CN101533521A - A method for reconstructing three-dimensional surface model - Google Patents

Abstract

The invention relates to a method for reconstructing three-dimensional surface model, in particular to a method for reconstructing three-dimensional surface model of a translucent object and a mirror object. The method comprises the steps of obtaining the three-dimensional stereo positions of the objects and multiple reflection parameters corresponding to the objects with a three-dimensional optical system; and then, constructing a synthetic image according to the three-dimensional stereo positions and the multiple reflection parameters; and finally, adjusting the multiple reflection parameters so as to adjust the synthetic image until the optimal parameters are smaller than a default value. The invention provides a surface optimal algorithm. The reflection characteristics of a real object can be obtained in the process of reconstructing the real object and optimising the surface.

Description

The method of reconstructing three-dimensional surface model

Technical field

The present invention relates to a kind of method of reconstructing three-dimensional surface model, particularly a kind of method for reconstructing of the 3 d surface model about translucent object and mirror object.

Background technology

In recent years, because the development of stereotelevision and computer animation, 3-D scanning reconstruction model technology has been widely applied in computerized mapping (computer graphic) or the computer vision fields such as (computer vision).3-D scanning reconstruction model technology can divide work following several classes haply: passive type stereo reconstruction (passive stereo), active stereo reconstruction (active stereo), shadow reconstructed surface (shape from shading) are rebuild (photometric stereo) with photometric stereo.

Wherein, passive type stereo reconstruction method be by intersect comparison a plurality of from different visual angles the entity image and utilize triangle to calculate the three-dimensional surface of entity for how much.The main benefit of passive type stereo reconstruction method is to carry out easily and only needs two or many s' camera to finish, but at the less place of texture (texture), its image corresponding point (correspond points) comparison is difficult for, and is lower in this partial correctness.

Active stereo reconstruction rule is to utilize the extra light source or the laser projector (laser projector) that the object of wanting the reconstruction of three-dimensional image is scanned, compared to the three-dimensional appearance method of passive type, active stereo reconstruction method is easier to for the calculating of corresponding point in the image, and the correctness of its image is also higher.But change an angle, the system of active stereo reconstruction method needs extra grenade instrumentation usually, so weight is big and cost is expensive.In addition, because the trickle part of 3-dimensional image of non-Lambert surface (non-lambertian surface) object that passive type or active stereo reconstruction method are calculated out, trickle part compared to the actual image of object is comparatively rough, and also reflection characteristic is not taken into account the influence of image in the process of calculating, therefore the 3 D stereoscopic image of non-Lambert surface object is can't calculate by passive type or active stereo reconstruction method.

Above-mentioned so-called Lambert surface (lambertian surface) can be learnt its meaning by following character.When Lambert surface and surface normal fixedly the time, all be to present identical briliancy in all observed rays, i.e. the constant that briliancy is and observed ray is irrelevant.But in fact, most in the world object is except lambert (lambertian) reflection characteristic, and the part mirror of also having reflection (specularreflection) or subsurface reflect (subsurface scattering) characteristic.

Shadow reconstructed surface method and photometric stereo reconstruction method are to utilize reflected by objects brightness delta data to rebuild the 3-dimensional image shape of object.The photometric stereo reconstruction method is normally at a plurality of direction irradiations, observe the variation of object reflecting brightness from the viewing angle of single direction, and its calculation process is mostly used Lambert's model (lambertian model), just object is assumed to be the Lambert surface object, so the mode that estimates of normal vector (normal) just becomes simple linear least-squares problem (linear least-squareproblem).But because actual object is not all only to have lambertian reflection characteristics (lambertian reflection properties), so traditional photometric stereo reconstruction method has than mistake for the object of mirror material.Shadow reconstructed surface rule is to utilize the Strength Changes of single image and known irradiation condition to come the reconstruction of three-dimensional three-dimensional surface.Yet can cause the image of reconstruction to have disturbed situation because input is disturbed or the influence of the reflection model of simplifying by degree of depth image (range image) shape that shadow reconstructed surface method is rebuild.

Therefore, known three-dimensional reconstruction modelling technique is subject to the geological information that scanning system can't provide the object fine portion, make object the three-dimensional geometry image resolution also be restricted.In addition, it is the translucent material that multiple layered struture is formed that known techniques also can't be handled the object or the composition of object itself with specular reflectance characteristics (specular reflection), just has the object of subsurface reflection (sub-surface scattering) characteristic.

