CN108960146A - The image pre-processing method of recognition of face monitor video - Google Patents
The image pre-processing method of recognition of face monitor video Download PDFInfo
- Publication number
- CN108960146A CN108960146A CN201810731822.5A CN201810731822A CN108960146A CN 108960146 A CN108960146 A CN 108960146A CN 201810731822 A CN201810731822 A CN 201810731822A CN 108960146 A CN108960146 A CN 108960146A
- Authority
- CN
- China
- Prior art keywords
- image
- face
- recognition
- digital video
- real
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
- G06V40/161—Detection; Localisation; Normalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
-
- 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
- G06V40/168—Feature extraction; Face representation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Processing (AREA)
- Image Analysis (AREA)
- Studio Devices (AREA)
Abstract
The present invention provides a kind of image pre-processing method of recognition of face monitor video, collects real-time digital video, pre-processes to the original image in real-time digital video, filters out the image that can be used for the face of matching identification；Utilize the foreground and background of differential technique separation original image, the middle foreground image of original image is separated with background image, obtain 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 carries out convolution algorithm with skin detection, obtains subject image.The present invention can be in the digital video image of ultrahigh resolution, facial image is found out in real time, the facial image of high value is provided for the backstage recognition of face server or portable equipment in a distant place, the data volume transmitted needed for greatly reducing improves the face recognition accuracy rate and speed of monitoring system.
Description
Technical field
The present invention relates to a kind of image pre-processing methods of recognition of face monitor video.
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.
Summary of the invention
The object of the present invention is to provide a kind of image pre-processing methods of recognition of face monitor video to solve in the prior art
Existing the problem of how fast and accurately high resolution video surveillance being carried out to mobile population.
The technical solution of the invention is as follows:
A kind of image pre-processing method of recognition of face monitor video, collects real-time digital video, in real-time digital video
Original image pre-processed, filter out the image that can be used for the face of matching identification；
Image preprocessing is carried out to real-time digital video, specifically, using the foreground and background of differential technique separation original image,
The middle foreground image of original image is separated with background image, obtains foreground image, to foreground image and high-pass filtering mould
Plate carries out the boundary profile that convolution algorithm finds out object, isolates independent object according to the continuity of profile and closure, right
The image of each object is normalized, then carries out convolution algorithm with skin detection, obtains subject image；
The image that can be used for the face of matching identification is filtered out, specifically, after carrying out image preprocessing to real-time digital video,
Subject image is obtained, judges whether the subject image is front face, if so, the clarity of facial image is seen again, if clearly
Clear degree is not less than setting value, then filters out the image that can be used for the face of matching identification.
Further, after carrying out image preprocessing to real-time digital video, subject image is obtained, judges the subject image
It whether is front face, if so, the clarity of facial image is seen again, if clarity is lower than setting value, control holder alignment
The face location, and control optical lens and amplify and focus on the face, it is then special according to facial image and positive eye opening face
Levy mask convolution as a result, capture optimum state facial image.
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, the image of the face that can be used for matching identification of acquisition is sent to control platform by telecommunications network；
Control platform passes through the facial image that telecommunications network receiving front-end monitoring device transmits, and accesses face server to these facial images
It is identified.
The beneficial effects of the present invention are:
One, the image pre-processing method of this kind of recognition of face monitor video, can in the digital video image of ultrahigh resolution,
Facial image is found out in real time, and controls camera holder and the valuable face of optical lens tracking amplification, carries out optimum state
It captures, provides the facial image of high value for the backstage recognition of face server or portable equipment in a distant place, needed for greatly reducing
The data volume of transmission improves the face recognition accuracy rate and speed of monitoring system.
Two, the present invention utilizes high-speed figure image processing techniques, the real-time digital video in recognition of face camera locality
Middle that people face image is separated from background image, control recognition of face camera tracks and amplifies valuable people face, when
When obtaining complete clearly people face image, captures and save the people face image, and by communication networks such as mobile phone wireless nets, people face figure
It is identified as being sent to distant place background server, carries out the pretreatment of front end High-speed video images for face identification system, screening is simultaneously
Capture clearly people face image, greatlys improve the efficiency of backstage human bioequivalence server, and filters out that account about video data total
The rubbish image of amount 99.99%, communication bandwidth needed for well solving thecamera head to distant place background server and image clearly
The contradiction of degree.
Three, in the present invention, the collected digital video of recognition of face monitoring camera accesses preprocessed chip, by real-time
After digital video pretreatment, effective facial image is filtered out, or best face is captured in control holder and optical lens tracking
Image is transferred to control platform by telecommunications network then these effective images, access face server to these images into
Row identification.For digital video image after screening, effective face image data about only has original video data amount very much
One of, existing telecommunication network or wireless network transmissions can be effectively utilized.And know since camera completes object
The work such as other and facial image screening, it is subsequent that recognition of face server can be sufficiently used for operational capability face alignment identification etc.
