CN108537163A

CN108537163A - A kind of biological characteristic 4 D data recognition methods taken pictures based on visible light and system

Info

Publication number: CN108537163A
Application number: CN201810302363.9A
Authority: CN
Inventors: 左忠斌; 左达宇
Original assignee: Tianmu Love Vision (beijing) Technology Co Ltd
Current assignee: Tianmu Love Vision (beijing) Technology Co Ltd; Tianmu Aishi Beijing Technology Co Ltd
Priority date: 2018-04-04
Filing date: 2018-04-04
Publication date: 2018-09-14

Abstract

The present invention provides a kind of biological characteristic 4 D data recognition methods taken pictures based on visible light, several biometric images of organism within given time are collected by camera, four dimension modules that biological characteristic is built according to several biometric images, to realize that the biological characteristic 4 D data of organism acquires；Using the identity information of organism as distinguishing mark, formation includes the database of a plurality of biological characteristic 4 D data；The biological characteristic 4 D data stored in database is found using the identity information of target organism, and point cloud is compared to identify the identity of target organism accordingly.Additionally provide a kind of biological characteristic 4 D data identifying system taken pictures based on visible light.The present invention improves acquisition and the recognition efficiency of biological information, using biological information is collected, completely restores the various features of biological characteristic spatially, and unlimited possibility is provided for the application such as identification.

Description

A kind of biological characteristic 4 D data recognition methods taken pictures based on visible light and system

Technical field

The present invention relates to biometrics identification technology field, especially a kind of biological characteristic taken pictures based on visible light is four-dimensional Data identification method and system.

Background technology

Biological characteristic is the intrinsic physiology or behavioural characteristic of biology, such as fingerprint, palmmprint, iris or face.Biological characteristic There are certain uniqueness and stability, i.e., the diversity ratio between certain biological characteristic of any two biology is larger, and biological characteristic It will not generally change a lot with the time, this allows for biological characteristic and is well suited for applying in authentication or identifying system In the scenes such as authentication information in.

Current biological attribute data is all the 2D data using plane, main to use by taking the biological characteristic of hand as an example The mode of 2D is imitative according to the collected 2D pictures of hand to identify the feature of some or several hands, part criminal 2D hand-characteristics processed, part identifying system of out-tricking bring prodigious security risk to personal information security；Again with head face Biological characteristic for, the data application in relation to head face all rests on simple picture using upper, i.e., can only be from some spy Fixed angle handles head face data, and personal facial expression can have some differences in identification process (such as：Smile or blink), bring certain difficulty to information identification.

Therefore, there is an urgent need for being directed to biological characteristic to carry out multidimensional data identification, safety is improved, and branch is provided for subsequent application Support.

Invention content

In view of the above problems, it is proposed that the present invention overcoming the above problem in order to provide one kind or solves at least partly State the biological characteristic 4 D data recognition methods taken pictures based on visible light and the system of problem.

A kind of biological characteristic 4 D data recognition methods taken pictures based on visible light comprising following steps：

S01. biological information is acquired,

Several biometric images of organism within given time are acquired by Visible Light Camera, according to several described lifes Object characteristic image builds four dimension modules of biological characteristic, to realize that the biological characteristic 4 D data of the organism acquires；

S02. biological characteristic 4 D data is stored,

Scanning or typing organism identity information (I1, I2 ... In), using the identity information (I1, I2 ... In) as Distinguishing mark is associated storage to collected biological characteristic 4 D data, and formation includes a plurality of biological characteristic 4 D data The database of (D1, D2 ... Dn)；

S03. the identification of target organism,

Acquire the biological characteristic 4 D data (T1, T2 ... Tn) of target organism, and target organism described in scanning or typing The identity information (I1, I2 ... In) of body finds the data by the identity information (I1, I2 ... In) of the target organism The biological characteristic 4 D data (D1, D2 ... Dn) stored in library, by the biological characteristic 4 D data of the target organism (T1, T2 ... Tn) it is compared respectively with the biological characteristic 4 D data (D1, D2 ... Dn) stored in the corresponding database, to know The identity of other target organism.

Further, step S01 further includes：

Several biometric images of organism within given time are collected by more Visible Light Cameras,

Several described biometric images are handled, respective feature in several described biometric images is extracted Point；

Based on respective characteristic point in several biometric images described in extraction, the characteristic point cloud number of biological characteristic is generated According to；

Four dimension modules that biological characteristic is built according to the feature point cloud data, to realize adopting for biological characteristic 4 D data Collection.

Further, the step of extracting respective characteristic point in several described biometric images further comprises：

Several described biometric images are transmitted to the processing list with image processor GPU and central processor CPU Member；The image information of several biometric images is assigned in the block block of GPU and carries out operation, and combines the collection of CPU Middle scheduling and distribution function calculate the respective characteristic point of several described biometric images.

Further, described based on respective characteristic point in several biometric images described in extraction, it is special to generate biology The step of feature point cloud data of sign, further comprises：

According to the feature of respective characteristic point in several biometric images described in extraction, the matching of characteristic point is carried out, Establish matched characteristic point data collection；

According to the optical information of Visible Light Camera, phase of each Visible Light Camera relative to biological characteristic spatially is calculated To position, and calculate according to the relative position space of characteristic point at a time in several described biometric images Depth information；

According to the spatial depth information of matched characteristic point data collection and characteristic point on different time, biological characteristic is generated Feature point cloud data.

Further, the feature of respective characteristic point is converted using scale invariant feature in several described biometric images SIFT feature describes son to describe；

According to the optical information of more Visible Light Cameras, each Visible Light Camera is calculated in certain a period of time using light-stream adjustment Carve the relative position relative to biological characteristic spatially；The spatial depth of characteristic point in several described biometric images is believed Breath includes：Spatial positional information and colouring information.

Further, the step of four dimension module that biological characteristic is built according to the feature point cloud data further wraps It includes：

Set the reference dimension of four dimension modules to be built；

According to the spatial positional information of the reference dimension and the feature point cloud data, the feature point cloud data is determined In each characteristic point bulk and time size, to build four dimension modules of biological characteristic.

Further, four dimension modules of the biological characteristic include at least one following 4 D data：

Spatial form characteristic of four dimension modules on different time is described；

Surface texture feature data of four dimension modules on different time are described；

Facing material and light characteristic of four dimension modules on different time are described.

Further, camera matrix is formed using more Visible Light Cameras to adopt the biological information of organism Collection is laid out camera matrix in the following manner：

Support construction is built, arc bearing structure is set in the support construction；

More Visible Light Cameras are arranged in the arc bearing structure.

Further, the organism is human body, and the identity information includes：In name, gender, age and certificate number It is one or more.

