CN208691422U - Recognition of face monitoring camera - Google Patents
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- CN208691422U CN208691422U CN201821062115.3U CN201821062115U CN208691422U CN 208691422 U CN208691422 U CN 208691422U CN 201821062115 U CN201821062115 U CN 201821062115U CN 208691422 U CN208691422 U CN 208691422U
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Abstract
The utility model provides a kind of recognition of face monitoring camera, including holder and camera body, camera body is movably connected on holder, camera body includes optical lens, imaging sensor, high-definition digital video controller, facial image pretreatment and candid photograph module, image cache module and network interface, the optical signal of light camera lens is converted to digital signal by imaging sensor, imaging sensor gives the digital data transmission of conversion to high-definition digital video controller, high-definition digital video controller connects facial image pretreatment and captures module, facial image pretreatment and candid photograph module pass through image cache module connection network interface；The utility model can be effectively reduced monitoring cost, and the data volume transmitted needed for greatly reducing improves transmission efficiency；Camera holder can be controlled and valuable face is amplified in optical lens tracking, optimum state candid photograph is carried out, provide the facial image of high value for the backstage recognition of face server or portable equipment in a distant place.
Description
Technical field
The utility model relates to a kind of recognition of face monitoring cameras.
Background technique
Existing recognition of face server can accomplish the comparison of two face pictures, usually a face photographed in real time
The standard certificate photograph of image and a lane database compares, and finding out this present people is whom, such as airport and high-speed rail station,
It is required that passenger takes pictures the face safety check camera sufficiently long time, then compared with the identity card of submission, confirmation is the same person.
However, in more application scenarios, such as public place monitoring system and crime scene investigation device etc., it is impossible to it is required that each
The people passed by stands to a bat standard photograph before camera, then waits server is allowed to identify within tens seconds.In monitoring system and hold
On method instrument, the image that camera obtains is intricate, fast changing, and many times face is all invisible at all.And it images
How high resolution digital video image is sent to recognition of face server all far from control platform by the position of head installation, and
How to obtain facial image is the bottleneck that monitoring system realizes recognition of face.
To solve the problems, such as high resolution digital video image transmitting, there are two types of present ways, and one is face is known
Other server is put into the place of camera installation, and the high resolution video image of camera is directly accessed server and carries out to image
Processing and identification；Another method is that after the high-definition digital video image of camera is handled into overcompression, have by dedicated
Line high-speed channel is sent to the control platform in a distant place, then is linked into recognition of face server and is handled and identified.
The above both methods is not able to satisfy the requirement of practical application.In former scheme, each camera exists
One expensive server of in-site installation is unrealistic, and the database in server is very high certificate of confidentiality requirement etc.
Information, it is easy to cause to divulge a secret, along with the content of these databases is controlled by control platform, that is to say, that these distributions
It must be connected with the Intranet of control platform in the server of each camera, this is not able to satisfy the requirement of network security.Latter
In kind scheme, since the data volume of digital video image is very big, the data of 4K high resolution video image 12Gb about per second.
Data volume big in this way cannot be transmitted in existing telecommunication path, need to be compressed to original thousand with the compression algorithms such as H.265
/ mono- in dedicated wired paths hereinafter, could transmit.But high resolution video image is after overcompression, image it is thin
Section is largely lost, and significantly reduces the accuracy of recognition of face, especially when there is multiple faces in image, each face
Information content compressed after can not identify.In the wearable devices such as crime scene investigation device, since transmission mode can only be wireless, and
It can only be battery power supply, image transmitting problem is more serious, and the video image of camera needs a ten thousandth or less to be possible to
Transmission.And wireless transmission expense is very high, is not able to satisfy real requirement.