Work, a server can handle the input picture of multiple cameras, and the capital investment of expensive server is greatly saved.
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 flow diagram of the image pre-processing method of recognition of face monitor video of the embodiment of the present invention.
Fig. 4 is that mobile population video monitoring system of the embodiment of the present invention based on recognition of face illustrates block diagram.
Fig. 5 is that recognition of face monitoring camera illustrates schematic diagram in embodiment.
Specific embodiment
The preferred embodiment that the invention will now be described in detail with reference to the accompanying drawings.
Embodiment
A kind of image pre-processing method of recognition of face monitor video of embodiment, face identification system according to function and
Complexity is divided into front end surveillance device and control platform two parts: front end surveillance device carries out high resolution digital video image
Pretreatment and backstage recognition of face control platform, enable front end in the place that image generates, before being transmitted to video figure
As processing, valuable facial image is filtered out, 99.9% or more hash is filtered, and controls holder and optical lens, is caught
Facial image high-definition is obtained, only into excessively wired or wireless channel sends valuable image to the background service in a distant place
Device carries out into a processing and identification facial image.
A kind of image pre-processing method of recognition of face monitor video, such as Fig. 3 collect real-time digital video, to real-time
Original image in digital video is pre-processed, and the image that can be used for the face of matching identification is filtered out；
Image preprocessing is carried out to real-time digital video, specifically, using the foreground and background of differential technique separation original image,
The middle foreground image of original image is separated with background image, obtains foreground image, to foreground image and high-pass filtering mould
Plate carries out the boundary profile that convolution algorithm finds out object, isolates independent object according to the continuity of profile and closure, right
The image of each object is normalized, then carries out convolution algorithm with skin detection, obtains subject image；
The image that can be used for the face of matching identification is filtered out, specifically, after carrying out image preprocessing to real-time digital video,
Subject image is obtained, judges whether the subject image is front face, if so, the clarity of facial image is seen again, if clearly
Clear degree is not less than setting value, then filters out the image that can be used for the face of matching identification.
The image pre-processing method of this kind of recognition of face monitor video, to the image of real-time digital video after screening,
The image data that can be used for the face of matching identification about only has a ten thousandth of original video data amount, can be effectively utilized
Existing telecommunication network or wireless network transmissions.And since recognition of face monitoring camera completes object identification and face
The work such as optical sieving, recognition of face server operational capability can be sufficiently used for face alignment identification etc. follow-up works, one
Platform server can handle the input picture of multiple cameras, and the capital investment of expensive server is greatly saved.This kind of people
Face identifies the image pre-processing method of monitor video, is able to solve the high resolution video image transmission encountered in recognition of face and asks
Topic and effective facial image Trapped problems.
The image pre-processing method of this kind of recognition of face monitor video can be found out simultaneously in huge video image data
It captures to the valuable facial image of recognition of face, is backstage recognition of face to screen out a large amount of repetition, unwanted picture
Server provides important clearly image, and recognition speed and accuracy is greatly improved.
In embodiment, after carrying out image preprocessing to real-time digital video, subject image is obtained, judges the subject image
It whether is front face, if so, the clarity of facial image is seen again, if clarity is lower than setting value, control holder alignment
The face location, and control optical lens and amplify and focus on the face, it is then special according to facial image and positive eye opening face
Levy mask convolution as a result, capture optimum state facial image.
In embodiment, in facial image pretreatment and candid photograph module, after carrying out image preprocessing to real-time digital video, obtain
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.
In embodiment, the image of the face that can be used for matching identification of acquisition is sent to control platform by telecommunications network；
Control platform passes through the facial image that telecommunications network receiving front-end monitoring device transmits, and accesses face server to these facial images
It is 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 and carry out image preprocessing.Facial image pretreatment and the candid photograph each width of block search
Face in image has enough pixels if face is clear enough, and the facial image that the face is sent to rear class is just cached mould
Then block is sent to control platform by network interface.Control platform accesses recognition of face server and carries out face alignment.
In embodiment, it is pre- that high resolution video image pre-processes and capture module progress image by the facial image of front end
After processing, a large amount of independent image data is filtered, only screens and captures high-resolution facial image and be sent to distant place control platform,
The data volume transmitted required for significantly reducing, while the facial image of high quality is provided, alleviate background server
Calculation processing resource can be used for recognition of face, improve recognition efficiency and speed by burden.