Further, the certificate number includes one in identification card number, passport No., license number, social security number or officer's identity card number Kind is a variety of；

Further, the biological information is header information, facial information and/or iris information, then the method Further include：

The pedestal being connect with the support construction is built, on the base seat of the setting for human body picture-taking position；

When human body is located on the seat, more Visible Light Camera groups being arranged in the arc bearing structure are utilized At camera matrix the header information of human body, facial information and/or iris information are acquired.

Further, display is set in the arc bearing structure；

After structure obtains four dimension modules of head, face and/or iris, shown over the display by visual means 4 D data；

Using more Visible Light Cameras composition camera matrix to header information, facial information and/or iris information into Before row acquisition, by display interfaces, the parameter of taking pictures of each Visible Light Camera is set.

Further, when the step S03 is to the identification of target organism, using temmoku point cloud matching identification method pair Four dimension of biological characteristic stored in the biological characteristic 4 D data (T1, T2 ... Tn) of the target organism and the database It is compared according to (D1, D2 ... Dn)；The temmoku point cloud matching identification method includes the following steps：

S301. characteristic point is fitted；

S302. curved surface entirety best fit；

S303. similarity calculation.

Further, the temmoku point cloud matching identification method comprises the following specific steps that：

Characteristic point fitting is carried out using based on spatial domain directly matched method, in the corresponding rigid region of two clouds, It chooses three and features above point is used as fitting key point, pass through coordinate transform, directly carry out characteristic point Corresponding matching；

After characteristic point Corresponding matching, the alignment of data of the point cloud after whole curved surface best fit；

Similarity calculation is carried out using least square method.

The present invention also provides a kind of biological characteristic 4 D data identifying systems taken pictures based on visible light, which is characterized in that Including following device：

Collecting biological feature information device, for acquiring several biometric images of organism within given time, and Four dimension modules that biological characteristic is built according to several described biometric images, the biological characteristic to realize the organism are four-dimensional Data acquire；

Biological characteristic 4 D data storage device, for scanning or the identity information of typing organism (I1, I2 ... In), with The identity information (I1, I2 ... In) stores collected biological characteristic 4 D data as distinguishing mark, forms packet Include the database of a plurality of biological characteristic 4 D data (D1, D2 ... Dn)；

The identity recognition device of target organism, for according to scanning or typing target organism identity information (I1, I2 ... In) find the biological characteristic 4 D data (D1, D2 ... Dn) stored in the database, and by the target organism Biological characteristic 4 D data (T1, T2 ... Tn) respectively with stored in the corresponding database biological characteristic 4 D data (D1, D2 ... Dn) it is compared, to identify the identity of target organism.

Further, the collecting biological feature information device includes：

Image acquisition units, the camera matrix for being formed using more cameras are acquired biological information, obtain To several biometric images；

Feature point extraction unit, for handling several described biometric images, several described biologies of extraction are special Levy respective characteristic point in image；

Point cloud generation unit, for based on respective characteristic point in several biometric images described in extraction, generating life The feature point cloud data of object feature；

Four-dimensional model construction unit, four dimension modules for building biological characteristic according to the feature point cloud data, with reality The acquisition of existing biological characteristic 4 D data.

Beneficial effects of the present invention：Provide a kind of biological characteristic 4 D data recognition methods taken pictures based on visible light and System is specifically that the camera matrix formed using more Visible Light Cameras is acquired biological information in method, obtains To several biometric images on different moments；And then several biometric images are handled, extract several biologies Respective characteristic point in characteristic image；Subsequently, based on respective characteristic point in several biometric images of extraction, biology is generated The feature point cloud data of feature；Later, four dimension modules that biological characteristic is built according to feature point cloud data, to realize biological characteristic The acquisition of 4 D data.It can be seen that the embodiment of the present invention carries out biological characteristic letter using more Visible Light Camera control technologies The acquisition of breath can significantly improve the collecting efficiency of biological information；Also, the embodiment of the present invention is biological special using collecting The characteristic information of sign spatially completely restores the various features of biological characteristic spatially, is subsequent biological characteristic number According to application provide unlimited possibility.To identify that the identity information of target identifies 4 D data, it is not necessary to by the number of target person It is compared one by one according to the mass data in database, improves the efficiency of matching identification, greatly improve identification Speed carries out characteristic point fitting using based on the directly matched temmoku point cloud matching identification method in spatial domain, realizes biological characteristic point Fast Fitting compare, and then realize identity rapid authentication identification.In addition, the face of people and hand are knots rigid and flexible Zoarium, for flexible portion because action variation has different forms, such as expression shape change, facial muscle can change correspondingly state, Hand carries out different actions, and hand state can also change correspondingly.Therefore different 3D renderings can be formed, if special with individual data Sign identifies can there is error.Therefore several biometric images of Visible Light Camera acquisition organism within given time, root Build four dimension modules of biological characteristic according to several described biometric images, realize and the 4 D data of organism is acquired, after deposit It stores up and is associated with to the identity information of organism, when whether again identify that target organism is the organism identity, even if target Organism such as face's espressiove or hand have action, also the identity of recognizable object organism, further improve identification essence Degree.

Description of the drawings

By reading the detailed description of hereafter preferred embodiment, various other advantages and benefit are common for this field Technical staff will become clear.Attached drawing only for the purpose of illustrating preferred embodiments, and is not considered as to the present invention Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings：

Fig. 1 shows the biological characteristic 4 D data recognition methods according to an embodiment of the invention taken pictures based on visible light Flow chart；

Fig. 2 shows the biological characteristic 4 D data acquisition method streams taken pictures based on visible light according to one embodiment of the invention Cheng Tu；

Fig. 3 show header information according to an embodiment of the invention, facial information and/or iris information 4 D data The schematic diagram of identifying system；

Fig. 4 shows the connection of the internal module of bearing structure and outside in 4 D data identifying system shown in Fig. 3 Schematic diagram；

Fig. 5 shows serial ports integration module, camera matrix and central processing mould in 4 D data identifying system shown in Fig. 3 The schematic diagram of the connection of block；

Fig. 6 shows the schematic diagram of 4 D data identifying system equipment according to another embodiment of the present invention；

Fig. 7 shows the structural schematic diagram of 4 D data harvester according to an embodiment of the invention；And

Fig. 8 shows the structural schematic diagram of 4 D data harvester according to another embodiment of the present invention.

Specific implementation mode

The exemplary embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although showing the disclosure in attached drawing Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure Completely it is communicated to those skilled in the art.