Refering to what is shown in Fig. 1, Fig. 1 is the structural schematic diagram of existing face identification system, server and Image Acquisition camera
In the same place, server is filtered camera acquired image, object separation, the processing such as Face datection, people
It after face is separated, is compared with the picture of identity card, confirmation is the same person.Such system structure can be used for airport and
The special safety check bayonet such as high-speed rail has enough spaces, there is special messenger guard because these places belong to special harbor,
Server and database are all relatively safer.But such system cannot be used in public place monitoring system, such as road, square,
The places such as market, the place for installing camera do not have place to put server.Even if there is place to put server, there is also very big peaces
Full hidden danger, is not able to satisfy application requirement.Especially server needs to be connected to the network with the control platform in a distant place, on these networks
The data such as certificate belong to private data, and the data that external equipment accesses these Intranets will cause many security breaches, violate number
According to security regulations.
Refering to what is shown in Fig. 2, indicating the structural schematic diagram of another existing face identification system, Image Acquisition camera passes through
Private telecommunication network sends video image to the control platform in a distant place, and server is filtered camera acquired image, object
Body separation, the processing such as Face datection, after face is separated, is compared with the picture of identity card, finds out the detailed of passing people
Thin information.But high-resolution digital video image is transferred to a distant place, it is necessary to calculate by a large amount of compressions, such as H.265 etc.
Data volume is compressed to original one thousandth hereinafter, can only many times see the result is that a large amount of details of image are lost by method
To the fuzzy shadow, the accuracy of recognition of face is not caused to seriously affect.And in such system image delay it is very long,
Usually want several seconds, etc. control platforms when identifying face, examined people has had been moved off scene, is not able to satisfy high request
Face recognition application.
In both the above system structure, server spends a large amount of calculation resources to be used to handle high-resolution digital view
Frequently, 100 twentieth images can only be handled in this way, that is to say, that a possibility that detecting face in image is small
In 1%, it requires that face face camera is greater than two seconds time, can just find an effective facial image.
Recognition of face is an extremely complex and time-consuming process, it is desirable that high performance server hardware and artificial intelligence are soft
Part.By existing computing capability, the digital picture of a 4K resolution ratio is handled, it is determined whether with the presence of identifiable face, greatly
It is general to need 2 seconds, if there is identifiable face exists, face is separated, is treated as to be compared with certificate photograph
Pair format, each facial image probably needs 1 second.Later using the photo on complicated intelligent algorithm and certificate into
Row compares, it is determined whether consistent.However digital video is 60 width image per second, this results in recognition of face server can only be every
Piece image is handled in 120 width images.This processed image is entirely random inside video flowing.That is it is
Guarantee that finding the facial image people that one can be used in identification comparison must keep face face camera 2 seconds or more.Then pass through
Can determine within several seconds whether face is consistent with certificate.This can satisfy the application on airport and high-speed rail safe examination system, can require
Each passenger's face is imaged several leading second and is identified.But in the wearable devices such as public's monitoring system and crime scene investigation device, in this way
Be not required to meet.There are many people in video image, and all ceaselessly moving, in face of the chance little time of camera
It is very short.Piece image in 120 width image of recognition of face server random process, can find the chance for the face that can be identified
Very little, and many computing resources are wasted for handling nugatory image.
The above problem should be paid attention to and be solved the problems, such as during the video monitoring of mobile population.
Utility model content
The purpose of the utility model is to provide a kind of recognition of face monitoring camera solve it is existing in the prior art how
The problem of high resolution video surveillance is carried out to mobile population at a lower cost.
The technical solution of the utility model is:
A kind of recognition of face monitoring camera, including holder and camera body, camera body are movably connected in holder
On, camera body includes optical lens, imaging sensor, high-definition digital video controller, facial image pretreatment and captures
The optical signal of light camera lens is converted to digital signal by module, image cache module and network interface, imaging sensor, and image passes
Sensor gives the digital data transmission of conversion to high-definition digital video controller, and it is pre- that high-definition digital video controller connects facial image
Processing and candid photograph module, facial image pretreatment and candid photograph module connect network interface by image cache module.
Further, holder uses electric platform, facial image pretreatment and candid photograph module control electric platform rotation.
Further, optical lens uses motorized light camera lens, and facial image pretreatment and candid photograph module control electronic light
Learn lens focusing.
Further, network interface is communicated by telecommunications network with control platform.