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, such as Fig. 5, recognition of face monitoring camera includes holder, optical lens, imaging sensor, high definition number
Word Video Controller, facial image pretreatment and candid photograph module, image cache module and network interface.Optical lens and image pass
The collected real-time digital video of sensor accesses facial image pretreatment by high-definition digital video controller and captures module.People
After face image pretreatment and candid photograph module pre-process real-time digital video, the figure that can be used for the face of matching identification is filtered out
Picture, or by control holder and optical lens tracking capture optimum state facial image, then facial image pretreatment and
Module is captured by the image of the face that can be used for matching identification filtered out, is cached by image cache module and passes through net
Network interface sends control platform to.
Such as Fig. 5, 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, 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.
Embodiment also provides a kind of mobile population video monitoring system based on recognition of face, such as Fig. 4, including front end monitoring
Equipment 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: the facial image transmitted by telecommunications network receiving front-end monitoring device accesses face server to this
A little facial images are identified.
With reference to shown in Fig. 4 and Fig. 5, 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 within the scope of the present invention in conjunction with other embodiments.
Although reference be made herein to invention has been described for multiple explanatory embodiments of the invention, however, it is to be understood that
Those skilled in the art can be designed that a lot of other modification and implementations, these modifications and implementations will fall in this Shen
It please be within disclosed scope and spirit.More specifically, disclose in the application, drawings and claims in the range of, can
With the building block and/or a variety of variations and modifications of layout progress to theme combination layout.In addition to building block and/or layout
Outside the variations and modifications of progress, to those skilled in the art, other purposes also be will be apparent.
Claims (4)
1. a kind of image pre-processing method of recognition of face monitor video, it is characterised in that: real-time digital video is collected, to reality
When digital video in original image pre-processed, filter out the image that can be used for the face of matching identification；
Image preprocessing is carried out to real-time digital video, specifically, using the foreground and background of differential technique separation original image,
The middle foreground image of original image is separated with background image, obtains foreground image, to foreground image and high-pass filtering mould
Plate carries out the boundary profile that convolution algorithm finds out object, isolates independent object according to the continuity of profile and closure, right
The image of each object is normalized, then carries out convolution algorithm with skin detection, obtains subject image；
The image that can be used for the face of matching identification is filtered out, specifically, after carrying out image preprocessing to real-time digital video,
Subject image is obtained, judges whether the subject image is front face, if so, the clarity of facial image is seen again, if clearly
Clear degree is not less than setting value, then filters out the image that can be used for the face of matching identification.
2. the image pre-processing method of recognition of face monitor video as described in claim 1, it is characterised in that: to real-time number
After word video carries out image preprocessing, subject image is obtained, judges whether the subject image is front face, if so, seeing again
The clarity of facial image, if clarity is lower than setting value, control holder is directed at the face location, and controls optical lens and put
It is big and focus on the face, then according to facial image and positive eye opening skin detection convolution as a result, capturing best shape
The facial image of state.
3. the image pre-processing method of recognition of face monitor video as described in claim 1, it is characterised in that: facial image is pre-
In processing and candid photograph module, after carrying out image preprocessing to real-time digital video, subject image is obtained, judges that the subject image is
No is front face, is not front face if it is the subject image, then deletes the subject image.
