CN108154549A - A kind of three dimensional image processing method - Google Patents
A kind of three dimensional image processing method Download PDFInfo
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- CN108154549A CN108154549A CN201711421179.8A CN201711421179A CN108154549A CN 108154549 A CN108154549 A CN 108154549A CN 201711421179 A CN201711421179 A CN 201711421179A CN 108154549 A CN108154549 A CN 108154549A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/50—Lighting effects
- G06T15/60—Shadow generation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
- G06T7/529—Depth or shape recovery from texture
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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Abstract
The invention discloses a kind of three dimensional image processing method, this method analyzes the three-dimensional informations such as the direction of real world object shadow and scene depth figure in image by acquiring image information；And according to above- mentioned information, when being put into dummy object in the picture, the size and three-dimensional information of dummy object is adaptively adjusted.
Description
Technical field
The present invention relates to image processing fields, and in particular to a kind of three dimensional image processing method.
Background technology
Virtual reality (virtual reality, VR) technology be emulation technology with computer graphics human-machine interface technology,
The set of the multiple technologies such as multimedia technology, sensing technology, network technology is that a challenging interleaving techniques forward position is learned
Section and research field.VR mainly includes simulated environment, perception, natural technical ability and sensing equipment etc..Simulated environment is by counting
The generation of calculation machine, real-time dynamic 3 D stereo photorealism.
Virtual reality fusion scene generation technique based on picture material is becoming virtual reality and the skill in augmented reality direction
Art development trend and cross-section study hot spot.In order to ensure that the image later stage can carry out the processing of actual situation shadow consistency, it is necessary to protect
The dummy object hatching effect that the dummy object added in the picture with image there is shade to match is demonstrate,proved, i.e., with identical projection
Direction and scene depth.
The function of traditional offer VR elements, the VR elements of drafting generally in the fixed position of image, fix by ways of presentation,
Cause addition VR elements cannot picture element corresponding with the real scene that mobile terminal is shot merge well, influence entirety
The authenticity of picture.
Three-dimensionalreconstruction and fusion are carried out to the dummy object in merging image, first have to obtain three of real world object in image
Image information is tieed up, 3-D graphic information includes the colour information and depth information of object.Existing 3 Dimension Image Technique mainly leads to
Colour information and depth information that sensor obtains object are crossed, colour information and depth information are merged, obtain graphics
As information.
Invention content
The present invention provides a kind of three dimensional image processing method, and this method is analyzed existing in image by acquiring image information
The three-dimensional informations such as the direction of real object shadow and scene depth；And it according to above- mentioned information, when being put into dummy object in the picture, fits
Answering property adjusts the size and three-dimensional information of dummy object.
To achieve these goals, the present invention provides a kind of three dimensional image processing method, and this method specifically includes following step
Suddenly：
S1. web camera remote collection image information is sent to image processing server；
S2. all real world object three-dimensional features in image processing server identification image；
S3. it is placed in dummy object in the picture；
S4. according to the three-dimensional feature of dummy object periphery real world object, be adaptively adjusted the size of dummy object with
And three-dimensional information.
Preferably, the three-dimensional information feature includes three-dimensional depth information and projecting direction.
Preferably, in the step S2, including S21：By the phase for calculating adjacent pixel in each real world object in image
Like degree, and then the depth of the pixel is obtained, obtain the three-dimensional depth information of real world object.
Preferably, the similarity for calculating adjacent pixel in each real world object in image, is propagated using adjacent pixel
It is similar with iterative calculation adjacent pixel including horizontal pixel is initialized as random planar with the multi-cycle algorithm of random optimization
The step of spending.
Preferably, it is described that horizontal pixel is initialized as random planar, including step：
S211. horizontal pixel is initialized as random planar；
S212. the initial depth of each pixel is set as random value, is set by the normal to a surface vector of each pixel
It is set to random unitary vector.
