CN110059644A - A kind of biopsy method based on facial image, system and associated component - Google Patents
A kind of biopsy method based on facial image, system and associated component Download PDFInfo
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- CN110059644A CN110059644A CN201910329185.3A CN201910329185A CN110059644A CN 110059644 A CN110059644 A CN 110059644A CN 201910329185 A CN201910329185 A CN 201910329185A CN 110059644 A CN110059644 A CN 110059644A
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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
- G06V40/161—Detection; Localisation; Normalisation
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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
- G06V40/40—Spoof detection, e.g. liveness detection
- G06V40/45—Detection of the body part being alive
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Abstract
This application discloses a kind of biopsy method based on facial image, the biopsy method includes the visible images for obtaining target area, and executes Face datection operation to the visible images；When in the visible images including facial image, the near infrared light image of the target area is acquired；The near-infrared face information of the visible light face information and the near infrared light image in the visible images is extracted respectively；It compares the visible light face information and the near-infrared face information obtains comparing result, judge the target area with the presence or absence of living body faces according to the comparing result.This method can accurate judgement facial image whether be living body faces image.Disclosed herein as well is a kind of In vivo detection system, a kind of computer readable storage medium and a kind of electronic equipment based on facial image have the above beneficial effect.
Description
Technical field
The present invention relates to human face detection tech field, in particular to a kind of biopsy method based on facial image is
System, a kind of computer readable storage medium and a kind of electronic equipment.
Background technique
In vivo detection technology is the method that object real physiological feature is determined in authentication scene, to help user
Fraud is screened, ensures the interests of user.In vivo detection is often referred to the detection process of living body faces, to identify current region
Interior face-image whether be true man face-image.
In the related technology, it generallys use binocular In vivo detection algorithm and carries out living body faces detection, (commonly may be used from RGB image
Light-exposed camera) detection face, corresponding region is intercepted near infrared light image, when can detect near infrared light image
It can determine whether that target is living body to face characteristic.But above-mentioned binocular In vivo detection algorithm can only detect screen attack, Wu Fajian
Survey the attack of paper.
Therefore, it is that those skilled in the art need to solve at present that how whether accurate judgement facial image, which is living body faces image,
Certainly the technical issues of.
Summary of the invention
The purpose of the application is to provide a kind of biopsy method based on facial image, system, a kind of computer-readable
Storage medium and a kind of electronic equipment, can accurate judgement facial image whether be living body faces image.
In order to solve the above technical problems, the application provides a kind of biopsy method based on facial image, living body inspection
Survey method includes:
The visible images of target area are obtained, and Face datection operation is executed to the visible images；
When in the visible images including facial image, the near infrared light image of the target area is acquired；
The near-infrared people of the visible light face information and the near infrared light image in the visible images is extracted respectively
Face information；
It compares the visible light face information and the near-infrared face information obtains comparing result, tied according to the comparison
Fruit judges the target area with the presence or absence of living body faces.
Optionally, it compares the visible light face information and the near-infrared face information obtains comparing result, according to institute
It states comparing result and judges that the target area includes: with the presence or absence of living body faces
It compares the visible light face information and the near-infrared face information obtains human face similarity degree；
When the human face similarity degree is 0, then determine that there is no the living body faces for the target area；
When the human face similarity degree is greater than 0 and when less than the first preset value, then determine that there are the work for the target area
Body face；
When the human face similarity degree is greater than or equal to first preset value, then determine that there is no institutes for the target area
State living body faces.
Optionally, further includes:
When the human face similarity degree is 0, then the prompt information of screen attack is generated；
When the human face similarity degree is greater than or equal to first preset value, then the prompt information of paper attack is generated.
Optionally, it compares the visible light face information and the near-infrared face information obtains comparing result, according to institute
It states comparing result and judges that the target area includes: with the presence or absence of living body faces
Visible images and described close are calculated according to the visible light face information and the near-infrared face information
The friendship in facial image region and ratio in infrared light image；
When the friendship and when than less than the second preset value, then determine the target area there is no the living body faces.
Optionally, the visible images of target area are obtained, and Face datection operation packet is executed to the visible images
It includes:
The visible images for obtaining the target area hold the visible images using mtcnn Face datection algorithm
The operation of row Face datection.