In order to solve the above technical problems, an embodiment of the present invention provides a kind of biological characteristic taken pictures based on visible light is four-dimensional Data identification method and system.It should be noted that the 4 D data in the present invention refers to three-dimensional space data binding time dimension Degrees of data is formed by data, and three dimensions binding time dimension refers to：Multiple same time intervals or different time intervals, no The data acquisition system that the image or image of situations such as same angle, different direction or different conditions is formed.4 D data is more in other words Open the 3D data acquisition systems at same time interval or different time intervals, different angle, different direction, different expression forms etc..Institute The head said refers to all organs of human body neck (cervical vertebra) or more；Described face refers to face and ear.

Fig. 1 shows the biological characteristic 4 D data recognition methods according to an embodiment of the invention taken pictures based on visible light Flow chart：

S01. biological information is acquired,

S02. biological characteristic 4 D data is stored,

S03. the identification of target organism,

Preferably, as shown in Fig. 2, step S01 acquisition biological informations can also specifically include following steps S102 extremely Step S108.

Step S102 is acquired biological information using more Visible Light Cameras, obtains on different moments Several biometric images, it is preferred that more Visible Light Camera composition camera matrixes are acquired organism；

Step S104 handles several collected biometric images, extracts respective in biometric image Characteristic point；

Step S106, respective characteristic point in several biometric images based on extraction, generates the feature of biological characteristic Point cloud data；

Step S108 builds four dimension modules of biological characteristic according to feature point cloud data, to realize organism biological characteristic The acquisition of 4 D data.

The present embodiment carries out the acquisition of biological information using more Visible Light Camera control technologies, can significantly improve The collecting efficiency of biological information；Also, the embodiment of the present invention completely restores biology using biological information is collected The various features of feature spatially provide unlimited possibility for the application of subsequent biological attribute data.

In another embodiment of the invention, a camera can be used to carry out collecting biological feature information, at this moment, this Camera can turn around shooting along planned orbit, to realize to the multi-angled shooting of biological information, obtain several lifes Object characteristic image.

Preferably, it by several biometric images of above-mentioned acquisition, is transmitted to image processor GPU and central processing The processing unit of device CPU；The image information of several biometric images is assigned in the block block of GPU and carries out operation, and tied Centralized dispatching and the distribution function for closing CPU, calculate the respective characteristic point of several biometric images.It can be seen that the present invention is real The acquisition that example carries out biological information using more photographing camera control technologies is applied, biological information can be significantly improved Collecting efficiency.Also, parallel computation of the embodiment of the present invention based on central processing unit and graphics processor, can efficiently be realized The processing of characteristic information.

Preferably, GPU is double GPU, and every GPU has a multiple block, such as 56 block, the embodiment of the present invention to this not It is restricted.

In the alternative embodiment of the present invention, in above step S106 in several biometric images based on extraction respectively Characteristic point, generate the feature point cloud data of biological characteristic, can be specifically to include the following steps S1061 to step S1063.

Step S1061 carries out characteristic point according to the feature of respective characteristic point in several biometric images of extraction Matching, establishes matched characteristic point data collection.

Step S1062 calculates each camera relative to biological characteristic in sky according to the optical information of more Visible Light Cameras Between on relative position, and calculate according to relative position the spatial depth information of the characteristic point in several biometric images.

Step S1063 generates biological characteristic according to the spatial depth information of matched characteristic point data collection and characteristic point Feature point cloud data.

In above step S1061, SIFT may be used in the feature of respective characteristic point in several biometric images (Scale-Invariant Feature Transform, scale invariant feature conversion) Feature Descriptor describes.SIFT feature Description has 128 feature description vectors, and the spy of 128 aspects of any characteristic point can be described on direction and scale Sign significantly improves the precision to feature description, while Feature Descriptor has independence spatially.

In step S1062, according to the optical information of more Visible Light Cameras, each camera is calculated relative to biological characteristic Relative position spatially, an embodiment of the present invention provides a kind of optional schemes, in this scenario, can according to more The optical information of light-exposed camera, using light-stream adjustment calculate each camera at a time relative to biological characteristic spatially Relative position.

In the definition of light-stream adjustment, it is assumed that at a time there are one the point in 3d space, it is by positioned at different positions The multiple cameras set are seen, then light-stream adjustment is to extract this 3d space of the moment from these various visual angles information The coordinate and the relative position of each camera and the process of optical information of point.

Further, the space of the characteristic point at a time several biometric images referred in step S1062 Depth information may include：Spatial positional information and colouring information, that is, can be X axis coordinate of the characteristic point in spatial position, spy Sign point is in the Y axis coordinate of spatial position, characteristic point in the channels R of the Z axial coordinates of spatial position, the colouring information of characteristic point The colouring information of the value in the channels G of the colouring information of value, characteristic point, the value of the channel B of the colouring information of characteristic point, characteristic point The value etc. in the channels Alpha.In this way, containing the spatial positional information and color letter of characteristic point in the feature point cloud data generated Breath, the format of feature point cloud data can be as follows：

X1 Y1 Z1 R1 G1 B1 A1

X2 Y2 Z2 R2 G2 B2 A2

……

Xn Yn Zn Rn Gn Bn An

Wherein, X axis coordinate of the Xn expression characteristic points in spatial position；Y axis coordinate of the Yn expression characteristic points in spatial position； Z axis coordinate of the Zn expression characteristic points in spatial position；Rn indicates the value in the channels R of the colouring information of characteristic point；Gn indicates feature The value in the channels G of the colouring information of point；Bn indicates the value of the channel B of the colouring information of characteristic point；An indicates the color of characteristic point The value in the channels Alpha of information.

In embodiments of the present invention, the dimension of time is added in the biological characteristic of 3D, constitutes four-dimensional biological characteristic, completely The various features for restoring biology, unlimited possibility is provided for the application of subsequent biological attribute data.

In the alternative embodiment of the present invention, the four of biological characteristic are built according to feature point cloud data in above step S108 Dimension module can be specifically the reference dimension for setting four dimension modules to be built；And then according to reference dimension and characteristic point cloud number According to spatial positional information, the bulk of each characteristic point and time size in feature point cloud data are determined, to build life Four dimension modules of object feature.

May include the space shape for describing four dimension modules on different time in four dimension modules of the biological characteristic of structure Shape characteristic, surface texture feature data of four dimension modules of description on different time, four dimension modules of description are in different time On Facing material and 4 D datas, the embodiment of the present invention such as light characteristic this is not restricted.

In the alternative embodiment of the present invention, the camera square of more Visible Light Cameras composition is utilized in above step S102 Before battle array is acquired biological information, more Visible Light Cameras can also be laid out, are laid out the side of more Visible Light Cameras Method may comprise steps of S202 to step S204.

Step S202 builds support construction, and arc bearing structure is arranged on the support structure；And

More Visible Light Cameras are arranged in arc bearing structure by step S204.