Preferably, it is described that horizontal pixel is initialized as random planar, including following process：
By the plane of the depth coordinate of the horizontal pixel, represented by formula (1),
Z=f1▽px+f2▽py+f3 (1)
Wherein, z is the depth coordinate and p of the horizontal pixelxAnd pyFor random planar, f1、f2And f3Respectively such as formula (2-
1), formula (2-2) and formula (2-3) are shown,
f1=-n1/n3 (2-1)
f2=-n2/n3 (2-2)
f3=(n1·x0+n2·y0+n3·z0)/n3 (2-3)
In formula (2-1), formula (2-2) and formula (2-3), n1、n2And n3It is scalar, is as the numerical value vector as shown in formula (3)
Plane, x are possible to where the minimum polymerization cost of expression0And y0The coordinate values of the horizontal pixel respectively initialized,
z0The initial depth value of the horizontal pixel for initialization,
M is provided by formula (4) in formula (3),
In formula (4), w be used to implement it is adaptive weighted, w by formula (5) provide；E represents Similarity measures factor, and E is by formula
(10) it provides；▽ represents Grad, WpExpression concentrates on a square window of p,
In formula (5), | | Ip-Iq| | represent the distance between two adjacent pixel ps and q, p is horizontal pixel, and q is same flat with p
Adjacent pixel in face,
E=α | | Ii-Ij||+(1-α)||▽Ii-▽Ij|| (6)
In formula (6), I is the intensity of pixel in real world object, and subscript i, j are the indexes of real world object, Ii, IjIt represents respectively
I-th, the intensity of the respective pixel in j-th of real world object, IiAnd IjIt is projected onto identical spatial point, IiAnd IjCoordinate by
Formula (11) is calculated, | | Ii-Ij| | for the I in rgb spaceiAnd IjColor manhatton distance, ▽ IiWith ▽ IjIt is pixel
Gray value gradient, | | ▽ Ii-▽Ij| | it represents in IiAnd IjThe absolute difference of the shade of gray of calculating, α are the weights of no unit
The factor, for balancing the influence of color and gradual change item；
In formula (7), uiIt is the local coordinate for the pixel for corresponding to the point that coordinate is y and z in each real world object.
Preferably, the similarity of the iterative calculation adjacent pixel, including step：
S213. it initializes a horizontal pixel in a random planar and calculates its depth coordinate and vector value, calculate
It polymerize cost, using this polymerization cost as with reference to polymerization cost；
S214. calculate any one adjacent pixel with horizontal pixel in step S213. in the same plane polymerize cost；
S215. it polymerize cost with adjacent pixel in step S214. with reference to polymerization cost in comparison step S213.；
S216. using polymerization cost respective pixel smaller in step S215. as new reference value；
S217., reference value respective pixel new in step S216. is set as to the respective pixel upper left with the comparison reference value
It is adjacent；
S218. it imposes a condition：New reference value corresponds to depth value in the permitted maximum range in step S216.；
S219. it if step S218. conditions are set up, recycles and performs step S213. to step S218.；
S220. step S218. conditions are invalid, using in last time circulation step S217. as image Far Left pixel；
S221. on the basis of step S220, image bottom right carries out declining even iteration；
S222. the calculation times of each pixel are calculated according to the iterations of step S221..
Preferably, the S2 further includes step S22：Analysis obtains the direction of real world object shadow：
S221., real world object in image is divided into the texture region of N number of same size, wherein, N >=2；
S222. the target view frustums using eye position as viewpoint are generated；
S223 by the target view frustums by closely to being far divided into N number of sub- view frustums, wherein, the region of every sub- view frustums
By closely to being far sequentially increased；
S224. the rendering parameter of the sub- view frustums is generated, the rendering parameter includes viewing matrix and projection matrix；
S225. according to the rendering parameter of the sub- view frustums, the sub- view frustums are rendered in a texture region
Real world object in corresponding image obtains the real world object shadow direction using light source position as viewpoint.
Preferably, following steps are further included in the step S4：
S41. the projecting direction analyzed according to S22 determines the light-receiving surface and shady face of dummy object；
S42. the lighting color of gradual change is configured in the transitional region for the light-receiving surface and the shady face；
S43. the lighting color received according to each pixel of the light-receiving surface, determines each pixel of light-receiving surface respectively
The color of point；
S44. the lighting color received according to each pixel of the shady face, determines each pixel of shady face respectively
The color of point.
