CN110602453A - Internet of things big data intelligent video security monitoring system - Google Patents
Internet of things big data intelligent video security monitoring system Download PDFInfo
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- CN110602453A CN110602453A CN201910847313.3A CN201910847313A CN110602453A CN 110602453 A CN110602453 A CN 110602453A CN 201910847313 A CN201910847313 A CN 201910847313A CN 110602453 A CN110602453 A CN 110602453A
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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
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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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
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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Abstract
The invention discloses an Internet of things big data intelligent video security monitoring system which comprises a camera group, a monitoring software system, a central processing unit and a security system, wherein the camera group is respectively connected with the monitoring software system and the central processing unit in a bidirectional mode, and the output end of the central processing unit is connected with the input end of the security system. This thing networking big data intelligence video security protection monitored control system, can carry out face identification to the guest of meeting place through setting up face identification system, face accessible integrity recognition unit to the discernment can not come out discerns, and then the people of face appearance is hidden to the distinguishable carelessness, and the control picture through secondary recognition unit combination other cameras carries out the secondary and discerns the back, can effectual discernment guest's identity and face appearance, and then can warn when suspicious personnel appear in the meeting place, guarantee the safety in meeting place, can prevent in advance, the probability of loss of property has been reduced.
Description
Technical Field
The invention relates to the technical field of monitoring systems, in particular to an Internet of things big data intelligent video security monitoring system.
Background
The monitoring system is one of the most applied systems in the security system, the construction site monitoring system suitable for the market is a handheld video communication device, and video monitoring is the mainstream at present. From the earliest analog monitoring to the digital monitoring of the fire and heat in the previous years to the emerging network video monitoring, the change of the network coverage occurs. Today, the IP technology gradually unifies the world, and it is necessary to reconsider the development history of the video surveillance system. From the technical point of view, the development of video monitoring systems is divided into a first generation analog video monitoring system (CCTV), a second generation digital video monitoring system (DVR) based on 'PC + multimedia card', and a third generation video monitoring system (IPVS) based on an IP network.
The existing monitoring system generally only uses a camera to monitor on-site pictures, the flow of people is large in some important meeting places, and some stealing phenomena can often occur, but the camera in such places is usually placed on the open face, experienced criminals can avoid being shot by the camera in a face-covering mode, and at the moment, the criminals are difficult to track in the later period and are difficult to identify manually.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides an Internet of things big data intelligent video security monitoring system, which solves the problems that in some important meeting places, cameras are placed on the open, experienced criminals can be prevented from being shot by the cameras in a face-covering mode, tracking is difficult in the later period, and identification is performed manually, and the difficulty is high.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: an Internet of things big data intelligent video security monitoring system comprises a camera group, a monitoring software system, a central processing unit and a security system, wherein the camera group is respectively in bidirectional connection with the monitoring software system and the central processing unit, the output end of the central processing unit is connected with the input end of the security system, the security system comprises a face recognition system, a completeness recognition unit, a secondary recognition unit, a feedback module and a warning module, the output end of the face recognition system is connected with the input end of the completeness recognition unit, the output end of the completeness recognition unit is connected with the input end of the secondary recognition unit, the output end of the secondary recognition unit is connected with the input end of the face recognition system, the output ends of the face recognition system, the completeness recognition unit and the secondary recognition unit are connected with the input end of the feedback module, and the output end of the feedback module is respectively connected with the input ends of the central processing unit and the warning module, the output end of the warning module is connected with the input end of the central processing unit.
Preferably, the secondary recognition unit comprises a multi-camera image calling module, an integrity comparison unit, a maximum integrity output module and an image recording module, the output end of the multi-camera image calling module is connected with the input end of the face recognition system, and the output end of the integrity recognition unit is connected with the input end of the integrity comparison unit.
Preferably, the output end of the integrity contrast unit is connected with the input end of the maximum integrity output module, and the output end of the maximum integrity output module is respectively connected with the input ends of the feedback module and the image recording module.
Preferably, the camera group comprises a main camera and a hidden camera, and the main camera and the hidden camera are both provided with N.
Preferably, the monitoring software system comprises a static capture module, a dynamic capture module and a body type recognition system, and the output ends of the static capture module and the dynamic capture module are connected with the input end of the body type recognition system.
Preferably, the body type recognition system comprises a region grid division module, a reference object comparison measurement module, a distance analysis module, a body type metering algorithm and a statistic output module, wherein the output end of the region grid division module is connected with the input end of the reference object comparison measurement module.
Preferably, the output end of the reference object comparison measurement module is connected with the input end of the distance analysis module, the output ends of the distance analysis module and the reference object comparison measurement module are both connected with the input end of the body type metering algorithm, and the output end of the body type metering algorithm is connected with the input end of the statistic output module.