It can be seen that the embodiment of the present invention carries out adopting for biological information using more Visible Light Camera control technologies Collection, can significantly improve the collecting efficiency of biological information.Also, more cameras are arranged in arc bearing structure and form phase Machine matrix.

Further, when the biological characteristic difference for needing to acquire, the specific acquisition mode of step S102 is not yet Together, it will describe in detail respectively below.

Situation one can take if biological information is header information, facial information and/or the iris information of human body The pedestal being connect with support construction is built, seat of the setting for fixing human picture-taking position on pedestal；When people is located on seat When, using the camera matrix for the more Visible Light Cameras composition being arranged in arc bearing structure to its head, face and/or rainbow Film information is acquired.

In an alternate embodiment of the invention, can also display be set in arc bearing structure；Head face is obtained in structure Four dimension modules after, over the display pass through visual means show head face 4 D data.

In an alternate embodiment of the invention, head facial information is carried out in the camera matrix formed using more Visible Light Cameras Before acquisition, the parameter of taking pictures of each camera can also be set by display interfaces, such as sensitivity, shutter speed, zoom times Number, aperture etc., the embodiment of the present invention is without being limited thereto.

Preferably, in step S02, the collected biological characteristic 4 D data of storing step S01 institutes, and with organism Identity information (I1, I2 ... In) stores collected biological characteristic 4 D data as distinguishing mark, and it includes more to be formed The database of biological characteristic 4 D data (D1, D2 ... Dn), such as：The identity information I1 of 4 D data D1 and the organism into Row associated storage, the 4 D data D2 of another organism and the identity information I2 of the organism are associated storage, and so on, Formation includes the database of n organism 4 D data.

Wherein, when acquisition target, that is, organism is human body, then identity information I includes but not limited to people's：Name, property , not one or more in age and certificate number, certificate number may include people in life commonly used such as identification card number, It is one or more in passport No., license number, social security number or officer's identity card number.

Preferably, the identity information is obtained by scanning identity card, passport, driving license, social security card or officer's identity card, alternatively, Manually or automatically the mode of typing obtains identity information from identity card, passport, driving license, social security card or officer's identity card.

Preferably, in identifications of the step S03 to target organism, using temmoku point cloud matching identification method to target The life stored in the biological characteristic 4 D data (T1, T2 ... Tn) and database of organism (organism of identity i.e. to be identified) Object feature 4 D data (D1, D2 ... Dn) is compared, to identify the identity of target organism.First, by inputting target life The identity information of object can be quickly found out have stored in database with the identity card in this way such as the identification card number of human body Number be filename 4 D data (D1, D2 ... Dn), without in the data and database by target person mass data carry out It compares one by one, improves the efficiency of matching identification, greatly improve the speed of identification, be then somebody's turn to do again currently collected The 4 D data (T1, T2 ... Tn) of human body is compared with the 4 D data taken out in data, finally identifies the human body Whether identity meets, and then realizes authentication, specifically, being included the following steps using temmoku point cloud matching identification method：

S301. characteristic point is fitted；

S302. curved surface entirety best fit；

S303. similarity calculation.

Preferably, temmoku point cloud matching identification method further includes following specific steps：

Similarity calculation is carried out using least square method.

Temmoku point cloud matching identification method (Yare Eyes point cloud match recognition method) is known Other process and operation principle are as follows：First, point cloud at a time is the basic element for forming four dimension modules, it includes space Coordinate information (XYZ) and colouring information (RGB).The attribute of point cloud includes spatial resolution, positional accuracy, surface normal etc.. Its feature is not influenced by external condition, will not all be changed for translating and rotating.Reverse software can carry out a cloud Editor and processing, such as：Imageware, geomagic, catia, copycad and rapidform etc..Temmoku point cloud, which compares, to be known Other method is distinctive to include based on the directly matched method in spatial domain：Iteration closest approach method ICP (Iterative closest Point), ICP methods are generally divided into two steps, the fitting of first step characteristic point, second step curved surface entirety best fit.First fitting alignment The purpose of characteristic point is in order to which the shortest time is found and is aligned two clouds of fitting to be compared.But not limited to this.Such as it can be with It is：

The first step chooses three and features above point is used as fitting key point in the corresponding rigid region of two clouds, By coordinate transform, characteristic point Corresponding matching is directly carried out.

ICP is a very effective tool in 3D data reconstruction process, at certain for curve or the registration of curved surface segment One moment gave the rough initial alignment condition of two 3D models, and ICP iteratively seeks rigid transformation between the two with minimum Change alignment error, realizes the registration of the space geometry relationship of the two.

Given setWithSet element two model surfaces of expression Coordinate points, ICP registration techniques iteratively solve apart from nearest corresponding points, establish transformation matrix, and implement transformation to one of, Until reaching some condition of convergence, its coding of iteration stopping is as follows：

1.1ICP algorithm

Input .P₁, P₂.

P after output is transformed₂

P₂(0)=P₂, l=0；

Do

For P₂(l) each point in

A nearest point y is looked in P1₁；

End For

It calculatesRegistration error E；

If E are more than a certain threshold value

Calculate P₂(l) the transformation matrix T (l) between Y (l)；

P₂(l+1)=T (l) P₂(l), l=l+1；

Else

Stop；

End If

While||P₂(l+l)-P₂(l)||>threshold；

Wherein registration error

1.2 matchings based on local feature region：

By taking the identification of human face's information as an example, faceform is broadly divided into rigid model part and plasticity model part, plasticity The accuracy of deformation effect alignment, and then influence similarity.Second of gathered data has local difference to plasticity model for the first time, A kind of solution route be only in rigid region selected characteristic point, characteristic point be extracted from an object, under certain condition Constant attribute is stablized in holding, and alignment is fitted to characteristic point using iteration closest approach method ICP.

Extraction face is by the smaller region of expression influence first, such as nasal area nose, eye outer frame angle, forehead region, cheekbone Bone region, ear region etc..Human hands finger joint is rigid region, and metacarpus is plastic region, in finger portion region selected characteristic point It is best.Iris is rigid model.

Requirement to characteristic point：

1) completeness contains object information as much as possible, is allowed to be different from the object of other classifications；2) compactedness tables It is as few as possible up to required data volume；3) feature is also required preferably to be remained unchanged under model rotation, translation, mirror transformation.

In 3D living things feature recognitions, using two 3D biological characteristic model point clouds of alignment, the similar of input model is calculated Degree, wherein registration error is as difference measure.

Second step：After characteristic point best fit, the alignment of data of the point cloud after whole curved surface best fit.