Preferably, the lighting color of gradual change is configured in the transitional region for the light-receiving surface and the shady face, including：
Out of dot product value range [- 1,1], choose an interval [- x1, x2], wherein, x1 and x2 be positive number and
Less than 1；
A transitional region is selected from the dummy object surface, wherein, each pixel corresponds in the transitional region
Dot product in the interval [- x1, x2]；
Make the second lighting color gradual change that the first lighting color that the transitional region side receives is received to opposite side,
In, fixed-illumination color of first lighting color for the light-receiving surface reception in addition to the transitional region, second light
The fixed-illumination color received according to color for the shady face in addition to the transitional region.
Preferably, the lighting color received according to each pixel of the light-receiving surface, determines the light-receiving surface respectively
The color of each pixel, including：
Determine the corresponding shadow factor of each light receiving pixel point in the light-receiving surface, wherein, the size of the shadow factor
It is related to the shade shield coverage suffered by the light receiving pixel point；
According to texture color of the light receiving pixel point itself, the lighting color received, environment intrinsic colour, the shade
The factor determines the color of the light receiving pixel point.
Preferably, it is described to determine the corresponding shadow factor of each light receiving pixel point in the light-receiving surface, including：
The M reference image vegetarian refreshments that the light receiving pixel selects periphery is chosen, wherein, M >=2；
Depth information of scene is obtained using the step S2, determines that the light receiving pixel is selected and whether is the reference image vegetarian refreshments
In shade；
If not in shade, the shadow factor value of the light receiving pixel point is 0；If there are m pixel in the moon
In shadow, then the corresponding default shading value of each pixel in the m pixel determines the moon of the light receiving pixel point
Shadow factor value, wherein, 0<m≤M+1.
Preferably, in step sl, the data transmission of web camera and image processing server is led to using instant encryption
Letter, before instant encryption communication, web camera generates session key WK temporarily；Image processing server obtains web camera
Then identity public key and the basic public key of key agreement form public private key pair with image processing server and roll generation to negotiate to calculate father
Table initial key N_CC, detailed process are as follows：
By T_SKA/T_PKA, NB_SKB/NB_PKB, by scalar multiplication algorithm on elliptic curve, the key of web camera is calculated
Negotiate first part Part1；
Web camera key agreement first part Part1=DPSM2(TSKA, NBPKB)；
By NB_SKA/NB_PKA, T_SKB/T_PKB, by scalar multiplication algorithm on elliptic curve, the key of web camera is calculated
Negotiate second part Part2；
Web camera key agreement second part Part2=DPSM2(NBSKA, TPKB)；
By NB_SKA/NB_PKA, NB_SKB/NB_PKB, by scalar multiplication algorithm on elliptic curve, calculate web camera and calculate hair
The key agreement Part III Part3 for the side of sending；
Web camera key agreement Part III Part3=DPSM2(NBSKA, NBPKB)；
By web camera key agreement first part Part1, web camera key agreement second part Part2, net
Network video camera key agreement Part III Part3 connects into web camera key components KM；
Web camera key components KM=Part1 | | Part2 | | Part3)；
By web camera key components KM and the first character string with SM3 compression algorithms into the web camera of 256bit
Father rolls and represents initial key N_CC；
Initial key N_CC=HSM3 (KM | | the first character string)
According to scalar multiplication algorithm on elliptic curve feature, by the calculating process, web camera key and image processing services
Device both sides calculate consistent father's rolling and represent initial key N_CC.
The present invention has the following advantages and beneficial effect：(1) present invention analyzes to obtain three using the real world object in image
Dimensional feature, the fusion of the dummy object for merging, which provides to be adaptively adjusted, provides accurate three-dimensional coefficient；(2) the application carries
The new calculation method of real world images three dimensional depth extraction is gone out, this method calculates the similarity of pixel in each real world object, examines
The continuity on surface is considered, to improve resolution ratio, it is excessively multiple to solve algorithm in current depth of 3 D picture information extraction process
The problem of miscellaneous；(3) present invention proposes the projecting direction that real world object in image is obtained using sub- view frustums, quick and saving money
Source；(4) image data communication of the present invention carries out data exchange using instantaneous safety communication mode, it is ensured that the peace of data transmission
Quan Xing prevents information leakage.