Optionally, after executing Face datection operation to the visible images using mtcnn Face datection algorithm, also
Include:
Face confidence level is determined according to Face datection result；
When the face confidence level is greater than default confidence level, determine to include the face figure in the visible images
Picture.
The In vivo detection system based on facial image that present invention also provides a kind of, should the In vivo detection based on facial image
System includes:
Face detection module executes face for obtaining the visible images of target area, and to the visible images
Detection operation；
Near-infrared image acquisition module, for acquiring the target when in the visible images including facial image
The near infrared light image in region；
Information extraction modules, for extracting visible light face information and the near-infrared in the visible images respectively
The near-infrared face information of light image；
In vivo detection module obtains comparison knot for comparing the visible light face information and the near-infrared face information
Fruit judges the target area with the presence or absence of living body faces according to the comparing result.
Optionally, the In vivo detection module includes:
It is similar to obtain face for comparing the visible light face information with the near-infrared face information for comparison unit
Degree；
First processing units, for when the human face similarity degree is 0, then determining that there is no the work for the target area
Body face；
The second processing unit then determines the mesh for being greater than 0 and when less than the first preset value when the human face similarity degree
Marking region, there are the living body faces；
Third processing unit, for when the human face similarity degree is greater than or equal to first preset value, then determining institute
Stating target area, there is no the living body faces.
Present invention also provides a kind of computer readable storage mediums, are stored thereon with computer program, the computer
Program realizes the step of above-mentioned biopsy method based on facial image executes when executing.
Present invention also provides a kind of electronic equipment, including light can be imaged to light video camera head, memory and processor
Head is used for the visible images in photographic subjects region；Computer program is stored in the memory, the processor calls institute
The step of above-mentioned biopsy method based on facial image executes is realized when stating the computer program in memory.
The present invention provides a kind of biopsy methods based on facial image, the visible light figure including obtaining target area
Picture, and Face datection operation is executed to the visible images；When in the visible images including facial image, institute is acquired
State the near infrared light image of target area；The visible light face information in the visible images and the near-infrared are extracted respectively
The near-infrared face information of light image；It compares the visible light face information and the near-infrared face information obtains comparison knot
Fruit judges the target area with the presence or absence of living body faces according to the comparing result.
The application is detecting that target area there are when face, acquires the near infrared light of target area according to visible images
Image, since imaging effect of the same living body faces in visible images and near infrared light image has certain difference, because
This can be according to pair of the near-infrared face information of visible light face information and the near infrared light image in visible images
Than whether there is living body faces in result judgement target area.The application can accurate judgement facial image whether be living body faces
Image.The application additionally provides a kind of In vivo detection system based on facial image, a kind of computer readable storage medium simultaneously
And a kind of electronic equipment, there is above-mentioned beneficial effect, details are not described herein.
Detailed description of the invention
In ord to more clearly illustrate embodiments of the present application, attached drawing needed in the embodiment will be done simply below
It introduces, it should be apparent that, the drawings in the following description are only some examples of the present application, for ordinary skill people
For member, without creative efforts, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of flow chart of the biopsy method based on facial image provided by the embodiment of the present application；
Fig. 2 is the flow chart of biopsy method of the another kind based on facial image provided by the embodiment of the present application；
Fig. 3 is the flow chart of the In vivo detection in practical application；
Fig. 4 is a kind of structural schematic diagram of the In vivo detection system based on facial image provided by the embodiment of the present application.
Specific embodiment
To keep the purposes, technical schemes and advantages of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
Every other embodiment obtained without making creative work, shall fall in the protection scope of this application.
Below referring to Figure 1, Fig. 1 is a kind of biopsy method based on facial image provided by the embodiment of the present application
Flow chart.
Specific steps may include:
S101: the visible images of target area are obtained, and Face datection operation is executed to the visible images；
Wherein, the purpose of the present embodiment is that the facial image to target area carries out In vivo detection, to determine the mesh
Mark the facial image presented in the image or photo or display screen that the facial image occurred in region is mankind's real life facial.
The present embodiment can be applied in the face-recognition procedures such as gate inhibition checks card, mobile phone unlocks, by being detected whether based on facial image
The safety that whole face identification system is promoted for living body avoids the occurrence of and pretends him using mask, papery photo, electronic photo
The case where people.