Third walks, similarity calculation.Least square method

Least square method (also known as least squares method) is a kind of mathematical optimization techniques.It by minimize error quadratic sum Find the optimal function matching of data.Unknown data can be easily acquired using least square method, and these are acquired Data and real data between error quadratic sum be minimum.Least square method can also be used for curve matching.It is some other excellent Change problem can also be expressed by minimizing energy or maximizing entropy with least square method.It is usually used in solving curve fit problem, And then solve the complete fitting of curved surface.It can accelerate Data Convergence by iterative algorithm, quickly acquire optimal solution.

If 3D data models at a time are inputted with stl file format, pass through calculating point cloud and triangle The distance of piece determines its deviation.Therefore, this method needs to establish plane equation to each tri patch, and deviation arrives flat for point The distance in face.And be IGES or STEP models for 3D data models at a time, since free form surface expression-form is The faces NURBS, so the distance calculating in point to face needs the method for using numerical optimization to be calculated.By in iterative calculation point cloud Each point expresses deviation to the minimum range of nurbs surface, or that nurbs surface carried out specified scale is discrete, with point and point Apart from approximate expression point deviation, or it is converted into STL formats and carries out deviation calculating.Different coordinate alignment and deviation calculating side The testing result of method, acquisition is also different.The size of alignment error will directly affect the confidence level of accuracy of detection and assessment report.

Best fit alignment is that detection error averagely arrives entirety, is terminated in terms of iteration by ensureing the whole minimum condition of deviation The alignment procedure of calculation carries out 3D analyses to registration result, generates result object in the form of the root mean square of error between two figures Output, root mean square is bigger, and difference of two models of reflection at this is bigger.Vice versa.Judge according to registration ratio is compared Whether it is to compare subject matter.

The present invention also provides a kind of biological characteristic 4 D data identifying systems taken pictures based on visible light comprising following dress It sets：

Collecting biological feature information device, for acquiring several biometric images of organism within given time, and Four dimension modules that biological characteristic is built according to several biometric images, to realize that the biological characteristic 4 D data of organism is adopted Collection；

Biological characteristic 4 D data storage device, is used to scan or the identity information of typing organism (I1, I2 ... In) is made Storage is associated to collected biological characteristic 4 D data for distinguishing mark, formation includes a plurality of biological characteristic 4 D data The database of (D1, D2 ... Dn)；

The identity recognition device of target organism, for according to scanning or typing target organism identity information (I1, I2 ... In) find the biological characteristic 4 D data (D1, D2 ... Dn) stored in database, and by the biology of the target organism Feature 4 D data (T1, T2 ... Tn) respectively with biological characteristic 4 D data (D1, D2 ... for being stored in the corresponding database Dn it) is compared, to identify the identity of target organism.

Preferably, collecting biological feature information device includes：

Feature point extraction unit is extracted for handling several biometric images in several biometric images Respective characteristic point；

It is special to generate biology for respective characteristic point in several biometric images based on extraction for point cloud generation unit The feature point cloud data of sign；

Four-dimensional model construction unit, four dimension modules for building biological characteristic according to feature point cloud data, to realize life The acquisition of object feature 4 D data.

It should be noted that the biological characteristic in the embodiment of the present invention is not limited to above-mentioned head, face and/or rainbow Film and hand, can also be without limitation including other biological feature, such as foot, the embodiment of the present invention.

It is four-dimensional to the biological characteristic provided in an embodiment of the present invention taken pictures based on visible light below by specific embodiment Data identification method and system are described further.

In one embodiment of the present of invention, the 3D data recognition systems of header information, facial information and/or iris information are such as Shown in Fig. 3, which may include：

Pedestal 31, the main lower support structure as entire invention equipment；

Seat 32, fixed take pictures position of human body and adjusting human height；

Support construction 33 connects bottom and other main body mechanisms of equipment；

Display 34, the operation interface of device systems work；

Bearing structure 35, camera, central processing unit, light fixed structure；

Camera matrix 36, the 3D data acquisition of human body head information, facial information and/or iris information；

Band-like light compensating lamp 37, environment light supplement use.

The connection relation explanation of equipment

Pedestal 31 is connected by connection structure with seat 32；

Pedestal 31 is connected by mechanism connection structure with support construction 33；

Support construction 33 is connected by mechanical connecting structure with bearing structure 35；

Display 34 is by being mechanically anchored in bearing structure 35；

Camera matrix 36 is fixed on by the fixed mode of structure in bearing structure 35；

Band-like light compensating lamp 37 is fixed on by the fixed mode of structure in bearing structure 35.

The internal module composition of (1-2) bearing structure 35 is as follows.

As shown in figure 4, the internal module of bearing structure 35 can be made of following several parts：

Power management module is responsible for providing the required various power supplys of whole system；

Light management module can adjust the brightness of light by central processing module；

Serial ports integration module is responsible for the both-way communication of central processing module and camera matrix；

Central processing module is responsible for system information processing, display, the control of light, seat；

Further include identification module in central processing module, is used for the identification of target organism, first gives birth to target The biological characteristic 4 D data (T1, T2 ... Tn) of object respectively with the biological characteristic 4 D data that is stored in corresponding database (D1, D2 ... Dn) is compared, then using the identity of temmoku point cloud matching identification method identification target organism；

Seat lifts management module, is responsible for height of seat adjustment；

It shows driven management module, is responsible for the display driving of display.

The internal module of bearing structure 35 and the connection relation of outside are as follows：

1) power management module is to camera matrix, serial ports integration module, light management module, central processing module, display Driven management module, seat lifting management module provide power supply；

2) serial ports integration module connection camera matrix and central processing module, realize the both-way communication between them, such as Fig. 5 It is shown；

2.1) camera is connected in a manner of serial ports with serial ports integration module in a manner of independent part

2.2) serial ports integration module is connected by USB interface with central processing module

2.3) central processing module realizes the visualized operation with camera matrix by the software interface of customized development

2.4) may be implemented to take pictures to camera in operation interface the setting of parameter

Sensitivity ISO (range 50~6400)

Shutter speed (1/4000~1/2) (second)

Zoom magnification (1~3.8x)

Aperture (big/small)

2.5) initialization operation being switched on to camera may be implemented in operation interface

2.6) order of camera image acquisition may be implemented in operation interface

2.7) setting in camera image storage path may be implemented in operation interface

2.8) browsing of camera real-time imaging and the switching of camera may be implemented in operation interface

3) light management module connection power management module, central processing module and external band-like light compensating lamp；

4) seat lifting management module connection power management module, central processing module and external seat, central processing Module realizes the up and down adjustment to height of seat by visualization interface；

5) display driven management module connection power management module, central processing module and the display of outside；

6) central processing module connection power management module, light management module, seat lifting management module, serial ports are integrated Module, display driven management module.

Equipment application method is as follows

A. starting device：After turning on the power switch, central processing unit, camera matrix, band-like light compensating lamp is respectively started.