Summary of the invention

The objective of the invention is to overcome the deficiencies in the prior art, a kind of method of reconstructing three-dimensional surface model is provided, this method can be rebuild the 3 d surface model of the object with part mirror material or the translucent material characteristic of part.

In addition, the present invention also provides a kind of method of reconstructing three-dimensional surface model parameter, and this method can merge mirror material part or the translucent material part of considering object, and then synthesizes the resultant image with specular reflectance characteristics and subsurface reflection characteristic.

For achieving the above object, the present invention proposes a kind of method of reconstructing three-dimensional surface model, its step comprises:

(1) the 3 D stereo position of obtaining object with the three-dimensional structure photosystem and a plurality of reflection parameters corresponding to described object;

(2) set up resultant image according to described 3 D stereo position and described a plurality of reflection parameters;

(3) adjust reflection parameters to adjust described resultant image, up to the optimization parameter less than default value.

Wherein, described optimization parameter is corresponding to the difference of the brightness of a plurality of pixels in the brightness (intensity) of a plurality of pixels of correspondence position in the adjusted described resultant image and the actual image.

In an embodiment of the present invention, above-mentioned optimization parameter comprises one first and one second, described first corresponding to the difference of the brightness of the brightness of the pixel in the described resultant image and the respective pixel in the actual image square, the difference of described second estimating depth (depth) and the degree of depth of corresponding a plurality of surrounding pixels corresponding to each pixel in the described resultant image.

In an embodiment of the present invention, the equation of above-mentioned optimization parameter is expressed as follows:

$C\left(Z\right)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}[{(S^i-R^i)}^2+w\underset{j=1}{\overset{m}{\mathrm{\Σ}}}{(r_j-z_i)}^2]$

Wherein, the described optimization parameter of C (Z) expression; S ⁱRepresent the brightness of the pixel in the described resultant image; R ⁱRepresent the brightness of pixel in the described actual image; Z _iThe degree of depth of representing the pixel in the described resultant image; r _jExpression is corresponding to Z _iThe degree of depth of pixel of surrounding pixel; N represents the sum of all pixels in the described resultant image; M represents the sum of a plurality of surrounding pixels; I represents the index value of the pixel in the described resultant image; J represents the index value of described a plurality of surrounding pixels; W is second weights (proportion) in the optimization parameter.

In an embodiment of the present invention, in step (1), more comprise and utilize Lambertian reflection model and shadow reconstructed surface technology to obtain the 3 D stereo position of object and the initial value of a plurality of reflection parameters.

In an embodiment of the present invention, above-mentioned reflection parameters comprise scattering coefficient and normal vector at least one of them.

In an embodiment of the present invention, in step (2), more comprise and utilize a mirror material model and described a plurality of reflection parameters to set up described resultant image.Wherein reflection parameters comprises scattering coefficient, mirror coefficient and gloss coefficient (shiness).

In an embodiment of the present invention, above-mentioned mirror material model is the Phong model, and its equation is expressed as:

S _i＝k _d*N _l·L+k _s*(F _i·V) ^α

Wherein, S _iBrightness for pixel; k _dBe scattering coefficient (diffuse coefficient); k _sBe mirror coefficient (specularcoefficient); N _iBe described some surface normal, can be by contiguous z _iSlope obtain; L is the incident light vector; F _iBe complete mirror reflection vector, can be by N _i, L obtains; V is the visual angle vector; α is gloss coefficient (shine coefficient).

In an embodiment of the present invention, in step (2), more comprise and utilize half transparent material model and described a plurality of reflection parameters to set up described resultant image.Wherein reflection parameters comprises dispersion coefficient, absorption coefficient and refractive index.

In an embodiment of the present invention, above-mentioned translucent material model is two-way Subsurface Scattering reflection distribution function model, and its equation is as follows:

$S_d(x_i,{\stackrel{\→}{\mathrm{\ω}}}_i,x_o,{\stackrel{\→}{\mathrm{\ω}}}_o)=\frac{1}{\mathrm{\π}}{F}_t(x_i,{\stackrel{\→}{\mathrm{\ω}}}_i)P_d\left({\left|\right|x_i-x_o\left|\right|}_2\right)F_t(x_o,{\stackrel{\→}{\mathrm{\ω}}}_o)$

Wherein, S _dBrightness for pixel; F _tBe the Fresnel transfer function; x _iEnter the incoming position of object for light; x _oThe refraction position of leaving object for light; Be incident angle;

Be refraction angle; P _dScattered quantum varied curve letter formula for object.