Description of the drawings
Fig. 1 shows the graphic system block diagram that a kind of three dimensional image processing method of the present invention is based on；
Fig. 2 shows a kind of flow charts of three dimensional image processing method of the present invention；
Fig. 3 shows that a kind of analysis of the present invention obtains the flow chart of the three-dimensional feature of real world object in image；
Fig. 4 shows that a kind of analysis of the present invention obtains the flow chart of real world object projecting direction；
Fig. 5 shows a kind of flow chart of generation dummy object of the present invention.
Specific embodiment
Innovative point for a better understanding of the present invention below in conjunction with the accompanying drawings, is explained the specific implementation method of the present invention
It states.
Fig. 1 shows the graphic system block diagram that a kind of three dimensional image processing method of the present invention is based on, the system
Including web camera 1, for acquiring the image information of reality, and it is transmitted through the network to image processing server 2.The figure
As server 2 includes：For storing the image storage module 21 of the image of video camera transmission, for analyzing real world images in image
Depth information three dimensional depth analysis module 22, for analyzing the projecting direction analysis module of the projecting direction in image
23, according to for being placed in the dummy object generation module 24 of dummy object in the picture, to real world object in image and virtual object
The image co-registration module 25 and the image output module 26 to the display output image of equipment 3 that body is merged.
Fig. 2 shows a kind of flow charts for the three dimensional image processing method for utilizing the present invention.A kind of 3-D view processing side
Method, this method specifically comprise the following steps：
S1. web camera remote collection image information is sent to image processing server；
S2. all real world object three-dimensional features in image processing server identification image；Preferably, the three-dimensional information is special
Sign includes three-dimensional depth information and projecting direction.
S3. it is placed in dummy object in the picture；
S4. according to the three-dimensional feature of dummy object periphery real world object, be adaptively adjusted the size of dummy object with
And three-dimensional information.
Referring to Fig. 3, in the step S2, including S21：By the phase for calculating adjacent pixel in each real world object in image
Like degree, and then the depth of the pixel is obtained, obtain the three-dimensional depth information of real world object.
Preferably, the similarity for calculating adjacent pixel in each real world object in image, is propagated using adjacent pixel
With the multi-cycle algorithm of random optimization.
Preferably, including horizontal pixel is initialized as random planar and the step of similarity for iterating to calculate adjacent pixel
Suddenly.
It is described that horizontal pixel is initialized as random planar, including step：
S211. horizontal pixel is initialized as random planar；
S212. the initial depth of each pixel is set as random value, is set by the normal to a surface vector of each pixel
It is set to random unitary vector.
It is further preferred that described be initialized as random planar by horizontal pixel, including following process：
By the plane of the depth coordinate of the horizontal pixel, represented by formula (1),
Z=f1▽px+f2▽py+f3 (1)
Wherein, z is the depth coordinate and p of the horizontal pixelxAnd pyFor random planar, f1、f2And f3Respectively such as formula (2-
1), formula (2-2) and formula (2-3) are shown,
f1=-n1/n3 (2-1)
f2=-n2/n3 (2-2)
f3=(n1·x0+n2·y0+n3·z0)/n3 (2-3)
In formula (2-1), formula (2-2) and formula (2-3), n1、n2And n3It is scalar, is as the numerical value vector as shown in formula (3)
Plane, x are possible to where the minimum polymerization cost of expression0And y0The coordinate values of the horizontal pixel respectively initialized,
z0The initial depth value of the horizontal pixel for initialization,
M is provided by formula (4) in formula (3),
In formula (4), w be used to implement it is adaptive weighted, w by formula (5) provide；E represents Similarity measures factor, and E is by formula
(10) it provides；▽ represents Grad, WpExpression concentrates on a square window of p,
In formula (5), | | Ip-Iq| | represent the distance between two adjacent pixel ps and q, p is horizontal pixel, and q is same flat with p
Adjacent pixel in face,
E=α | | Ii-Ij||+(1-α)||▽Ii-▽Ij|| (6)
In formula (6), I is the intensity of pixel in real world object, and subscript i, j are the indexes of real world object, Ii, IjIt represents respectively
I-th, the intensity of the respective pixel in j-th of real world object, IiAnd IjIt is projected onto identical spatial point, IiAnd IjCoordinate by
Formula (11) is calculated, | | Ii-Ij| | for the I in rgb spaceiAnd IjColor manhatton distance, ▽ IiWith ▽ IjIt is pixel
Gray value gradient, | | ▽ Ii-▽Ij| | it represents in IiAnd IjThe absolute difference of the shade of gray of calculating, α are the weights of no unit
The factor, for balancing the influence of color and gradual change item；
In formula (7), uiIt is the local coordinate for the pixel for corresponding to the point that coordinate is y and z in each real world object.