B. parameter setting：By display interfaces, the parameters that camera matrix is taken pictures can be set.

C. information collection：After parameter setting, starts matrix camera and starts to carry out information collection to human body head face, The information collection time completes in 0.8 second, and the signal of acquisition finally reaches central processing mould with the format of digital picture (.jpg) Block is handled, and central processing module core is made of following components：

C.1CPU (Central Processing Unit, central processing unit)：It is responsible for the transmission tune of entire digital signal Degree, task distribution, the single calculation processing of memory management and part；

C.2GPU (Graphics Processing Unit, image processing unit)：The GPU for selecting special type, has Outstanding image-capable and efficient computing capability；

C.3DRAM (Dynamic Random Access Memory, i.e. dynamic random access memory)：As entire number The temporary storage center of word signal processing needs the operational capability for matching CPU and GPU, obtains best processing and calculates efficiency.

D. information processing：The signal that matrix camera has acquired is transmitted to central processing module and carries out signal processing.

D.1 the process of information processing is as follows

D.1.1 the filtering of image is acquired

Using the characteristic of GPU, in conjunction with the characteristic of matrix operation of image filtering, image filtering can be in certain algorithm Under support, it is rapidly completed.

D.1.2 the feature point extraction of image is acquired

The GPU to match using CPU and with overall performance, because the format of the various information of this equipment is all image pane The various information contents of jpg can be evenly distributed to GPU's by formula in conjunction with the GPU with outstanding image-capable In block, since this equipment has 56 block using double GPU, every GPU itself, so the jpg that acquisition information scratching arrives Image can be evenly distributed to carry out operation above 112 block, and combine centralized dispatching and the distribution function of CPU, can be with The characteristic point that every photo has rapidly is calculated, arranges in pairs or groups the GPU's of other common models relative to independent CPU or CPU Operation, whole arithmetic speed time are the 1/10 or shorter of the latter.

D.1.3 the calculating of the matching and spatial depth information of acquisition image

The extraction of image characteristic point uses pyramidal hierarchical structure and the particular algorithm of space scale invariance, this Two kinds of special algorithms are all the special tectonics of the GPU in conjunction with this equipment choosing, play the calculated performance of system to the greatest extent, Realize the characteristic point in rapid extraction image information.

The Feature Descriptor of this process has 128 feature descriptions using SIFT feature description, SIFT feature description Vector can describe the feature of 128 aspects of any characteristic point on direction and scale, significantly improve the essence to feature description Degree, while Feature Descriptor has independence spatially.

The particular image that this equipment uses handles GPU, the calculating with excellent independent vector and processing capacity, for adopting For SIFT feature vector with 128 special description, it is to be most suitable for only to be handled under conditions of special GPU in this way , the specific calculations ability of the GPU can be given full play to, compares and is arranged in pairs or groups other common specifications using common CP U or CPU The match time of GPU, characteristic point can reduce by 70%.

Feature Points Matching finishes, and system can use the algorithm of light-stream adjustment to calculate camera relative to head face in sky Between on relative position, according to the space coordinate of this relative position, GPU can rapidly calculate the depth of head face feature point Spend information.

D.1.4 the generation of feature point cloud data

According to depth information of the head face feature point in space is D.1.3 calculated, since the GPU vectors having calculate energy Power can rapidly match spatial position and the colouring information of head face feature point cloud, and the model for forming a standard is built The vertical point cloud information needed.

E. characteristic size is demarcated：By the standard of characteristic point cloud size, initial reference is set for the size of entire model Size.

By the special calibration in information collection, which there is space to determine size, since head face is special Sign point cloud has spatially consistency of scale, is sized really by the special calibration, between any characteristic point of head face Size can be calculated from the spatial position coordinate of cloud.

F. the subsequent processing of data：It can by the way that point cloud data is further processed based on the size demarcated in E To obtain the 3D data of face head face or iris at a time.

The format of 3D data has following several files：

.obj --- the spatial form feature of description 3D models

.jpg --- the surface texture feature of description 3D models

.mtl --- the Facing material and light feature of description 3D models

G. face 4 D data in head is shown over the display by visualization method.

Identification module in central processing module finds the number according to the identity information (I1, I2 ... In) of target organism According to the biological characteristic 4 D data (D1, D2 ... Dn) stored in library, and by the biological characteristic 4 D data of the target organism (T1, T2 ... Tn) is compared with the biological characteristic 4 D data (D1, D2 ... Dn) stored in the corresponding database respectively, To identify the identity of target organism, and over the display by recognition result output display.

Based on the biological characteristic 4 D data recognition methods taken pictures based on visible light that each embodiment provides above, it is based on Same inventive concept, the embodiment of the present invention additionally provide a kind of biological characteristic 4 D data acquisition dress based on Visible Light Camera It sets.

Certainly in another embodiment of the invention, can not also include seat 32, as shown in Figure 6 comprising 61 supports Seat, 62 identification devices, 63 controls and display device, 64 camera matrixes, 65 arc load carriers, 66 arc light compensating lamps, acquisition are known When other, human body station is in the U-shaped region that device surrounds.

Fig. 7 shows the biological characteristic 4 D data harvester according to an embodiment of the invention taken pictures based on visible light Structural schematic diagram.As shown in fig. 7, the device may include image acquisition units 910, feature point extraction unit 920, point cloud life At unit 930 and four-dimensional model construction unit 940.

Image acquisition units 910, for using more Visible Light Cameras composition camera matrix to biological information into Row acquisition, obtains several biometric images；

Feature point extraction unit 920 is coupled with image acquisition units 910, for being carried out to several biometric images Processing, extracts respective characteristic point in several biometric images；

Point cloud generation unit 930, is coupled with feature point extraction unit 920, is used for several biological characteristics based on extraction Respective characteristic point in image generates the feature point cloud data of biological characteristic；

Four-dimensional model construction unit 940 is coupled with a cloud generation unit 930, for being built according to feature point cloud data Four dimension modules of biological characteristic, to realize the acquisition of biological characteristic 4 D data.

In the alternative embodiment of the present invention, above-mentioned cloud generation unit 930 is additionally operable to：

According to the feature of respective characteristic point in several biometric images of extraction, the matching of characteristic point is carried out, is established Matched characteristic point data collection；

According to the optical information of more Visible Light Cameras, each camera is calculated relative to biological characteristic spatially opposite Position, and calculate according to relative position the spatial depth information of the characteristic point in several biometric images；

According to the spatial depth information of matched characteristic point data collection and characteristic point, the characteristic point cloud number of biological characteristic is generated According to.

In the alternative embodiment of the present invention, the feature of respective characteristic point uses scale not in several biometric images Become Feature Conversion SIFT feature and describes son to describe.