Further, optical lens and the collected real-time digital video of imaging sensor are controlled by high-definition digital video
Device accesses facial image pretreatment and captures module；Facial image pretreatment and candid photograph module pre-process real-time digital video
Afterwards, the image that can be used for the face of matching identification is filtered out, or best shape is captured by control holder and optical lens tracking
The facial image of state, then facial image pre-processes and captures module for the figure of the face that can be used for matching identification filtered out
Picture cache by image cache module and sends control platform to by network interface.
Further, facial image pretreatment and candid photograph module carry out image preprocessing to real-time digital video, specifically,
Using the foreground and background of differential technique separation original image, the middle foreground image of original image and background image are divided
From obtaining foreground image, the boundary profile that convolution algorithm finds out object carried out to foreground image and high-pass filtering template, according to wheel
Wide continuity and closure isolates independent object, and the image of each object is normalized, then special with face
It levies template and carries out convolution algorithm, obtain subject image.
Further, facial image pretreatment and candid photograph module filter out the image that can be used for the face of matching identification, have
Body is, after carrying out image preprocessing to real-time digital video, obtains subject image, judges whether the subject image is positive dough figurine
Face, if clarity is not less than setting value, filters out if so, seeing the clarity of facial image again and can be used for matching identification
Face image.
Further, facial image pretreatment and candid photograph module capture optimum state facial image, specifically, to real-time
After digital video carries out image preprocessing, subject image is obtained, judges whether the subject image is front face, if so, again
See the clarity of facial image, if clarity is lower than setting value, control holder is directed at the face location, and controls optical lens
Amplify and focus on the face, then according to facial image and positive eye opening skin detection convolution as a result, capture is best
The facial image of state.
Further, facial image is pre-processed and is captured in module, after carrying out image preprocessing to real-time digital video, is obtained
To subject image, judge whether the subject image is front face, is not front face if it is the subject image, then deleting should
Subject image.
Further, control platform receives the facial image of transmission by telecommunications network, accesses face server to these people
Face image is identified.
The beneficial effects of the utility model are:
One, this kind of recognition of face monitoring camera, can be effectively reduced monitoring cost, the number transmitted needed for greatly reducing
According to amount, transmission efficiency is improved, the face recognition accuracy rate and speed of monitoring system are improved.This kind of recognition of face monitoring camera,
Camera holder can be controlled and valuable face is amplified in optical lens tracking, optimum state candid photograph is carried out, for behind a distant place
Platform recognition of face server or portable equipment provide the facial image of high value.This kind of recognition of face monitoring camera, Neng Gou
In the digital video image of high-resolution or ultrahigh resolution, facial image is found out in real time, and is sent backstage to and carried out at identification
Reason.
Two, the utility model utilizes high-speed figure image processing techniques, the real-time digital in recognition of face camera locality
People face image is separated from background image in video, control recognition of face camera tracks and amplifies valuable people
Face captures when obtaining complete clearly people face image and saves the people face image, and pass through the communication networks such as mobile phone wireless net,
People face image is sent to distant place background server and identifies, carries out the pretreatment of front end High-speed video images for face identification system,
Clearly people face image is screened and captured, greatlys improve the efficiency of backstage human bioequivalence server, and filter out and account about video
The rubbish image of total amount of data 99.99%, communication bandwidth needed for well solving thecamera head to distant place background server and figure
The contradiction of image sharpness.
Three, in the utility model, the collected digital video of recognition of face monitoring camera accesses preprocessed chip, passes through
After real-time digital video pretreatment, effective facial image is filtered out, or control holder and optical lens tracking are captured most preferably
Facial image is transferred to control platform by telecommunications network then these effective images, accesses face server to these figures
As being identified.For digital video image after screening, effective face image data about only has original video data amount
Existing telecommunication network or wireless network transmissions can be effectively utilized in a ten thousandth.And since camera completes object
The work such as body identification and facial image screening, recognition of face server can be sufficiently used for operational capability face alignment identification etc.
Follow-up work, a server can handle the input picture of multiple cameras, and the fund of expensive server is greatly saved
Investment.