The present embodiment does not limit the position for obtaining the target area of visible images and size, and there may be for shooting mesh
Mark the camera of the visible images in region.After obtaining visible images, the present embodiment is first to visible images executor
Face detection operation, to judge in visible images with the presence or absence of facial image.The method for judging whether there is facial image has
Very much, it can be operated to that light image can be executed background removal, and detect and whether there is in the visible images after removal background
The face feature information (such as relative position of face) of people then illustrates to include facial image in visible images if it exists.Also
Light image can be inputted in trained deep learning model, be judged in visible images based on deep learning model
It whether include facial image.
As a kind of feasible embodiment, it can be determined that whether target area image captured by visible image capturing head is sent out
Changing can shoot the visible images of a target area if changing to execute the related behaviour of the present embodiment
Make.
S102: when in the visible images including facial image, the near infrared light image of the target area is acquired；
Wherein, this step establishes the visible images as the result is shown that in S101 visible images are carried out with Face datection operation
In include facial image, i.e. target area is in the presence of can take the object of facial image.Certainly, it is examined according only to visible images
Measure facial image can not illustrate the facial image be by real human face present image, possible someone utilize papery photo or
The case where electronic photo pretends other people.Therefore the present embodiment obtains identical when detecting facial image from visible images
The near infrared light image in region (target area i.e. mentioned above).The near infrared light image that the present embodiment is mentioned refers to: close red
The image shot under external light reflection.Since under near infrared light and visible light, the imaging effect of living body and non-living body has
Significant difference, therefore can use the imaging effect difference of visible images and near infrared light image to judge in visible images
Existing facial image whether be really face present image.
S103: the close red of visible light face information in the visible images and the near infrared light image is extracted respectively
Outer face information；
Wherein, the purpose of this step is to extract in the visible light face information and near infrared light image in visible images
Near-infrared face information the two is compared.It is right that visible light face information refers specifically to facial image institute in visible images
The information for all areas answered may include position, size, face feature information etc. that visible light servant's face image is presented；
Similarly it is found that near infrared light face information refers specifically to the information of all areas corresponding to facial image near infrared light image,
It may include position, size, the face feature information etc. that near infrared light servant's face image is presented.That is, it is assumed that target
There are when real human face in region, it is seen that light face information refers to all image informations that the real human face is presented under visible light, closely
Infrared light face information refers to all image informations that the real human face is presented under near infrared light.
S104: comparing the visible light face information and the near-infrared face information obtains comparing result, according to described
Comparing result judges the target area with the presence or absence of living body faces.
Wherein, this step is established on the basis of having obtained visible light face information and near infrared light face information, right
Than visible light face information and near-infrared face information, the visible light face letter of the same object under infrared light and visible light is judged
Whether breath and near-infrared face information have significant ground difference, illustrate that there are real human faces for target area if having, if not having
There were significant differences then illustrates that there is no real human faces for target area.
The present embodiment is detecting that target area there are when face, acquires the near-infrared of target area according to visible images
Light image, since imaging effect of the same living body faces in visible images and near infrared light image has certain difference,
It therefore can be according to the near-infrared face information of visible light face information and the near infrared light image in visible images
Comparing result determines to whether there is living body faces in target area.The present embodiment can accurate judgement facial image whether be living body
Facial image.
Fig. 2 is referred to below, and Fig. 2 is In vivo detection side of the another kind based on facial image provided by the embodiment of the present application
The flow chart of method, may comprise steps of:
S201: obtaining the visible images of the target area, using mtcnn Face datection algorithm to the visible light figure
As executing Face datection operation.
Wherein, mtcnn Face datection algorithm can quickly detect the face in visible images, have detection accurate and
Quick feature.
S202: determining face confidence level according to Face datection result, when the face confidence level is greater than default confidence level,
Determine in the visible images include the facial image and enter S203；
It is understood that executing the visible light Face datection based on mtcnn Face datection algorithm to visible images
Corresponding face confidence level can be generated according to Face datection result after operation, it can be with when face confidence level is greater than preset value
Judge that, there are facial image in visible images, there is no the operation streams that facial image can terminate the present embodiment on the contrary then explanation
Journey.