Preferably, the face recognition system comprises a human body feature recognition module, a face image framing module, a face recognition analysis module, a classification output module and an police database, and the output end of the human body feature recognition module is connected with the input end of the face image framing module.
Preferably, the output ends of the face image framing module and the police database are connected with the input end of the face recognition analysis module, and the output end of the face recognition analysis module is connected with the input end of the classification output module.
(III) advantageous effects
The invention provides an Internet of things big data intelligent video security monitoring system. Compared with the prior art, the method has the following beneficial effects:
(1) the output end of the face recognition system, the integrity recognition unit and the output end of the secondary recognition unit are connected with the input end of the feedback module, the output end of the feedback module is respectively connected with the input ends of the central processing unit and the warning module, the output end of the warning module is connected with the input end of the central processing unit, the face recognition system can recognize the face of a guest in a meeting place by arranging the face recognition system, and the face which cannot be recognized can be recognized by the integrity recognition unit, and then can discern the people who hides the face deliberately, and after the control picture that combines other cameras through secondary identification unit carries out the secondary discernment, can effectual discernment guest's identity and face, and then can warn when the suspicious personnel appear in the meeting place, guarantee the safety in meeting place, can prevent in advance, reduced the probability of property loss.
(2) This big data intelligence video security protection monitored control system of thing networking, through making camera group include the main camera and hide the camera, and the main camera all is provided with N with hiding the camera, sets up a plurality of cameras and distributes in the meeting place, can effectively avoid the control dead angle to appear, and hides partial camera, and partial camera is explicit, both can be used to warning the on-the-spot personnel, also can puzzlement suspicious molecule, improves and catches the probability of its complete face.
(3) The Internet of things big data intelligent video security monitoring system is characterized in that the body type identification system comprises an area grid dividing module, a reference object comparison and measurement module, a distance analysis module, a body type metering algorithm and a statistic output module, wherein the output end of the area grid dividing module is connected with the input end of the reference object comparison and measurement module, the output end of the reference object comparison and measurement module is connected with the input end of the distance analysis module, the output ends of the distance analysis module and the reference object comparison and measurement module are both connected with the input end of the body type metering algorithm, the output end of the body type metering algorithm is connected with the input end of the statistic output module, by arranging the body type identification system, a monitored person can be compared with surrounding reference objects by using the reference object comparison and measurement module, the body type parameters of the monitored person are roughly calculated, and the monitoring area of the camera is divided by, the distance can be conveniently and accurately identified, the calculation is carried out by combining the angle, the body shape parameters of the monitored personnel can be more accurately identified, and the follow-up is convenient.
(4) The Internet of things big data intelligent video security monitoring system comprises a human face recognition system, a human face image framing module, a human face recognition analysis module, a classification output module and a police database, wherein the output end of the human face recognition module is connected with the input end of the human face image framing module, the output ends of the human face image framing module and the police database are connected with the input end of the human face recognition analysis module, the output end of the human face recognition analysis module is connected with the input end of the classification output module, the human face recognition system can recognize the shielded face, the recognized human face image can be contrasted and recognized with the police database, if the scene has the person who escapes, the scene is registered in the database, the person can be automatically recognized and warned, and the police can catch the face conveniently.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention;
FIG. 2 is a schematic block diagram of a secondary identification unit of the present invention;
FIG. 3 is a schematic block diagram of a body type recognition system of the present invention;
FIG. 4 is a schematic block diagram of a face recognition system of the present invention;
fig. 5 is a schematic block diagram of the camera group of the present invention.