4. the image pre-processing method of recognition of face monitor video as described in any one of claims 1-3, it is characterised in that: will
The image of the face that can be used for matching identification obtained sends control platform to by telecommunications network；Control platform is connect by telecommunications network
The facial image of front end surveillance device transmission is received, access face server identifies these facial images.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810731822.5A CN108960146A (en) | 2018-07-05 | 2018-07-05 | The image pre-processing method of recognition of face monitor video |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810731822.5A CN108960146A (en) | 2018-07-05 | 2018-07-05 | The image pre-processing method of recognition of face monitor video |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108960146A true CN108960146A (en) | 2018-12-07 |
Family
ID=64486096
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810731822.5A Pending CN108960146A (en) | 2018-07-05 | 2018-07-05 | The image pre-processing method of recognition of face monitor video |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108960146A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111368579A (en) * | 2018-12-25 | 2020-07-03 | 中国电信股份有限公司 | Image recognition method, apparatus and system, and computer-readable storage medium |
| CN113297912A (en) * | 2021-04-26 | 2021-08-24 | 云南电网有限责任公司信息中心 | Image preprocessing method for image recognition of distribution network field operating personnel |
| CN114333119A (en) * | 2021-12-31 | 2022-04-12 | 上海商汤临港智能科技有限公司 | Vehicle unlocking method, vehicle management method, terminal, vehicle unlocking system, vehicle unlocking device, and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060098729A1 (en) * | 2004-11-09 | 2006-05-11 | Lien-Chieh Shen | Smart image processing CCTV camera device and method for operating same |
| CN101079107A (en) * | 2007-06-29 | 2007-11-28 | 丹东华日理学电气有限公司 | Automatic identification method for hub type |
| CN102799877A (en) * | 2012-09-11 | 2012-11-28 | 上海中原电子技术工程有限公司 | Method and system for screening face images |
| CN104580121A (en) * | 2013-10-28 | 2015-04-29 | 腾讯科技（深圳）有限公司 | People search/people information matching and pushing method, system, client and server |
| CN107278369A (en) * | 2016-12-26 | 2017-10-20 | 深圳前海达闼云端智能科技有限公司 | Method, device and the communication system of people finder |
-
2018
- 2018-07-05 CN CN201810731822.5A patent/CN108960146A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060098729A1 (en) * | 2004-11-09 | 2006-05-11 | Lien-Chieh Shen | Smart image processing CCTV camera device and method for operating same |
| CN101079107A (en) * | 2007-06-29 | 2007-11-28 | 丹东华日理学电气有限公司 | Automatic identification method for hub type |
| CN102799877A (en) * | 2012-09-11 | 2012-11-28 | 上海中原电子技术工程有限公司 | Method and system for screening face images |
| CN104580121A (en) * | 2013-10-28 | 2015-04-29 | 腾讯科技（深圳）有限公司 | People search/people information matching and pushing method, system, client and server |
| CN107278369A (en) * | 2016-12-26 | 2017-10-20 | 深圳前海达闼云端智能科技有限公司 | Method, device and the communication system of people finder |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111368579A (en) * | 2018-12-25 | 2020-07-03 | 中国电信股份有限公司 | Image recognition method, apparatus and system, and computer-readable storage medium |
| CN111368579B (en) * | 2018-12-25 | 2023-07-07 | 中国电信股份有限公司 | Image recognition method, apparatus and system, and computer-readable medium |
| CN113297912A (en) * | 2021-04-26 | 2021-08-24 | 云南电网有限责任公司信息中心 | Image preprocessing method for image recognition of distribution network field operating personnel |
| CN114333119A (en) * | 2021-12-31 | 2022-04-12 | 上海商汤临港智能科技有限公司 | Vehicle unlocking method, vehicle management method, terminal, vehicle unlocking system, vehicle unlocking device, and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108513110A (en) | Recognition of face monitoring camera | |
| CN108540707A (en) | Recognition of face crime scene investigation device | |
| WO2020078229A1 (en) | Target object identification method and apparatus, storage medium and electronic apparatus | |
| KR101831973B1 (en) | Iris imaging apparatus and methods for configuring an iris imaging apparatus | |
| CN109711318B (en) | Multi-face detection and tracking method based on video stream | |
| US20090051787A1 (en) | Apparatus and method for photographing image using digital camera capable of providing preview images | |
| KR101798979B1 (en) | Smart Pedestrian Traffic Light System | |
| CN112165573A (en) | Shooting processing method and device, equipment and storage medium | |
| CN108960146A (en) | The image pre-processing method of recognition of face monitor video | |
| CN108921104A (en) | Mobile population video monitoring method based on recognition of face | |
| CN109359577B (en) | System for detecting number of people under complex background based on machine learning | |
| CN105022999A (en) | Man code company real-time acquisition system | |
| CN208156681U (en) | A kind of video monitoring image identifying system | |
| WO2020249054A1 (en) | Living body detection method and system for human face by using two long-baseline cameras | |
| KR101337554B1 (en) | Apparatus for trace of wanted criminal and missing person using image recognition and method thereof | |
| CN109451233A (en) | A kind of device acquiring fine definition face-image | |
| CN108960147A (en) | Mobile population video monitoring system based on recognition of face | |
| CN208522852U (en) | Recognition of face crime scene investigation device | |
| CN208691422U (en) | Recognition of face monitoring camera | |
| JPH1040386A (en) | Iris recognition system | |
| KR102194409B1 (en) | Face Detection and Recogniton System and Method using Multi-focusing AI Convolution Neural Network | |
| WO2023231479A1 (en) | Pupil detection method and apparatus, and storage medium and electronic device | |
| CN109241947A (en) | Information processing unit and method for the monitoring of stream of people's momentum | |
| CN110062150A (en) | A kind of Atomatic focusing method and device | |
| KR102108391B1 (en) | Moving Object Linkage Tracking System and Method Using Multiple Cameras |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181207 |
|
| RJ01 | Rejection of invention patent application after publication |