S203: the near infrared light image of the target area is acquired；
S204: the close red of visible light face information in the visible images and the near infrared light image is extracted respectively
Outer face information；
S205: the visible images and institute are calculated according to the visible light face information and the near-infrared face information
State the friendship in facial image region near infrared light image and ratio；When it is described friendship and than less than the second preset value when, then determine described in
The living body faces are not present in target area；When it is described friendship and than be greater than or equal to the second preset value when, then enter S206；
Wherein it is possible to determine corresponding facial image region respectively according to visible light face information and near-infrared face information
Profile information, illustrate visible images and near infrared light image when the coincidence degree (hand over and than) of the profile of the two is smaller
Taken object is not same object, therefore can directly determine the object of target area for non-living body.When friendship and than big
When the second preset value, operation can be further determined into S206.
S206: comparing the visible light face information and the near-infrared face information obtains human face similarity degree；
Wherein, criminal malice pretend other people by face detection system generally use paper attack and screen attack
Mode, paper attack refer to the attack pattern using papery photo deception face identification system, and screen attack, which refers to, utilizes electronic curtain
The attack pattern of the electronic photo deception face identification system of display.Visible light face information and near-infrared people under screen attack
The human face similarity degree of face information is 0, and visible light face information is similar with the face of near-infrared face information under paper attack
Degree is very high, and the visible light face information of normal living body faces and the human face similarity degree of near-infrared face information are attacked between paper
Between the similarity of screen attack.
S207: when the human face similarity degree is 0, then determine that there is no the living body faces for the target area；Work as institute
When stating human face similarity degree more than or equal to first preset value, then determine that there is no the living body faces for the target area.
S208: when the human face similarity degree is greater than 0 and when less than the first preset value, then determine that there are institutes for the target area
State living body faces；
As a kind of feasible embodiment, when detecting human face similarity degree is 0, then the prompt letter of screen attack is generated
Breath；When detecting that human face similarity degree is greater than or equal to first preset value, then the prompt information of paper attack is generated.
Illustrate the above process below by specific embodiment in practical application, refer to Fig. 3, Fig. 3 is practical application
In In vivo detection flow chart: firstly, using mtcnn Face datection algorithm, face is detected under visible light, if can't detect
Or face confidence level is not up to 0.5, then continues to test.Secondly, in that corresponding frame near-infrared of the visible light for detecting face
Face is detected in image, if can't detect or confidence level is not greater than 0.5, or is handed over and is compared with visible light human face region and be not greater than
0.7, then it is judged to non-living body.Finally, interception visible light and near infrared light human face region, and feature is extracted, carry out human face similarity degree
Compare, if more than or be equal to 0.65, then be judged to non-living body；Otherwise, it is judged to living body.
This detection method of above-described embodiment can be applied to gate inhibition's punch card system based on visible light and it is close it is red in.With door
For access control system, user may use other people papery photo or video etc., it is intended to pretend other people by access control system, so
In vivo detection algorithm can prevent passing through for illegal user in access control system.In order to distinguish the attack shape such as living body and papery or screen
The non-living body of formula, using under near infrared light and visible light, the significant difference of living body and non-living body, Lai Jinhang In vivo detection.
Above-described embodiment detects face under visible light and near infrared light, if not detecting face under near infrared light,
It is determined as non-living body.Further, its visible light and near infrared light human face region are intercepted, and extracts its feature and is compared,
It is considered as non-living body if being more than certain threshold value.That is, can't detect face under near infrared light, then determine to detect that screen is attacked
Situation, in addition under visible light and near infrared light, the similarity of living body faces is very low, and two kinds of human face similarity degrees of papery photo are very
Height, so the method for above-described embodiment is can effectively to detect screen and paper attack.
Fig. 4 is referred to, Fig. 4 is a kind of knot of the In vivo detection system based on facial image provided by the embodiment of the present application
Structure schematic diagram；
The system may include:
Face detection module 100, for obtaining the visible images of target area, and to the visible images executor
Face detection operation；
Near-infrared image acquisition module 200, for acquiring the mesh when in the visible images including facial image
Mark the near infrared light image in region；
Information extraction modules 300, for extracting visible light face information in the visible images and described close respectively
The near-infrared face information of infrared light image；
In vivo detection module 400, for comparing the visible light face information and the near-infrared face information obtains pair
Than as a result, judging the target area with the presence or absence of living body faces according to the comparing result.