In the figure, 1-camera group, 11-main camera, 12-hidden camera, 2-monitoring software system, 21-static capture module, 22-dynamic capture module, 23-body type recognition system, 24-area grid division module, 25-reference object comparison measurement module, 26-distance analysis module, 27-body type metering algorithm, 28-statistical output module, 3-central processor, 4-security system, 41-face recognition system, 411-body characteristic recognition module, 412-face image frame selection module, 413-face recognition analysis module, 414-classification output module, 415-police database, 42-integrity recognition unit, 43-secondary recognition unit, 44-feedback module, etc, 45-warning module, 46-multi-camera image retrieval module, 47-integrity contrast unit, 48-maximum integrity output module and 49-image recording module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, an embodiment of the present invention provides a technical solution: the utility model provides an thing networking big data intelligence video security protection monitored control system, including camera group 1, monitoring software system 2, central processing unit 3 and security protection system 4, camera group 1 includes main camera 11 and hidden camera 12, and main camera 11 and hidden camera 12 all are provided with N, set up a plurality of cameras and distribute in the meeting place, can effectively avoid monitoring the dead angle that appears, and hide part of camera, and part camera is explicit, both can be used to warn the field personnel, also can puzzlement suspicious molecule, improve and catch the probability of its complete face, monitoring software system 2 includes static capture module 21, dynamic capture module 22 and size identification system 23, static capture module 21 and dynamic capture module 22 can catch personnel's dynamic image and static image respectively, preferably static image when image identification contrast, can improve the accuracy, the output of static capture module 21 and dynamic capture module 22 all is connected with the input of size identification system 23 The figure recognition system 23 comprises an area grid dividing module 24, a reference object comparison measuring module 25, a distance analysis module 26, a figure metering algorithm 27 and a statistic output module 28, wherein the output end of the area grid dividing module 24 is connected with the input end of the reference object comparison measuring module 25, the output end of the reference object comparison measuring module 25 is connected with the input end of the distance analysis module 26, the output ends of the distance analysis module 26 and the reference object comparison measuring module 25 are both connected with the input end of the figure metering algorithm 27, the output end of the figure metering algorithm 27 is connected with the input end of the statistic output module 28, by arranging the figure recognition system 23, the monitored person can be compared with surrounding reference objects by using the reference object comparison measuring module 25, the figure parameter of the monitored person can be roughly calculated, the monitoring area of the camera is divided by grids, and the distance can be conveniently and accurately recognized, the body shape parameters of the monitored personnel can be more accurately identified by combining the calculation of angles, the later period tracing is convenient, the camera group 1 is respectively and bidirectionally connected with the monitoring software system 2 and the central processing unit 3, the output end of the central processing unit 3 is connected with the input end of the security system 4, the security system 4 comprises a face recognition system 41, an integrity recognition unit 42, a secondary recognition unit 43, a feedback module 44 and a warning module 45, the face recognition system 41 comprises a human body feature recognition module 411, a face image framing module 412, a face recognition analysis module 413, a classification output module 414 and an alarm database 415, the output end of the human body feature recognition module 411 is connected with the input end of the face image framing module 412, the output ends of the face image framing module 412 and the alarm database 415 are connected with the input end of the face recognition analysis module 413, the output end of the face recognition analysis module 413 is connected with the input end of the classification output module 414, the face recognition system 41 can recognize the person with the face being shielded, and can also compare the recognized face image with the police database 415 for recognition, if there is a person in the bank that is escaping, it can automatically recognize and warn, and is convenient for the police to catch, the secondary recognition unit 43 includes a multi-camera image calling module 46, an integrity comparison unit 47, a maximum integrity output module 48 and an image recording module 49, the output end of the multi-camera image calling module 46 is connected with the input end of the face recognition system 41, the output end of the integrity recognition unit 42 is connected with the input end of the integrity comparison unit 47, the output end of the integrity comparison unit 47 is connected with the input end of the maximum integrity output module 48, the output end of the maximum integrity output module 48 is respectively connected with the input ends of the feedback module 44 and the image recording module 49, the output end of the face recognition system 41 is connected with the input end of the integrity recognition unit 42, the output end of the integrity recognition unit 42 is connected with the input end of the secondary recognition unit 43, the output end of the secondary recognition unit 43 is connected with the input end of the face recognition system 41, the output ends of the face recognition system 41, the integrity recognition unit 42 and the secondary recognition unit 43 are all connected with the input end of the feedback module 44, the output end of the feedback module 44 is respectively connected with the input ends of the central processor 3 and the warning module 45, the output end of the warning module 45 is connected with the input end of the central processor 3, the face recognition system 41 can recognize faces of guests at a meeting place, the unrecognized faces can be recognized through the integrity recognition unit 42, people intentionally hiding faces can be recognized, and after the secondary recognition is carried out by combining the secondary recognition unit 43 with monitoring pictures of other cameras, the identity and the face of the guests can be effectively recognized, furthermore, the monitoring system can warn when suspicious people appear in the meeting place, ensure the safety of the meeting place, prevent in advance and reduce the probability of property loss.
And those not described in detail in this specification are well within the skill of those in the art.
When the system is used, the camera group 1 monitors the scene in real time, the picture is transmitted to a monitoring room, the picture data is transmitted to the face recognition system 41 through the central processing unit 3 of the control host, the human body feature recognition module 411 recognizes people in the picture according to the human body feature parameters, the face image framing module 412 frames out the face images of the people for amplification recognition, the images which cannot be recognized by the face recognition analysis module 413 are transmitted to the integrity recognition unit 42, the recognized face images can be compared with the images in the police database 415, and if people escaping from the police are recognized, the warning information can be sent out through the warning module 45.