Preferably, the similarity of the iterative calculation adjacent pixel, including step：
S213. it initializes a horizontal pixel in a random planar and calculates its depth coordinate and vector value, calculate
It polymerize cost, using this polymerization cost as with reference to polymerization cost；
S214. calculate any one adjacent pixel with horizontal pixel in step S213. in the same plane polymerize cost；
S215. it polymerize cost with adjacent pixel in step S214. with reference to polymerization cost in comparison step S213.；
S216. using polymerization cost respective pixel smaller in step S215. as new reference value；
S217., reference value respective pixel new in step S216. is set as to the respective pixel upper left with the comparison reference value
It is adjacent；
S218. it imposes a condition：New reference value corresponds to depth value in the permitted maximum range in step S216.；
S219. it if step S218. conditions are set up, recycles and performs step S213. to step S218.；
S220. step S218. conditions are invalid, using in last time circulation step S217. as image Far Left pixel；
S221. on the basis of step S220, image bottom right carries out declining even iteration；
S222. the calculation times of each pixel are calculated according to the iterations of step S221..
The similarity of the iterative calculation adjacent pixel, including spatial and the step of plane refine；
In the step of spatial, neighbor pixel is set as in the same plane, first by formula (4) assessment not
With the cost m of situation,
In formula (4), p represents current pixel, fpIt is the vector of its corresponding plane, q is the adjacent pixel of p, in p (x0, y0)
It is lower to use f respectivelypAnd fqIt calculates, to assess the cost of both of these case；Shown in inspection condition such as formula (8),
m(x0, y0, fp')<m(x0, y0, fp)； (8)
In formula (8) and obtained respectively by formula (4)；
If the expression formula shown in formula (8) is set up, fqIt is accepted as the new vector of p, i.e. fp=fq；
In odd number iteration, q is the left side and coboundary；
In even number iteration, q is right margin and lower boundary；
In the step of plane refine, by fpBe converted to normal vector np, two parameter ▽ z and ▽ n are defined as limiting respectively
Z processed0With the maximum allowable variation of n, z0' it is calculated as z0'=z0+ ▽ z, wherein ▽ z are located at [- ▽ zmax, ▽ zmax], and n'=u
(n+ ▽ n), u () represent unit of account vector, and ▽ n are located at [- ▽ nmax, ▽ nmax]；
Finally, a new f is obtained by p and n'p', if m (x0, y0, fp')<m(x0, y0, fp), then fp=fp'；
In the step of plane refine, from setting ▽ zmax=maxdisp/2 starts, and wherein maxdisp is allowed most
Big parallax, ▽ nmax=1, every time after refinement, parameter will be updated to ▽ zmax=▽ zmax/2、▽nmax=▽ nmax/2；Until ▽
zmax<Resolution/2, the resolution ratio minimized；For odd number iteration, since on the left of image, carried out to bottom right
Even number iteration；
The similarity of adjacent pixel is obtained after iteration, and then obtains the depth of the real world object.
Referring to Fig. 4, the S2 further includes step S22：Analysis obtains the direction of real world object shadow：
S221., real world object in image is divided into the texture region of N number of same size, wherein, N >=2；
S222. the target view frustums using eye position as viewpoint are generated；
S223 by the target view frustums by closely to being far divided into N number of sub- view frustums, wherein, the region of every sub- view frustums
By closely to being far sequentially increased；
S224. the rendering parameter of the sub- view frustums is generated, the rendering parameter includes viewing matrix and projection matrix；
S225. according to the rendering parameter of the sub- view frustums, the sub- view frustums are rendered in a texture region
Real world object in corresponding image obtains the real world object shadow direction using light source position as viewpoint.
Referring to Fig. 5, following steps are further included in the step S4：
S41. the projecting direction analyzed according to S22 determines the light-receiving surface and shady face of dummy object；
S42. the lighting color of gradual change is configured in the transitional region for the light-receiving surface and the shady face；
S43. the lighting color received according to each pixel of the light-receiving surface, determines each pixel of light-receiving surface respectively
The color of point；
S44. the lighting color received according to each pixel of the shady face, determines each pixel of shady face respectively
The color of point.