The present embodiment is detecting that target area there are when face, acquires the near-infrared of target area according to visible images
Light image, since imaging effect of the same living body faces in visible images and near infrared light image has certain difference,
It therefore can be according to the near-infrared face information of visible light face information and the near infrared light image in visible images
Comparing result determines to whether there is living body faces in target area.The present embodiment can accurate judgement facial image whether be living body
Facial image.
Further, the In vivo detection module includes:
It is similar to obtain face for comparing the visible light face information with the near-infrared face information for comparison unit
Degree；
First processing units, for when the human face similarity degree is 0, then determining that there is no the work for the target area
Body face；
The second processing unit then determines the mesh for being greater than 0 and when less than the first preset value when the human face similarity degree
Marking region, there are the living body faces；
Third processing unit, for when the human face similarity degree is greater than or equal to first preset value, then determining institute
Stating target area, there is no the living body faces.
Since the embodiment of components of system as directed is corresponded to each other with the embodiment of method part, the embodiment of components of system as directed is asked
Referring to the description of the embodiment of method part, wouldn't repeat here.
Present invention also provides a kind of computer readable storage mediums, have computer program thereon, the computer program
It is performed and step provided by above-described embodiment may be implemented.The storage medium may include: USB flash disk, mobile hard disk, read-only deposit
Reservoir (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or
The various media that can store program code such as CD.
Present invention also provides a kind of electronic equipment, may include can be by light video camera head, memory and processor, can be by light
Camera is used for the visible images in photographic subjects region, has computer program in the memory, and the processor calls
When computer program in the memory, step provided by above-described embodiment may be implemented.Certain electronic equipment is also
It may include various network interfaces, the components such as power supply.
Each embodiment is described in a progressive manner in specification, the highlights of each of the examples are with other realities
The difference of example is applied, the same or similar parts in each embodiment may refer to each other.For system disclosed in embodiment
Speech, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is referring to method part illustration
?.It should be pointed out that for those skilled in the art, under the premise of not departing from the application principle, also
Can to the application, some improvement and modification can also be carried out, these improvement and modification also fall into the protection scope of the claim of this application
It is interior.
It should also be noted that, in the present specification, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that the process, method, article or equipment for including a series of elements not only includes that
A little elements, but also including other elements that are not explicitly listed, or further include for this process, method, article or
The intrinsic element of equipment.Under the situation not limited more, the element limited by sentence "including a ..." is not arranged
Except there is also other identical elements in the process, method, article or apparatus that includes the element.
Claims (10)
1. a kind of biopsy method based on facial image characterized by comprising
The visible images of target area are obtained, and Face datection operation is executed to the visible images；
When in the visible images including facial image, the near infrared light image of the target area is acquired；
The near-infrared face letter of the visible light face information and the near infrared light image in the visible images is extracted respectively
Breath；
It compares the visible light face information and the near-infrared face information obtains comparing result, sentenced according to the comparing result
The target area break with the presence or absence of living body faces.
2. biopsy method according to claim 1, which is characterized in that compare the visible light face information and described close
Infrared face information obtains comparing result, judges the target area with the presence or absence of living body faces packet according to the comparing result
It includes:
It compares the visible light face information and the near-infrared face information obtains human face similarity degree；
When the human face similarity degree is 0, then determine that there is no the living body faces for the target area；
When the human face similarity degree is greater than 0 and when less than the first preset value, then determine that there are the living body people for the target area
Face；
When the human face similarity degree is greater than or equal to first preset value, then determine that there is no the work for the target area
Body face.
3. biopsy method according to claim 2, which is characterized in that further include:
When the human face similarity degree is 0, then the prompt information of screen attack is generated；
When the human face similarity degree is greater than or equal to first preset value, then the prompt information of paper attack is generated.
4. biopsy method according to claim 1, which is characterized in that compare the visible light face information and described close
Infrared face information obtains comparing result, judges the target area with the presence or absence of living body faces packet according to the comparing result
It includes:
The visible images and the near-infrared are calculated according to the visible light face information and the near-infrared face information
The friendship in facial image region and ratio in light image；
When the friendship and when than less than the second preset value, then determine the target area there is no the living body faces.