According to the optical information of more Visible Light Cameras, each camera is calculated relative to biological characteristic using light-stream adjustment Relative position spatially.

In the alternative embodiment of the present invention, the spatial depth information of the characteristic point in several biometric images includes： Spatial positional information and colouring information.

In the alternative embodiment of the present invention, above-mentioned four-dimension model construction unit 940 is additionally operable to：

Set the reference dimension of four dimension modules to be built；

According to the spatial positional information of reference dimension and feature point cloud data, each characteristic point in feature point cloud data is determined Bulk and time size, to build four dimension modules of biological characteristic.

In the alternative embodiment of the present invention, four dimension modules of biological characteristic include at least one following four dimensions According to：

In the alternative embodiment of the present invention, such as scheme8It is shown, upper texts and pictures7The device of displaying can also include：

Camera matrix layout unit 1010, is coupled with image acquisition units 910, in 910 profit of image acquisition units Before the camera matrix formed with more Visible Light Cameras is acquired biological information, it is laid out more in the following manner Visible Light Camera：

Support construction is built, arc bearing structure is set on the support structure；

More Visible Light Cameras are arranged in arc bearing structure.

In this embodiment, more cameras are arranged in formation camera matrix in arc bearing structure.

In the alternative embodiment of the present invention, if biological information is head facial information, above-mentioned image acquisition units 910 are additionally operable to：

The pedestal being connect with support construction is built, seat of the setting for fixed biological picture-taking position on pedestal；

When biology is located on seat, the camera for the more Visible Light Cameras composition being arranged in arc bearing structure is utilized Matrix is acquired head facial information.

In the alternative embodiment of the present invention, as shown in figure 8, the device of figure 7 above displaying can also include：

First display unit 1020 is coupled with four-dimensional model construction unit 940, for being arranged in arc bearing structure Display；After structure obtains four dimension modules of head face, head face four is shown by visual means over the display Dimension data.

In the alternative embodiment of the present invention, above-mentioned image acquisition units 910 are additionally operable to：

Before the camera matrix formed using more Visible Light Cameras is acquired head facial information, pass through display Device interface sets the parameter of taking pictures of each camera.

An embodiment of the present invention provides a kind of biological characteristic 4 D data recognition methods taken pictures based on visible light and system, It is specifically that the camera matrix formed using more Visible Light Cameras is acquired biological information in method, is given Several biometric images in time；And then several biometric images are handled, extract several biometric images In respective characteristic point；Subsequently, based on respective characteristic point in several biometric images of extraction, the spy of biological characteristic is generated Levy point cloud data；Later, four dimension modules that biological characteristic is built according to feature point cloud data, to realize biological characteristic 4 D data Acquisition.It can be seen that the embodiment of the present invention carries out the acquisition of biological information using more Visible Light Camera control technologies, The collecting efficiency of biological information can be significantly improved；Also, the embodiment of the present invention utilizes and collects biological characteristic in space On characteristic information, completely restore biological characteristic various features spatially, be the application of subsequent biological attribute data Provide unlimited possibility.

Further, parallel computation of the embodiment of the present invention based on central processing unit and graphics processor, can be rapidly and efficiently It realizes the processing of characteristic information and puts the generation of cloud in ground.Also, using scale invariant feature conversion SIFT feature description son knot The computation capability for closing special graph processor, can fast implement the generation of the matching and space characteristics point cloud of characteristic point. In addition, using unique sizing calibration method, can quickly and accurately extract any characteristic point of biological characteristic bulk and Time size generates four dimension modules of biological characteristic, to realize the acquisition of 4 D data.

In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that the implementation of the present invention Example can be put into practice without these specific details.In some instances, well known method, structure is not been shown in detail And technology, so as not to obscure the understanding of this description.

Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of each inventive aspect, Above in the description of exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes In example, figure or descriptions thereof.However, the method for the disclosure should be construed to reflect following intention：It is i.e. required to protect Shield the present invention claims the more features of feature than being expressly recited in each claim.More precisely, as following Claims reflect as, inventive aspect is all features less than single embodiment disclosed above.Therefore, Thus the claims for following specific implementation mode are expressly incorporated in the specific implementation mode, wherein each claim itself All as a separate embodiment of the present invention.

Those skilled in the art, which are appreciated that, to carry out adaptively the module in the equipment in embodiment Change and they are arranged in the one or more equipment different from the embodiment.It can be the module or list in embodiment Member or component be combined into a module or unit or component, and can be divided into addition multiple submodule or subelement or Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it may be used any Combination is disclosed to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so to appoint Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (including adjoint power Profit requires, abstract and attached drawing) disclosed in each feature can be by providing the alternative features of identical, equivalent or similar purpose come generation It replaces.

In addition, it will be appreciated by those of skill in the art that although some embodiments described herein include other embodiments In included certain features rather than other feature, but the combination of the feature of different embodiments means in of the invention Within the scope of and form different embodiments.For example, in detail in the claims, embodiment claimed it is one of arbitrary It mode can use in any combination.

The all parts embodiment of the present invention can be with hardware realization, or to run on one or more processors Software module realize, or realized with combination thereof.It will be understood by those of skill in the art that can use in practice Microprocessor or digital signal processor (DSP) are according to the ... of the embodiment of the present invention biological special based on Visible Light Camera to realize Levy some or all functions of some or all components in 4 D data harvester.The present invention is also implemented as using In executing some or all equipment or program of device of method as described herein (for example, computer program and meter Calculation machine program product).It is such to realize that the program of the present invention may be stored on the computer-readable medium, or can have one The form of a or multiple signals.Such signal can be downloaded from internet website and be obtained, or above be carried in carrier signal For, or provide in any other forms.

It should be noted that the present invention will be described rather than limits the invention for above-described embodiment, and ability Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.In the claims, Any reference mark between bracket should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not Element or step listed in the claims.Word "a" or "an" before element does not exclude the presence of multiple such Element.The present invention can be by means of including the hardware of several different elements and being come by means of properly programmed computer real It is existing.In the unit claims listing several devices, several in these devices can be by the same hardware branch To embody.The use of word first, second, and third does not indicate that any sequence.These words can be explained and be run after fame Claim.

So far, although those skilled in the art will appreciate that present invention has been shown and described in detail herein multiple shows Example property embodiment still without departing from the spirit and scope of the present invention, still can according to the present disclosure directly Determine or derive many other variations or modifications consistent with the principles of the invention.Therefore, the scope of the present invention is understood that and recognizes It is set to and covers other all these variations or modifications.