Preferably, the lighting color of gradual change is configured in the transitional region for the light-receiving surface and the shady face, including：
Out of dot product value range [- 1,1], choose an interval [- x1, x2], wherein, x1 and x2 be positive number and
Less than 1；
A transitional region is selected from the dummy object surface, wherein, each pixel corresponds in the transitional region
Dot product in the interval [- x1, x2]；
Make the second lighting color gradual change that the first lighting color that the transitional region side receives is received to opposite side,
In, fixed-illumination color of first lighting color for the light-receiving surface reception in addition to the transitional region, second light
The fixed-illumination color received according to color for the shady face in addition to the transitional region.
Preferably, the lighting color received according to each pixel of the light-receiving surface, determines the light-receiving surface respectively
The color of each pixel, including：
Determine the corresponding shadow factor of each light receiving pixel point in the light-receiving surface, wherein, the size of the shadow factor
It is related to the shade shield coverage suffered by the light receiving pixel point；
According to texture color of the light receiving pixel point itself, the lighting color received, environment intrinsic colour, the shade
The factor determines the color of the light receiving pixel point.
Preferably, it is described to determine the corresponding shadow factor of each light receiving pixel point in the light-receiving surface, including：
The M reference image vegetarian refreshments that the light receiving pixel selects periphery is chosen, wherein, M >=2；
Depth information of scene is obtained using the step S2, determines that the light receiving pixel is selected and whether is the reference image vegetarian refreshments
In shade；
If not in shade, the shadow factor value of the light receiving pixel point is 0；If there are m pixel in the moon
In shadow, then the corresponding default shading value of each pixel in the m pixel determines the moon of the light receiving pixel point
Shadow factor value, wherein, 0<m≤M+1.
Preferably, in step sl, the data transmission of web camera and image processing server is led to using instant encryption
Letter, before instant encryption communication, web camera generates session key WK temporarily；Image processing server obtains web camera
Then identity public key and the basic public key of key agreement form public private key pair with image processing server and roll generation to negotiate to calculate father
Table initial key N_CC, detailed process are as follows：
By T_SKA/T_PKA, NB_SKB/NB_PKB, by scalar multiplication algorithm on elliptic curve, the key of web camera is calculated
Negotiate first part Part1；
Web camera key agreement first part Part1=DPSM2(TSKA, NBPKB)；
By NB_SKA/NB_PKA, T_SKB/T_PKB, by scalar multiplication algorithm on elliptic curve, the key of web camera is calculated
Negotiate second part Part2；
Web camera key agreement second part Part2=DPSM2(NBSKA, TPKB)；
By NB_SKA/NB_PKA, NB_SKB/NB_PKB, by scalar multiplication algorithm on elliptic curve, calculate web camera and calculate hair
The key agreement Part III Part3 for the side of sending；
Web camera key agreement Part III Part3=DPSM2(NBSKA, NBPKB)；
By web camera key agreement first part Part1, web camera key agreement second part Part2, net
Network video camera key agreement Part III Part3 connects into web camera key components KM；
Web camera key components KM=Part1 | | Part2 | | Part3)；
By web camera key components KM and the first character string with SM3 compression algorithms into the web camera of 256bit
Father rolls and represents initial key N_CC；
Initial key N_CC=HSM3 (KM | | the first character string)
According to scalar multiplication algorithm on elliptic curve feature, by the calculating process, web camera key and image processing services
Device both sides calculate consistent father's rolling and represent initial key N_CC.
Those of ordinary skill in the art may realize that each exemplary lists described with reference to the embodiments described herein
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is performed with hardware or software mode, specific application and design constraint depending on technical solution.Professional technician
Described function can be realized using distinct methods to each specific application, but this realization is it is not considered that exceed
The scope of the present invention.
Although it as described above, is illustrated according to the embodiment and attached drawing that embodiment is limited, to the art
It can carry out various modifications and deform from above-mentioned record for technical staff with general knowledge.For example, according to explanation
Technology illustrated in the mutually different sequence of method carry out and/or according to system, structure, device, circuit with explanation etc.