Detailed description of the invention
Fig. 1 is structural schematic diagram of the existing recognition of face server in the local system of monitoring.
Fig. 2 is the structural schematic diagram of system of the existing recognition of face server in control platform.
Fig. 3 is the illustrative view of functional configuration of the utility model face identification system.
Fig. 4 is that mobile population video monitoring system of the embodiment based on recognition of face illustrates schematic diagram.
Fig. 5 is that recognition of face monitoring camera illustrates schematic diagram in the utility model embodiment.
Fig. 6 is the flow diagram of the image pre-processing method of facial image pretreatment and candid photograph module in embodiment.
Specific embodiment
The preferred embodiment that according to the present invention will be described in detail below with reference to the accompanying drawings.
Embodiment
A kind of recognition of face monitoring camera, such as Fig. 4, including holder and camera body, camera body are flexibly connected
On holder, camera body includes optical lens, imaging sensor, high-definition digital video controller, facial image pretreatment
And capture module, image cache module and network interface, imaging sensor and the optical signal of light camera lens is converted into digital signal,
Imaging sensor gives the digital data transmission of conversion to high-definition digital video controller, and high-definition digital video controller connects face
Image preprocessing and candid photograph module, facial image pretreatment and candid photograph module connect network interface by image cache module.
This kind of recognition of face monitoring camera, can be effectively reduced monitoring cost, the data transmitted needed for greatly reducing
Amount improves transmission efficiency, improves the face recognition accuracy rate and speed of monitoring system.This kind of recognition of face monitoring camera, energy
It enough controls camera holder and valuable face is amplified in optical lens tracking, carry out optimum state candid photograph, be the backstage in a distant place
Recognition of face server or portable equipment provide the facial image of high value.This kind of recognition of face monitoring camera, can be in height
In the digital video image of resolution ratio or ultrahigh resolution, facial image is found out in real time, and is sent backstage to and carried out identifying processing.
In embodiment, holder uses electric platform, facial image pretreatment and candid photograph module control electric platform rotation.Light
It learns camera lens and uses motorized light camera lens, facial image pretreatment and candid photograph module control motorized light lens focusing.Network interface
It is communicated by telecommunications network with control platform.
This kind of recognition of face monitoring camera can be used for matching identification to the image of real-time digital video after screening
Face image data about only have original video data amount a ten thousandth, existing telecommunication network can be effectively utilized
Or wireless network transmissions.And since recognition of face monitoring camera completes the works such as object identification and facial image screening
Make, recognition of face server can be sufficiently used for operational capability the follow-up works such as face alignment identification, and server can be with
The capital investment of expensive server is greatly saved in the input picture for handling multiple cameras.This kind of recognition of face monitoring is taken the photograph
As head, it is able to solve the high resolution video image transmission problem encountered in recognition of face and effective facial image Trapped problems.
This kind of recognition of face monitoring camera can be found out and be captured in huge video image data and be known to face
Not valuable facial image provides important to screen out a large amount of repetition, unwanted picture for backstage recognition of face server
Clearly image, recognition speed and accuracy is greatly improved.
In embodiment, optical lens and the collected real-time digital video of imaging sensor are controlled by high-definition digital video
Device accesses facial image pretreatment and captures module.Facial image pretreatment and candid photograph module pre-process real-time digital video
Afterwards, the image that can be used for the face of matching identification is filtered out, or best shape is captured by control holder and optical lens tracking
The facial image of state, then facial image pre-processes and captures module for the figure of the face that can be used for matching identification filtered out
Picture cache by image cache module and sends control platform to by network interface.
Such as Fig. 4, embodiment pre-processes facial image and captures module and recognition of face monitoring camera is integrated.?
In such system, the collected real-time digital video access facial image pretreatment of camera and candid photograph module, by real-time
After digital video pretreatment, the image that can be used for the face of matching identification, or control holder and optical lens tracking are filtered out
Best facial image is captured, then these effective images, control platform is transferred to by telecommunications network, accesses face server
These images are identified.