The integrity recognition unit 42 analyzes and processes the received image, recognizes the integrity of the face image, transmits the face image with integrity lower than 60% to the secondary recognition unit 43, the multi-camera image retrieving module 46 in the secondary recognition unit 43 retrieves the image of the same person from other cameras, and then the integrity of each face image is obtained after face recognition and integrity recognition, the data is compared by an integrity comparison unit 47 to find out the image with the maximum integrity representing the face of the person, then, the image recording module 49 records the image, if the integrity of the image is still less than 60%, it means that the person conceals his face intentionally, the information can be fed back to the warning module 45 through the feedback module 44, warning information is sent to the central processing unit 3, security personnel need to pay attention to the dynamic state of the personnel, and field confirmation can be carried out if the personnel need to be used.
For the suspicious recorded people, the camera group 1 detects the distance of the people according to the monitoring areas divided by the area grid dividing module 24, further calculates the included angle between the camera and the people according to the pythagorean theorem, further calculates the actual data according to the height data in the image, if the lower limbs of the people are blocked and the complete height cannot be identified, the approximate height data of the people can be identified according to the nearby reference object, and then the statistic output module 28 transmits the data to record and stores the data together with the image.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. The utility model provides an thing networking big data intelligence video security protection monitored control system, includes camera group (1), monitoring software system (2), central processing unit (3) and security protection system (4), camera group (1) realizes the both way junction with monitoring software system (2) and central processing unit (3) respectively, the output of central processing unit (3) is connected its characterized in that with the input of security protection system (4): the security system (4) comprises a face recognition system (41), an integrity recognition unit (42), a secondary recognition unit (43), a feedback module (44) and a warning module (45), the output end of the face recognition system (41) is connected with the input end of the integrity recognition unit (42), the output end of the integrity recognition unit (42) is connected with the input end of the secondary recognition unit (43), the output end of the secondary recognition unit (43) is connected with the input end of the face recognition system (41), the output ends of the face recognition system (41), the integrity recognition unit (42) and the secondary recognition unit (43) are all connected with the input end of the feedback module (44), the output end of the feedback module (44) is respectively connected with the input ends of the central processing unit (3) and the warning module (45), the output end of the warning module (45) is connected with the input end of the central processing unit (3).
2. The Internet of things big data intelligent video security monitoring system according to claim 1, characterized in that: the secondary recognition unit (43) comprises a multi-camera image calling module (46), a completeness comparison unit (47), a maximum completeness output module (48) and an image recording module (49), the output end of the multi-camera image calling module (46) is connected with the input end of the face recognition system (41), and the output end of the completeness recognition unit (42) is connected with the input end of the completeness comparison unit (47).
3. The Internet of things big data intelligent video security monitoring system according to claim 2, characterized in that: the output end of the integrity contrast unit (47) is connected with the input end of a maximum integrity output module (48), and the output end of the maximum integrity output module (48) is respectively connected with the input ends of a feedback module (44) and an image recording module (49).
4. The Internet of things big data intelligent video security monitoring system according to claim 1, characterized in that: the camera group (1) comprises a main camera (11) and a hidden camera (12), and N cameras are arranged on the main camera (11) and the hidden camera (12).
5. The Internet of things big data intelligent video security monitoring system according to claim 1, characterized in that: the monitoring software system (2) comprises a static capture module (21), a dynamic capture module (22) and a body type recognition system (23), wherein the output ends of the static capture module (21) and the dynamic capture module (22) are connected with the input end of the body type recognition system (23).
6. The Internet of things big data intelligent video security monitoring system according to claim 1, characterized in that: the body type recognition system (23) comprises an area grid dividing module (24), a reference object comparison measuring module (25), a distance analysis module (26), a body type metering algorithm (27) and a statistic output module (28), wherein the output end of the area grid dividing module (24) is connected with the input end of the reference object comparison measuring module (25).
7. The Internet of things big data intelligent video security monitoring system according to claim 1, characterized in that: the output end of the reference object comparison measurement module (25) is connected with the input end of the distance analysis module (26), the output ends of the distance analysis module (26) and the reference object comparison measurement module (25) are both connected with the input end of a body type measurement algorithm (27), and the output end of the body type measurement algorithm (27) is connected with the input end of a statistic output module (28).
8. The Internet of things big data intelligent video security monitoring system according to claim 1, characterized in that: the human face recognition system (41) comprises a human body feature recognition module (411), a human face image framing module (412), a human face recognition analysis module (413), a classification output module (414) and a police database (415), wherein the output end of the human body feature recognition module (411) is connected with the input end of the human face image framing module (412).
9. The Internet of things big data intelligent video security monitoring system according to claim 8, characterized in that: the output ends of the face image frame selection module (412) and the police database (415) are both connected with the input end of the face recognition analysis module (413), and the output end of the face recognition analysis module (413) is connected with the input end of the classification output module (414).
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