In an embodiment of the present invention, in step (3), more comprise according to adjusted resultant image and recomputate the optimization parameter to readjust reflection parameters.

In an embodiment of the present invention, the method for above-mentioned reconstructing three-dimensional surface model more comprises, adjusts the depth parameter (depth) of 3 D stereo position according to adjusted reflection parameters, up to the optimization parameter less than default value.

In an embodiment of the present invention, the method for above-mentioned reconstructing three-dimensional surface model more comprises, repeats to adjust reflection parameters and 3 D stereo position, up to the difference of resultant image and actual image less than default value.

The invention allows for the method for another kind of reconstructing three-dimensional surface model, may further comprise the steps:

(1) obtains the 3 D stereo position of object with the three-dimensional structure photosystem;

(2) according to 3 D stereo position and Phong modelling resultant image;

(3) adjust a plurality of first reflection parameters in the Phong model to adjust resultant image, up to the optimization parameter less than first default value;

(4) adjust depth parameter in the 3 D stereo position according to adjusted first reflection parameters, up to the optimization parameter less than second default value;

(5) adjust resultant image according to adjusted 3 D stereo position and two-way Subsurface Scattering reflection distribution function model;

(6) adjust second reflection parameters in the described two-way Subsurface Scattering reflection distribution function model to adjust resultant image, up to the optimization parameter less than the 3rd default value;

(7) adjust depth parameter in the 3 D stereo position according to adjusted second reflection parameters, up to the optimization parameter less than the 4th default value.

Wherein, the optimization parameter comprises first and second, wherein the difference of the brightness of the brightness of the pixel in first corresponding resultant image and the pixel in the actual image square, and second difference corresponding to the degree of depth of the degree of depth of each pixel in the resultant image and corresponding a plurality of surrounding pixels.All the other details of the method for above-mentioned another kind of reconstructing three-dimensional surface model do not repeat them here as above-mentioned.

The invention has the beneficial effects as follows and proposed new optimization equation, and utilize Phong model and BSSRDF model to carry out image reconstruction, consider the character of object scattering mirror and sub-surface scattering (sub-surface scattering) respectively, therefore the present invention does not need before scanning the object surfaces branch painted or uses in addition coverture surface of lime, do not need expensive instrument yet, and can obtain non-lambert (Non-lambertian) and the more correct geological information of sub-surface scatterer.

The present invention is described in further detail below in conjunction with drawings and the specific embodiments.

Description of drawings

Fig. 1 is the method flow diagram that the 3 d surface model of object is according to an embodiment of the invention rebuild.

Fig. 2 is the method flow diagram that the 3 d surface model of object is according to another embodiment of the present invention rebuild.

Embodiment

First embodiment

Fig. 1 is the method flow diagram of the reconstructing three-dimensional surface model of one embodiment of the invention.Please refer to Fig. 1, at first, utilize three-dimensional structure photosystem (structure light system) to obtain the initial 3 D stereo position of object, and obtain shadow information, camera position and the light position of object in real scene as described in the step S110.Then as described in the step S120, the technology and the Lambertian reflection model (lambertain reflectance model) that see through shadow reconstructed surface (shape from shading) are obtained the synthetic 3 D stereo position and the initial value of reflection parameters, and the above-mentioned reflection parameters that obtains can be the position of the picture element reflect parameter value preliminary with it (for example scattering coefficient and its surface normal), brightness (intensity) or image depth parameters such as (image depth).

Next the object material characteristic partly that then will synthesize according to the user decides and utilizes the model that is fit to come resultant image.For example among the step S130, the Phong material model that is utilized is applicable to as this object that has the mirror composition of silver plate, and above-mentioned Phong material model comprises lambert (lamertian model) and mirror model (specular).In addition, if translucent object (translucent materials), for example be rice, bread, marble and skin, then need to set up resultant image as the described translucent material model of step S140, following elder generation is example with tool mirror (specular) with scattering (diffuse) material model, narrates the process of setting up resultant image and image optimumization.Then can adopt wherein a kind of image model (as mirror material model) to carry out optimization earlier if mix the object of unlike material, and then utilize another kind of image model (as translucent material model) to carry out the optimization of local image.