5. according to claim 1 to any one of 4 biopsy methods, which is characterized in that obtain the visible light of target area
Image, and Face datection operation is executed to the visible images and includes:
The visible images for obtaining the target area, using mtcnn Face datection algorithm to the visible images executor
Face detection operation.
6. biopsy method according to claim 5, which is characterized in that in utilization mtcnn Face datection algorithm to described
Visible images execute after Face datection operation, further includes:
Face confidence level is determined according to Face datection result；
When the face confidence level is greater than default confidence level, determine to include the facial image in the visible images.
7. a kind of In vivo detection system based on facial image characterized by comprising
Face detection module executes Face datection for obtaining the visible images of target area, and to the visible images
Operation；
Near-infrared image acquisition module, for acquiring the target area when in the visible images including facial image
Near infrared light image；
Information extraction modules, for extracting visible light face information and the near infrared light figure in the visible images respectively
The near-infrared face information of picture；
In vivo detection module obtains comparing result for comparing the visible light face information and the near-infrared face information,
Judge the target area with the presence or absence of living body faces according to the comparing result.
8. In vivo detection system according to claim 7, which is characterized in that the In vivo detection module includes:
Comparison unit obtains human face similarity degree for comparing the visible light face information and the near-infrared face information；
First processing units, for when the human face similarity degree is 0, then determining that there is no the living body people for the target area
Face；
The second processing unit then determines the target area for being greater than 0 and when less than the first preset value when the human face similarity degree
There are the living body faces in domain；
Third processing unit, for when the human face similarity degree is greater than or equal to first preset value, then determining the mesh
It marks region and the living body faces is not present.
9. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium
Program is realized as described in any one of claim 1 to 6 when the computer program is executed by processor based on the work of facial image
The step of body detecting method.
10. a kind of electronic equipment characterized by comprising
It can visible images by light video camera head, for photographic subjects region；
Memory, for storing computer program；
Processor, realization is as described in any one of claim 1 to 6 when for executing the computer program based on facial image
The step of biopsy method.
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Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110443192A (en) * | 2019-08-01 | 2019-11-12 | 中国科学院重庆绿色智能技术研究院 | A kind of non-interactive type human face in-vivo detection method and system based on binocular image |
| CN110503023A (en) * | 2019-08-19 | 2019-11-26 | 深圳市商汤科技有限公司 | Biopsy method and device, electronic equipment and storage medium |
| CN110532992A (en) * | 2019-09-04 | 2019-12-03 | 深圳市捷顺科技实业股份有限公司 | A kind of face identification method based on visible light and near-infrared |
| CN110740315A (en) * | 2019-11-07 | 2020-01-31 | 杭州宇泛智能科技有限公司 | Camera correction method and device, electronic equipment and storage medium |
| CN110956114A (en) * | 2019-11-25 | 2020-04-03 | 展讯通信（上海）有限公司 | Face living body detection method, device, detection system and storage medium |
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| CN111339840A (en) * | 2020-02-10 | 2020-06-26 | 浙江大华技术股份有限公司 | Face detection method and monitoring system |
| CN112488018A (en) * | 2020-12-09 | 2021-03-12 | 巽腾(广东)科技有限公司 | Binocular in-vivo detection method, device, equipment and storage medium |
| CN112989866A (en) * | 2019-12-02 | 2021-06-18 | 浙江宇视科技有限公司 | Object identification method and device, electronic equipment and readable storage medium |
| CN113065507A (en) * | 2021-04-20 | 2021-07-02 | 支付宝(杭州)信息技术有限公司 | Method and device for realizing face authentication |
