop, armed etc. are predefined abnormal behaviour, then system carries out predefined modeling to these behaviors first, for it is any with
This class behavior it is similar analyze, in this way, output alarm signal.
User can also some self-defined abnormal behaviours, as the work hours are forbidden to phone with mobile telephone, then we make a reservation in system
It is abnormal behaviour that behavior of phoning with mobile telephone is set when adopted, and system has autonomous learning function, finds similar behavior, when user sets
Between be considered as abnormal behaviour in section.
Server（Data center）Upper installation management platform software, is mainly used in the embedded Activity recognition main frame of real-time collecting
The abnormal behaviour alert data of transmission, an abnormal behaviour occurs, then platform will jump out warning message, click on and may bring up
The road real-time video picture.The data of all these abnormal behaviours are to be stored in server in real time（Data center）In.
The present invention identifies main frame and front end high definition monitoring camera by the intelligent behavior of plug and play, can realize to emphasis
Region suspicious figure and the round-the-clock early warning of event, while realize to controlled area personnel crowd abnormal behaviour and armed, dangerous
The identification early warning of cutter.
Claims (6)
1. a kind of embedded system based on abnormal behaviour identification, including monitoring camera（1）, Activity recognition main frame（2）, service
Device（Data center）（3）, comprehensive management platform（4）, it is characterised in that：The monitoring camera is used for collection site video counts
According to Activity recognition main frame is used to judge the posture of Field Force according to acceleration magnitude, described server（In data
The heart）（3）With Activity recognition main frame（2）It is connected, the data sent according to Activity recognition main frame carry out comprehensive analysis, then
Final sumbission is drawn, sends comprehensive management platform to（4）.
A kind of 2. embedded system based on abnormal behaviour identification as described in claim 1, it is characterised in that the Activity recognition
Main frame（2）With monitoring camera（1）Connection, by the image in monitoring camera visual range；Activity recognition main frame（2）Interior deposits
Reservoir is stored with the program analyzed behavior, and performs following steps by the actuator of Activity recognition main frame：A is by camera
The image information captured, is positioned after pretreatment, analyzes the behavior of people in image, including：Walking, direction of travel, stop,
Residence time, expression；And carry out identity discriminating；B is counted demographic data caused by behavioural analysis, and statistics is tied
Fruit, which preserves, to be sent to server（Data center）（3）, the server（Data center）Data interaction is carried out by communication module, should
Monitoring camera（1）With Activity recognition main frame（2）Controlled by comprehensive management platform.
A kind of 3. embedded system based on abnormal behaviour identification as described in claim 1, it is characterised in that the integrated management
Platform（4）Touch-screen including man-machine interaction, the program of man-machine interaction is also stored with the memory of the comprehensive management platform, led to
The actuator for crossing comprehensive management platform performs：In response to the instruction of the man-machine interaction on touch-screen, realize to Activity recognition main frame
The broadcasting of content, the control to camera and with server carry out data interaction；Also include what is be connected with Activity recognition main frame
Internet video module, described internet video module are responsible for compression, decompression and the verification of interaction data.
A kind of 4. embedded system based on abnormal behaviour identification as described in claim 1, it is characterised in that the Activity recognition
Main frame（2）Recognition result performs preset strategy；Described the step of performing preset strategy according to the recognition result, includes：Judge institute
State whether recognition result meets default abnormal behaviour condition；If the recognition result meets default abnormal behaviour condition, to described
Pedestrian corresponding to recognition result carries out emphasis monitoring, while generates alarm.
A kind of 5. embedded system based on abnormal behaviour identification as described in claim 1, it is characterised in that the Activity recognition
Main frame（2）It is the intelligent behavior identification main frame of plug and play.
A kind of 6. embedded system based on abnormal behaviour identification as described in claim 1, it is characterised in that the monitoring camera
Head（1）It is front end high definition monitoring camera.