Claims

1. a kind of biological characteristic 4 D data recognition methods taken pictures based on visible light, which is characterized in that include the following steps：

S01. biological information is acquired,

Several biometric images of organism within given time are acquired by Visible Light Camera, it is special according to several described biologies Four dimension modules for levying picture construction biological characteristic, to realize that the biological characteristic 4 D data of the organism acquires；

S02. biological characteristic 4 D data is stored,

The identity information (I1, I2 ... In) of scanning or typing organism is marked using the identity information (I1, I2 ... In) as identification Will is associated storage to collected biological characteristic 4 D data, and formation includes a plurality of biological characteristic 4 D data (D1, D2 ... Dn database)；

S03. the identification of target organism,

Acquire the biological characteristic 4 D data (T1, T2 ... Tn) of target organism, and target organism described in scanning or typing Identity information (I1, I2 ... In) is found in the database by the identity information (I1, I2 ... In) of the target organism and is deposited The biological characteristic 4 D data (D1, D2 ... Dn) of storage, by the biological characteristic 4 D data (T1, T2 ... Tn) of the target organism It is compared respectively with the biological characteristic 4 D data (D1, D2 ... Dn) stored in the corresponding database, to identify target The identity of organism.

2. according to the method described in claim 1, it is characterized in that, step S01 further includes：

Several described biometric images are handled, respective characteristic point in several described biometric images is extracted；

Based on respective characteristic point in several biometric images described in extraction, the feature point cloud data of biological characteristic is generated；

Four dimension modules that biological characteristic is built according to the feature point cloud data, to realize the acquisition of biological characteristic 4 D data.

3. according to the method described in claim 2, it is characterized in that, extracting respective feature in several described biometric images The step of point, further comprises：

Several described biometric images are transmitted to the processing unit with image processor GPU and central processor CPU；It will The image information of several biometric images, which is assigned in the block block of GPU, carries out operation, and combines the concentration tune of CPU Degree and distribution function calculate the respective characteristic point of several described biometric images.

4. according to the method described in claim 3, it is characterized in that,

It is described based on respective characteristic point in several biometric images described in extraction, generate the characteristic point cloud number of biological characteristic According to the step of further comprise：

According to the feature of respective characteristic point in several biometric images described in extraction, the matching of characteristic point is carried out, is established Matched characteristic point data collection；

According to the optical information of Visible Light Camera, opposite position of each Visible Light Camera relative to biological characteristic spatially is calculated It sets, and calculates the spatial depth of characteristic point at a time in several described biometric images according to the relative position Information；

According to the spatial depth information of matched characteristic point data collection and characteristic point on different time, the spy of biological characteristic is generated Levy point cloud data.

5. according to the method described in claim 4, it is characterized in that,

The feature of respective characteristic point is using scale invariant feature conversion SIFT feature description in several described biometric images Son describes；

According to the optical information of more Visible Light Cameras, each Visible Light Camera at a time phase is calculated using light-stream adjustment For the relative position of biological characteristic spatially；The spatial depth information packet of characteristic point in several described biometric images It includes：Spatial positional information and colouring information.

6. according to the method described in claim 3, it is characterized in that, described build biological characteristic according to the feature point cloud data Four dimension modules the step of further comprise：

Set the reference dimension of four dimension modules to be built；

According to the spatial positional information of the reference dimension and the feature point cloud data, determine each in the feature point cloud data The bulk and time size of a characteristic point, to build four dimension modules of biological characteristic.

7. according to the method described in claim 6, it is characterized in that, four dimension modules of the biological characteristic include it is following at least One of 4 D data：

8. according to the method described in claim 3, it is characterized in that, forming camera matrix to biology using more Visible Light Cameras The biological information of body is acquired, and is laid out camera matrix in the following manner：

More Visible Light Cameras are arranged in the arc bearing structure；

The organism is human body, and the identity information includes：It is one or more in name, gender, age and certificate number；

The certificate number includes one or more in identification card number, passport No., license number, social security number or officer's identity card number；

The biological information be header information, facial information and/or iris information, then the method further include：

When human body is located on the seat, the more Visible Light Cameras composition being arranged in the arc bearing structure is utilized Camera matrix is acquired the header information of human body, facial information and/or iris information.

9. according to the method described in claim 8, it is characterized in that,

Display is set in the arc bearing structure；

After structure obtains four dimension modules of head, face and/or iris, shown over the display by visual means four-dimensional Data；

Header information, facial information and/or iris information are adopted in the camera matrix formed using more Visible Light Cameras Before collection, by display interfaces, the parameter of taking pictures of each Visible Light Camera is set；

When the step S03 is to the identification of target organism, using temmoku point cloud matching identification method to the target organism Biological characteristic 4 D data (D1, the D2 ... stored in the biological characteristic 4 D data (T1, T2 ... Tn) of body and the database Dn it) is compared；The temmoku point cloud matching identification method includes the following steps：

S301. characteristic point is fitted；

S302. curved surface entirety best fit；

S303. similarity calculation；

The temmoku point cloud matching identification method comprises the following specific steps that：Feature is carried out using based on the directly matched method in spatial domain Point fitting chooses three and features above point is used as fitting key point, pass through coordinate in the corresponding rigid region of two clouds Transformation directly carries out characteristic point Corresponding matching；

Similarity calculation is carried out using least square method.

10. a kind of biological characteristic 4 D data identifying system taken pictures based on visible light, which is characterized in that including following device：

Collecting biological feature information device, for acquiring several biometric images of organism within given time, and according to Four dimension modules of several biometric images structure biological characteristic, to realize the biological characteristic 4 D data of the organism Acquisition；

Biological characteristic 4 D data storage device, for scanning or the identity information of typing organism (I1, I2 ... In), with described Identity information (I1, I2 ... In) stores collected biological characteristic 4 D data as distinguishing mark, and it includes more to be formed The database of biological characteristic 4 D data (D1, D2 ... Dn)；

The identity recognition device of target organism, for identity information (I1, I2 ... according to scanning or the target organism of typing In the biological characteristic 4 D data (D1, D2 ... Dn) stored in the database) is found, and by the biology of the target organism Feature 4 D data (T1, T2 ... Tn) respectively with biological characteristic 4 D data (D1, D2 ... for being stored in the corresponding database Dn it) is compared, to identify the identity of target organism；

The collecting biological feature information device includes：

Image acquisition units, the camera matrix for being formed using more cameras are acquired biological information, obtain more Width biometric image；

Feature point extraction unit extracts several described biological characteristic figures for handling several described biometric images The respective characteristic point as in；

Point cloud generation unit, for based on respective characteristic point in several biometric images described in extraction, it is special to generate biology The feature point cloud data of sign；

Four-dimensional model construction unit, four dimension modules for building biological characteristic according to the feature point cloud data, to realize life The acquisition of object feature 4 D data.