The mutually different form of method illustrated by inscape is combined or combines or carried out according to other inscapes or equipollent
It replaces or displacement also may achieve appropriate effect.For those of ordinary skill in the art to which the present invention belongs, it is not taking off
Under the premise of from present inventive concept, several equivalent substitute or obvious modifications are made, and performance or use is identical, should be all considered as
It belongs to the scope of protection of the present invention.
Claims (10)
1. a kind of three dimensional image processing method, this method specifically comprise the following steps：
S1. web camera remote collection image information is sent to image processing server；
S2. all real world object three-dimensional features in image processing server identification image；
S3. it is placed in dummy object in the picture；
S4. according to the three-dimensional feature of dummy object periphery real world object, the size and three of dummy object is adaptively adjusted
Tie up information.
2. the method as described in claim 1, which is characterized in that the three-dimensional information feature includes three-dimensional depth information and projection
Direction.
3. method as claimed in claim 2, which is characterized in that in the step S2, including S21：It is every in image by calculating
The similarity of adjacent pixel in a real world object, and then the depth of the pixel is obtained, obtain the three dimensional depth letter of real world object
Breath.
4. method as claimed in claim 3, which is characterized in that adjacent pixel in each real world object in the calculating image
Similarity propagates the multi-cycle algorithm with random optimization, including horizontal pixel is initialized as random planar using adjacent pixel
With iterative calculation adjacent pixel similarity the step of.
5. method as claimed in claim 4, which is characterized in that it is described that horizontal pixel is initialized as random planar, including step
Suddenly：
S211. horizontal pixel is initialized as random planar；
S212. the initial depth of each pixel is set as random value, is arranged to by the normal to a surface vector of each pixel
Random unitary vector.
6. method as claimed in claim 5, which is characterized in that it is described that horizontal pixel is initialized as random planar, including such as
Lower process：
By the plane of the depth coordinate of the horizontal pixel, represented by formula (1),
Wherein, z is the depth coordinate and p of the horizontal pixelxAnd pyFor random planar, f1、f2And f3Respectively such as formula (2-1), formula
Shown in (2-2) and formula (2-3),
f1=-n1/n3 (2-1)
f2=-n2/n3 (2-2)
f3=(n1·x0+n2·y0+n3·z0)/n3 (2-3)
In formula (2-1), formula (2-2) and formula (2-3), n1、n2And n3It is scalar, is as the numerical value vector as shown in formula (3)It represents
Plane, x are possible to where minimum polymerization cost0And y0The coordinate values of the horizontal pixel respectively initialized, z0For
The initial depth value of the horizontal pixel of initialization,
M is provided by formula (4) in formula (3),
In formula (4), w be used to implement it is adaptive weighted, w by formula (5) provide；E represents Similarity measures factor, and E is carried by formula (10)
For；Represent Grad, WpExpression concentrates on a square window of p,
In formula (5), | | Ip-Iq| | represent the distance between two adjacent pixel ps and q, p is horizontal pixel, q be with p in the same plane
Adjacent pixel,
In formula (6), I is the intensity of pixel in real world object, and subscript i, j are the indexes of real world object, Ii, IjI-th is represented respectively,
The intensity of respective pixel in j-th of real world object, IiAnd IjIt is projected onto identical spatial point, IiAnd IjCoordinate by formula
(11) it is calculated, | | Ii-Ij| | for the I in rgb spaceiAnd IjColor manhatton distance,WithIt is the ash of pixel
Angle value gradient,It represents in IiAnd IjThe absolute difference of the shade of gray of calculating, α are the weight factors of no unit,
For balancing the influence of color and gradual change item；
In formula (7), uiIt is the local coordinate for the pixel for corresponding to the point that coordinate is y and z in each real world object.