In embodiment, optical lens accesses 4K high-resolution image sensors, and imaging sensor converts light image signal
At electric signal, by high-definition digital video controller, image signal encoding is become per second 50 or 60 width digital videos, then
It accesses facial image pretreatment and captures module.Face in facial image pretreatment and the candid photograph every piece image of block search,
If face is clear enough, there are enough pixels, just send the face to the facial image cache module of rear class, then passes through network
Interface is sent to control platform.Control platform accesses recognition of face server and carries out face alignment.
In embodiment, such as Fig. 6, facial image pretreatment and candid photograph module carry out image preprocessing to real-time digital video,
Specifically, using the foreground and background of differential technique separation original image, by the middle foreground image and background image of original image
It is separated, obtains foreground image, the boundary profile that convolution algorithm finds out object is carried out to foreground image and high-pass filtering template,
Independent object is isolated according to the continuity of profile and closure, the image of each object is normalized, then with
Skin detection carries out convolution algorithm, obtains subject image.
Facial image pretreatment and candid photograph module filter out the image that can be used for the face of matching identification, specifically, right
After real-time digital video carries out image preprocessing, subject image is obtained, judges whether the subject image is front face, if
It is, then sees the clarity of facial image, if clarity is not less than setting value, filters out the face that can be used for matching identification
Image.
Facial image pretreatment and candid photograph module capture optimum state facial image, specifically, to real-time digital video
After carrying out image preprocessing, subject image is obtained, judges whether the subject image is front face, if so, seeing face figure again
The clarity of picture, if clarity is lower than setting value, control holder is directed at the face location, and controls optical lens and amplify and gather
Coke arrives the face, then according to facial image and positive eye opening skin detection convolution as a result, the people of capture optimum state
Face image.
In facial image pretreatment and candid photograph module, after carrying out image preprocessing to real-time digital video, object figure is obtained
Picture judges whether the subject image is front face, is not front face if it is the subject image, then deletes the object figure
Picture.
In embodiment, high resolution video image filters big into after the facial image pretreatment for crossing front end and capturing module
The independent image data of amount, only screens and captures high-resolution facial image and be sent to distant place control platform, significantly reduces
The data volume of required transmission, while the facial image of high quality is provided, the burden of background server is alleviated, it can be meter
It calculates process resource and is used for recognition of face, improve recognition efficiency and speed.
In embodiment, facial image pretreatment and candid photograph module are integrated into recognition of face monitoring camera in front, directly handle
Raw digital video image, using the foreground and background of differential technique separate picture, to foreground image and high-pass filtering template into
Row convolution algorithm finds out the boundary profile of object, independent object is isolated according to the continuity of profile and closure, to each
The image of object is normalized, then carries out convolution algorithm with skin detection, judges whether the object is positive dough figurine
Face, if clarity is inadequate, just controls holder and is directed at the face location, and control if it is the clarity for seeing facial image again
Optical lens amplifies and focuses on the face, then according to facial image and positive eye opening skin detection convolution as a result,
Optimum state facial image is captured, the further identifying processing of distant place background server is then passed to.It can be realized processing per second 60
The high resolution video image of width 4K handles every piece image in real time, finds any useful human face image information, and can
In the case where piece image up to 80 facial images, quickly control holder and optical lens capture each valuable respectively
People face image.
In embodiment, the high-definition digital image of 60 width 4K resolution ratio of real-time processing per second is realized using high speed ASIC, to figure
As carrying out calculus of differences wiping out background image, then carries out convolutional filtering and extract contour of object, multiple objects are isolated from image
The object separated is compared with face characteristic for body, excludes non-face object, thus people face from video image
It separates, up to 80 people faces can be discerned from each image.
After facial image is detected and separated from video, the angle of face and camera is judged according to face characteristic
Degree, picks out the face in face camera direction, controls the holder tracking of camera, alignment, and adjust optical lens focusing, puts
The big face, captures the facial image in the optimal situation of face state.
A kind of mobile population video monitoring system based on recognition of face using above-mentioned recognition of face monitoring camera, such as
Fig. 3, including front end surveillance device and control platform.