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| CN201711155914.5A CN107818312A (en) | 2017-11-20 | 2017-11-20 | A kind of embedded system based on abnormal behaviour identification |
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| CN201711155914.5A CN107818312A (en) | 2017-11-20 | 2017-11-20 | A kind of embedded system based on abnormal behaviour identification |
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109766779A (en) * | 2018-12-20 | 2019-05-17 | 深圳云天励飞技术有限公司 | It hovers personal identification method and Related product |
| CN109828545A (en) * | 2019-02-28 | 2019-05-31 | 武汉三工智能装备制造有限公司 | AI intelligent process anomalous identification closed loop control method, host and change system |
| CN110443312A (en) * | 2019-08-07 | 2019-11-12 | 恒锋信息科技股份有限公司 | A kind of municipal administration's method and system based on human body attitude |
| CN110490106A (en) * | 2019-08-06 | 2019-11-22 | 万翼科技有限公司 | Approaches to IM and relevant device |
| CN110555397A (en) * | 2019-08-21 | 2019-12-10 | 武汉大千信息技术有限公司 | crowd situation analysis method |
| CN110782639A (en) * | 2019-10-28 | 2020-02-11 | 深圳奇迹智慧网络有限公司 | Abnormal behavior warning method, device, system and storage medium |
| CN111222370A (en) * | 2018-11-26 | 2020-06-02 | 浙江宇视科技有限公司 | Case studying and judging method, system and device |
| CN111263114A (en) * | 2020-02-14 | 2020-06-09 | 北京百度网讯科技有限公司 | Abnormal event alarm method and device |
| CN111354024A (en) * | 2020-04-10 | 2020-06-30 | 深圳市五元科技有限公司 | Behavior prediction method for key target, AI server and storage medium |
| CN111353414A (en) * | 2020-02-25 | 2020-06-30 | 重庆中科云从科技有限公司 | Identity recognition method, system, machine readable medium and equipment |
| CN111405273A (en) * | 2020-03-02 | 2020-07-10 | 深圳奇迹智慧网络有限公司 | Camera operation and maintenance method and system |
| CN112053563A (en) * | 2020-09-16 | 2020-12-08 | 北京百度网讯科技有限公司 | Event detection method, device, equipment and storage medium for cloud control platform |
| CN112804489A (en) * | 2020-12-31 | 2021-05-14 | 重庆文理学院 | Internet + -based intelligent construction site management system and method |
| WO2022062396A1 (en) * | 2020-09-28 | 2022-03-31 | 深圳市商汤科技有限公司 | Image processing method and apparatus, and electronic device and storage medium |
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111222370A (en) * | 2018-11-26 | 2020-06-02 | 浙江宇视科技有限公司 | Case studying and judging method, system and device |
| CN109766779B (en) * | 2018-12-20 | 2021-07-20 | 深圳云天励飞技术有限公司 | Loitering person identification method and related product |
| CN109766779A (en) * | 2018-12-20 | 2019-05-17 | 深圳云天励飞技术有限公司 | It hovers personal identification method and Related product |
| CN109828545A (en) * | 2019-02-28 | 2019-05-31 | 武汉三工智能装备制造有限公司 | AI intelligent process anomalous identification closed loop control method, host and change system |
| CN109828545B (en) * | 2019-02-28 | 2020-09-11 | 武汉三工智能装备制造有限公司 | AI intelligent process anomaly identification closed-loop control method, host and equipment system |
| CN110490106A (en) * | 2019-08-06 | 2019-11-22 | 万翼科技有限公司 | Approaches to IM and relevant device |
| CN110490106B (en) * | 2019-08-06 | 2022-05-03 | 万翼科技有限公司 | Information management method and related equipment |
| CN110443312A (en) * | 2019-08-07 | 2019-11-12 | 恒锋信息科技股份有限公司 | A kind of municipal administration's method and system based on human body attitude |
| CN110443312B (en) * | 2019-08-07 | 2021-09-21 | 恒锋信息科技股份有限公司 | Urban management method and system based on human body posture |
| CN110555397A (en) * | 2019-08-21 | 2019-12-10 | 武汉大千信息技术有限公司 | crowd situation analysis method |
| CN110782639A (en) * | 2019-10-28 | 2020-02-11 | 深圳奇迹智慧网络有限公司 | Abnormal behavior warning method, device, system and storage medium |
| CN111263114A (en) * | 2020-02-14 | 2020-06-09 | 北京百度网讯科技有限公司 | Abnormal event alarm method and device |
| CN111353414A (en) * | 2020-02-25 | 2020-06-30 | 重庆中科云从科技有限公司 | Identity recognition method, system, machine readable medium and equipment |
| CN111405273A (en) * | 2020-03-02 | 2020-07-10 | 深圳奇迹智慧网络有限公司 | Camera operation and maintenance method and system |
| CN111354024A (en) * | 2020-04-10 | 2020-06-30 | 深圳市五元科技有限公司 | Behavior prediction method for key target, AI server and storage medium |
| CN111354024B (en) * | 2020-04-10 | 2023-04-21 | 深圳市五元科技有限公司 | Behavior prediction method of key target, AI server and storage medium |
| CN112053563A (en) * | 2020-09-16 | 2020-12-08 | 北京百度网讯科技有限公司 | Event detection method, device, equipment and storage medium for cloud control platform |
| WO2022062396A1 (en) * | 2020-09-28 | 2022-03-31 | 深圳市商汤科技有限公司 | Image processing method and apparatus, and electronic device and storage medium |
| CN112804489A (en) * | 2020-12-31 | 2021-05-14 | 重庆文理学院 | Internet + -based intelligent construction site management system and method |
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Application publication date: 20180320 |