| CN113128259A (en) * | 2019-12-30 | 2021-07-16 | 杭州海康威视数字技术股份有限公司 | Face recognition device and face recognition method |
| CN113128254A (en) * | 2019-12-30 | 2021-07-16 | 上海依图网络科技有限公司 | Face capturing method, device, chip and computer readable storage medium |
| CN113390515A (en) * | 2021-07-06 | 2021-09-14 | 新疆爱华盈通信息技术有限公司 | Multi-person mobile temperature measurement method based on double cameras |
| CN113657198A (en) * | 2021-07-28 | 2021-11-16 | 浙江大华技术股份有限公司 | Binocular living body face recognition method and device, electronic device and storage medium |
| CN115174818A (en) * | 2022-09-08 | 2022-10-11 | 深圳市维海德技术股份有限公司 | Target tracking method based on sound positioning, electronic equipment and readable storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107358181A (en) * | 2017-06-28 | 2017-11-17 | 重庆中科云丛科技有限公司 | The infrared visible image capturing head device and method of monocular judged for face live body |
| CN107577990A (en) * | 2017-08-09 | 2018-01-12 | 武汉世纪金桥安全技术有限公司 | A kind of extensive face identification method for accelerating retrieval based on GPU |
| CN108629305A (en) * | 2018-04-27 | 2018-10-09 | 朱旭辉 | A kind of face recognition method |
-
2019
- 2019-04-23 CN CN201910329185.3A patent/CN110059644A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107358181A (en) * | 2017-06-28 | 2017-11-17 | 重庆中科云丛科技有限公司 | The infrared visible image capturing head device and method of monocular judged for face live body |
| CN107577990A (en) * | 2017-08-09 | 2018-01-12 | 武汉世纪金桥安全技术有限公司 | A kind of extensive face identification method for accelerating retrieval based on GPU |
| CN108629305A (en) * | 2018-04-27 | 2018-10-09 | 朱旭辉 | A kind of face recognition method |
Non-Patent Citations (2)
| Title |
|---|
| 朱道明 等: "《建筑安防技术》", 31 January 2013, 东华大学出版社 * |
| 王斌 等: "《高校学生社团建设的理论与实践》", 30 June 2014, 四川大学出版社 * |
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| CN110443192A (en) * | 2019-08-01 | 2019-11-12 | 中国科学院重庆绿色智能技术研究院 | A kind of non-interactive type human face in-vivo detection method and system based on binocular image |
| CN110443192B (en) * | 2019-08-01 | 2023-04-28 | 中国科学院重庆绿色智能技术研究院 | Non-interactive human face living body detection method and system based on binocular image |
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| CN110956114A (en) * | 2019-11-25 | 2020-04-03 | 展讯通信（上海）有限公司 | Face living body detection method, device, detection system and storage medium |
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| CN112989866B (en) * | 2019-12-02 | 2024-04-09 | 浙江宇视科技有限公司 | Object recognition method, device, electronic equipment and readable storage medium |
| CN112989866A (en) * | 2019-12-02 | 2021-06-18 | 浙江宇视科技有限公司 | Object identification method and device, electronic equipment and readable storage medium |
| CN111126216A (en) * | 2019-12-13 | 2020-05-08 | 支付宝(杭州)信息技术有限公司 | Risk detection method, device and equipment |
| CN113128254A (en) * | 2019-12-30 | 2021-07-16 | 上海依图网络科技有限公司 | Face capturing method, device, chip and computer readable storage medium |
| CN113128259A (en) * | 2019-12-30 | 2021-07-16 | 杭州海康威视数字技术股份有限公司 | Face recognition device and face recognition method |
| CN113128259B (en) * | 2019-12-30 | 2023-08-29 | 杭州海康威视数字技术股份有限公司 | Face recognition device and face recognition method |
| CN111339840B (en) * | 2020-02-10 | 2023-04-07 | 浙江大华技术股份有限公司 | Face detection method and monitoring system |
| CN111339840A (en) * | 2020-02-10 | 2020-06-26 | 浙江大华技术股份有限公司 | Face detection method and monitoring system |
| CN112488018A (en) * | 2020-12-09 | 2021-03-12 | 巽腾(广东)科技有限公司 | Binocular in-vivo detection method, device, equipment and storage medium |
| CN113065507A (en) * | 2021-04-20 | 2021-07-02 | 支付宝(杭州)信息技术有限公司 | Method and device for realizing face authentication |
| CN113390515A (en) * | 2021-07-06 | 2021-09-14 | 新疆爱华盈通信息技术有限公司 | Multi-person mobile temperature measurement method based on double cameras |
| CN113657198A (en) * | 2021-07-28 | 2021-11-16 | 浙江大华技术股份有限公司 | Binocular living body face recognition method and device, electronic device and storage medium |
| CN115174818A (en) * | 2022-09-08 | 2022-10-11 | 深圳市维海德技术股份有限公司 | Target tracking method based on sound positioning, electronic equipment and readable storage medium |
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