As described in step 130, utilize mirror material model and reflection parameters to set up resultant image, in the present embodiment, we utilize the Phong model (about the Phong model, to please refer to B.T.Phong, Illumination for computer generated pictures, Communications of the ACM, v18, n8, p311-317,1975) mirror material model comes resultant image.The equation of Phong model is expressed as follows:

S _i＝k _d*N _l·L+k _s*(F _i·V) ^α

Wherein, S _iBrightness for picture element; k _dBe scattering coefficient (diffuse coefficient); k _sBe mirror coefficient (specularcoefficient); N _iBe described some surface normal, can be by contiguous z _iSlope obtain; z _iThe degree of depth of pixel in the expression resultant image; L is the incident light vector; F _iBe complete mirror reflection vector, can be by N _i, L obtains; V is the visual angle vector; α is gloss coefficient (shinenesscoefficient).

And scattering coefficient k _d, the mirror coefficient k _sBe the reflection parameters P of Phong Model with brightness α _M, therefore by scattering coefficient k _dWith the mirror coefficient k _sJust can clearly understand the Phong model is that a kind of scattering and mirror characteristic with object considered into non-lambert (non-lambertina) model that synthesizes 3-dimensional image, so synthetic 3-dimensional image that utilizes Phong Model to simulate out, the specular reflectance characteristics of the trickle part of its image can present, and therefore more can improve the true property of plan of synthetic 3-dimensional image.And by the image that the Phong model is synthesized, can be expressed as:

$T^i=<p_x^i,p_y^i,S^i>$

S wherein ⁱBe the brightness of the pixel of resultant image, S ⁱValue can be relevant to the reflection parameters P of reflection model _M, just be relevant to scattering coefficient k _d, the mirror coefficient k _sWith brightness α, x, y represent level and vertical coordinate, can be used to indicate the location of pixels in the image, and i represents the index value of picture element.

After obtaining resultant image, suppose that actual image is O ⁱ, it can be expressed as:

$O^i=<p_x^i,p_x^i,R^i>$

R wherein ⁱBrightness for the pixel of actual image.Then just can define optimization parameters C (Z), the equation of optimization parameters C (Z) can be expressed as:

$C\left(z\right)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{error}{(T^i,O^i)}^2$

Error (T wherein ⁱ, O ⁱ) be resultant image T ⁱWith the difference of actual image Oi, so error (T ⁱ, O ⁱ) also can be expressed as the difference e rror (T of brightness of the pixel of two images ⁱ, O ⁱ)=(S ⁱ-R ⁱ).So optimization parameters C (Z) can be expressed as in addition:

$C=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{error}{(T^i,O^i)}^2=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{(S^i-R^i)}^2$

In addition, for the resultant image that makes object has more continuity, so optimization parameters C (Z) is added level and smooth (smoothterm):

$C\left(Z\right)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}[{(S^i-R^i)}^2+\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}{(r_j-z_i)}^2]$

Therefore, optimization parameters C (Z) comprises first and second, and wherein first is the brightness S corresponding to a plurality of pixels of resultant image ⁱWith actual image O ⁱThe brightness R of a plurality of pixels ⁱBetween difference square, and second difference corresponding to the degree of depth of the degree of depth of each pixel of resultant image and corresponding a plurality of surrounding pixels.

Above-mentioned optimization parameters C (Z), wherein Z _iRepresent the degree of depth in the described resultant image; r _jExpression is corresponding to Z _iThe degree of depth of plural surrounding pixel; N represents the sum of all pixels in the described resultant image; M represents the sum of described a plurality of surrounding pixels; I is corresponding to the pixel in the described resultant image; J is corresponding to described a plurality of surrounding pixels.

Next, in step S132, adjust reflection parameters P _M, comprise scattering coefficient k _d, the mirror coefficient k _sWith brightness α, to adjust resultant image and optimization parameters C (Z).Then, whether judge optimization parameters C (Z) less than first default value (step S134), greater than first default value, then repeating step S132 continues to adjust reflection parameters P as if optimization parameters C (Z) _MIf optimization parameters C (Z) less than first default value, is then determined described reflection parameters P _MFor the best, then enter step S136, according to the reflection parameters P of described the best _MAdjust 3 D stereo depth parameter and optimization parameters C (Z).Then in step S318, whether judge the optimization parameter less than second default value, if not, then repeating step S136 continues to adjust depth parameter; If determine that then described depth parameter is best.Then, enter step S139, whether the difference of judging resultant image and actual image is less than the 3rd default value, if then expression obtains the object resultant image (step S150) of best mirror material; If not, then get back to step S132, repeat to adjust steps such as the reflection coefficient in the Phong model and the picture element degree of depth till the difference of resultant image and actual image is less than the 3rd default value.