Front end surveillance device: real-time digital video is collected by recognition of face monitoring camera, to real-time digital video
In original image pre-processed, filter out the image that can be used for the face of matching identification, acquisition can be used for comparing knowledge
The image of other face sends control platform to by telecommunications network.
Control platform: by telecommunications network receive transmission facial image, access face server to these facial images into
Row identification.
Mobile population video monitoring system of this kind based on recognition of face, face identification system according to function and complicated journey
Degree is divided into front end surveillance device and control platform two parts: front end surveillance device carries out high resolution digital video image preprocessing
With backstage recognition of face control platform, enable front end in the place that image generates, before being transmitted to video image processing,
Valuable facial image is filtered out, 99.9% or more hash is filtered, and controls holder and optical lens, captures high definition
The facial image of clear degree only into excessively wired or wireless channel sends valuable image to the background server in a distant place, to people
Face image is carried out into a processing and identification.
With reference to shown in Fig. 3 and Fig. 4, embodiment proposes handle for emerging recognition of face and the demand of artificial intelligence vision
The method that face snap and digital image video pretreatment are realized with special chip, and video pre-filtering be integrated into camera,
In crime scene investigation device and wearable device, after the high quality facial image shearing that then candid photograph is arrived, by wired or wireless network
It is sent to the system structure that a distant place control platform facial image is compared identification.In such a system, optical system and height
The digital video image that image in different resolution sensing acquisition arrives filters out valuable facial image, and control by processing in real time
Optical lens and holder track and capture the facial image of high quality, greatly reduce the data volume for needing to transmit, share a distant place
The video processing load of the backstage recognition of face server of control platform, is greatly improved facial image recognition speed, accuracy and
Efficiency.
And than that described above, it is also necessary to which explanation is " one embodiment " spoken of in the present specification, " another reality
Apply example ", " embodiment " etc., refer to specific features, structure or the feature of embodiment description is combined to be included in the application general
In at least one embodiment of including property description.In the description multiple places occur statements of the same race be not centainly refer to it is same
Embodiment.Furthermore, it is understood that when describing a specific features, structure or feature in conjunction with any embodiment, what is advocated is
Realize that this feature, structure or feature are also fallen in the scope of the utility model in conjunction with other embodiments.
Although reference be made herein to the utility model is described in multiple explanatory embodiments of the utility model, still,
It should be understood that those skilled in the art can be designed that a lot of other modification and implementations, these modifications and implementations
It will fall within scope and spirit disclosed in the present application.More specifically, it discloses in the application, drawings and claims
In range, can building block to theme combination layout and/or layout carry out a variety of variations and modifications.In addition to building block
And/or outside the variations and modifications of layout progress, to those skilled in the art, other purposes also be will be apparent.
Claims (4)
1. a kind of recognition of face monitoring camera, it is characterised in that: including holder and camera body, camera body activity connects
It connects on holder, camera body includes that optical lens, imaging sensor, high-definition digital video controller, facial image are located in advance
The optical signal of light camera lens is converted to digital letter by reason and candid photograph module, image cache module and network interface, imaging sensor
Number, imaging sensor gives the digital data transmission of conversion to high-definition digital video controller, the connection of high-definition digital video controller
Facial image pretreatment and candid photograph module, facial image pretreatment and candid photograph module connect network by image cache module and connect
Mouthful.
2. recognition of face monitoring camera as described in claim 1, which is characterized in that holder uses electric platform, face figure
As pre-processing and capturing module control electric platform rotation.
3. recognition of face monitoring camera as claimed in claim 1 or 2, which is characterized in that optical lens uses motorized light
Camera lens, facial image pretreatment and candid photograph module control motorized light lens focusing.
4. recognition of face monitoring camera as claimed in claim 1 or 2, which is characterized in that network interface by telecommunications network with
Control platform communication.
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| CN113658354A (en) * | 2021-08-27 | 2021-11-16 | 深圳市奥赛克科技有限公司 | Take control system's vehicle event data recorder |
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| CN113658354A (en) * | 2021-08-27 | 2021-11-16 | 深圳市奥赛克科技有限公司 | Take control system's vehicle event data recorder |
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