7. method as claimed in claim 6, which is characterized in that the similarity of the iterative calculation adjacent pixel, including step：
S213. it initializes a horizontal pixel in a random planar and calculates its depth coordinate and vector value, it is poly- to calculate it
Synthesis originally, using this polymerization cost as reference polymerize cost；
S214. calculate any one adjacent pixel with horizontal pixel in step S213. in the same plane polymerize cost；
S215. it polymerize cost with adjacent pixel in step S214. with reference to polymerization cost in comparison step S213.；
S216. using polymerization cost respective pixel smaller in step S215. as new reference value；
S217. reference value respective pixel new in step S216. is set as adjacent with the respective pixel upper left of the comparison reference value；
S218. it imposes a condition：New reference value corresponds to depth value in the permitted maximum range in step S216.；
S219. it if step S218. conditions are set up, recycles and performs step S213. to step S218.；
S220. step S218. conditions are invalid, using in last time circulation step S217. as image Far Left pixel；
S221. on the basis of step S220, image bottom right carries out declining even iteration；
S222. the calculation times of each pixel are calculated according to the iterations of step S221..
8. the method as described in claim 2-7 is any, which is characterized in that the S2 further includes step S22：Analysis obtains reality
The direction of shadows of objects：
S221., real world object in image is divided into the texture region of N number of same size, wherein, N >=2；
S222. the target view frustums using eye position as viewpoint are generated；
S223 by the target view frustums by closely to being far divided into N number of sub- view frustums, wherein, the region of every sub- view frustums is by near
To being far sequentially increased；
S224. the rendering parameter of the sub- view frustums is generated, the rendering parameter includes viewing matrix and projection matrix；
S225. according to the rendering parameter of the sub- view frustums, the sub- view frustums is rendered in a texture region and are corresponded to
Image in real world object, obtain the real world object shadow direction using light source position as viewpoint.
9. method as claimed in claim 8, which is characterized in that, further include following steps in the step S4：
S41. the projecting direction analyzed according to S22 determines the light-receiving surface and shady face of dummy object；
S42. the lighting color of gradual change is configured in the transitional region for the light-receiving surface and the shady face；
S43. the lighting color received according to each pixel of the light-receiving surface, determines each pixel of light-receiving surface respectively
Color；
S44. the lighting color received according to each pixel of the shady face, determines each pixel of shady face respectively
Color；
The lighting color of gradual change is configured in the transitional region for the light-receiving surface and the shady face, including：
In from dot product value range [- 1,1], an interval [- x1, x2] is chosen, wherein, x1 and x2 are positive number and are less than
1；
A transitional region is selected from the dummy object surface, wherein, the corresponding point of each pixel in the transitional region
Product is in the interval [- x1, x2]；
Make the second lighting color gradual change that the first lighting color that the transitional region side receives is received to opposite side, wherein,
The fixed-illumination color that first lighting color is received for the light-receiving surface in addition to the transitional region, the second illumination face
The fixed-illumination color that color is received for the shady face in addition to the transitional region.
10. the method as described in claim 1, which is characterized in that in step sl, web camera and image processing server
Data transmission using instant encryption communicate, instant encryption communication before, web camera generates session key WK temporarily；At image
It manages server and obtains the identity public key of web camera and the basic public key of key agreement, then formed with image processing server public
For private key to representing initial key N_CC to negotiate to calculate father's rolling, detailed process is as follows：
By T_SKA/T_PKA, NB_SKB/NB_PKB, by scalar multiplication algorithm on elliptic curve, the key agreement of web camera is calculated
First part Part1；
Web camera key agreement first part Part1=DPSM2(TSKA, NBPKB)；
By NB_SKA/NB_PKA, T_SKB/T_PKB, by scalar multiplication algorithm on elliptic curve, the key agreement of web camera is calculated
Second part Part2；
Web camera key agreement second part Part2=DPSM2(NBSKA, TPKB)；
By NB_SKA/NB_PKA, NB_SKB/NB_PKB, by scalar multiplication algorithm on elliptic curve, calculate web camera and calculate sender
Key agreement Part III Part3；
Web camera key agreement Part III Part3=DPSM2(NBSKA, NBPKB)；
Web camera key agreement first part Part1, web camera key agreement second part Part2, network are taken the photograph
Camera key agreement Part III Part3 connects into web camera key components KM；
Web camera key components KM=Part1 | | Part2 | | Part3)；
Web camera key components KM and the first character string are rolled with the father of SM3 compression algorithms into the web camera of 256bit
It is dynamic to represent initial key N_CC；
Initial key N_CC=HSM3 (KM | | the first character string)
According to scalar multiplication algorithm on elliptic curve feature, by the calculating process, web camera key and image processing server are double
Side calculates consistent father's rolling and represents initial key N_CC.
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