In addition, in the above-mentioned steps, obtain best reflection parameters P _MWith the adjustment process of depth parameter, the adjustment notion of its optimization parameters C (Z) is by adjusting reflection parameters P _MWith depth parameter, make resultant image can more approach the entity image, the value of therefore just wishing C (Z) can be the smaller the better, but the true property of the plan of resultant image is high more, the relative meeting of its needed adjustment time is long more, therefore the user of association area of the present invention can intend the speed that requires degree and resultant image of true property to resultant image according to the individual, sets first default value and second default value and the 3rd default value.

At optimization reflection parameters P _MWith the depth parameter aspect, can utilize Broyden-Fletcher-Goldfarb-Shanno (BFGS) method to obtain optimized the separating of C (Z), the BFGS method is a kind of quasi-Newton method (quasi-Newton Method) and is the most frequently used a kind of variable-metric method (variable metric method).The BFGS method mainly is divided into several steps, at first, get initial point and initial matrix, then objective matrix is carried out partial differential to obtain gradient vector, if its result then can stop to calculate less than default accuracy requirement, it is separated is optimum solution, if not, then calculates and searches direction to obtain optimum solution one by one.Algorithm details about the BFGS method please refer to Applied Optimization with MATLAB Programming, P.Venkataraman, WileyInterScience.

Utilize the method for BFGS, present embodiment can carry out C (Z) the reflection parameters P of the optimum solution that partial differential extrapolates earlier _MWith depth parameter, its calculation equation is:

$\frac{\mathrm{\&delta;C}\left(Z\right)}{\mathrm{\&delta;}\left(P_M\right)}=\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{error}{(T^i,O^i)}^2}{\mathrm{\&delta;}\left(P_M\right)}$

$=2\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\mathrm{error}(T^i,O^i)\&CenterDot;\frac{\mathrm{\&delta;error}(T^i,O^i)}{\mathrm{\&delta;}\left(P_M\right)}.$

Obtain to meet the reflection parameters P that the user requires whereby _MWith depth parameter, and then the object resultant image of the mirror material of acquisition the best.It should be noted that the present invention not only can come calculating optimum to separate by BFGS, other all can be applicable to this problem as conjugate gradient methods such as (conjugategradient).

In addition, if the part of synthetic body is translucent material, then can select translucent material model to come image is carried out optimization, promptly step S140～S160 at first, utilizes translucent model to set up resultant image T ⁱ(step S140):

$T^i=<p_x^i,p_x^i,S^i>$

The translucent model of present embodiment can be two-way Subsurface Scattering reflection distribution function (Bidirectional surfacescattering distribution function, BSSRDF) model (please refer to H.Jensen about the BSSRDF model, S.Marschner, M.Levoy, and P.Hanrahan, ＂ A Practical Model for Subsurface Light Transport ＂, Proceedings of SIGGRAPH, pages 511-518,2001), the equation of wherein two-way Subsurface Scattering reflection distribution function model is as follows:

$S_d(x_i,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_i,x_o,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_o)=\frac{1}{\mathrm{\&pi;}}{F}_t(x_i,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_i)P_d\left({\left|\right|x_i-x_o\left|\right|}_2\right)F_t(x_o,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_o)$

S _d F _t x _i x _o

P _d

S wherein _dBe the brightness of pixel, F _tBe Fresnel transmittance; x _iEnter the incoming position of object for light; x _oThe refraction position of leaving object for light; Be incident angle;

Be refraction angle; P _dScattered quantum varied curve letter formula for object.We are with reference to H.W.Jensen in the present embodiment, S.R.Marschner, M.Levoy and P.Hanrahan is at ＂ A PracticalModel for Subsurface Light Transport ＂, and the notion of the diffusion dipole (Rd) that Proceedings of ACM SIGGRAPH ' 01 this piece paper is proposed is similar to P _dThis letter formula is to reduce computing time.

$R_d\left(r\right)=\frac{\mathrm{\&alpha;}\&prime;z_r(1+{\mathrm{\&sigma;}}_{\mathrm{tr}}{d}_{r,i})e^{-{\mathrm{\&sigma;}}_{\mathrm{tr}}{d}_r}}{4\mathrm{\&pi;}{d}_r^3}-\frac{\mathrm{\&alpha;}\&prime;z_v(1+{\mathrm{\&sigma;}}_{\mathrm{tr}}{d}_{v,i})e^{-{\mathrm{\&sigma;}}_{\mathrm{tr}}{d}_v}}{4\mathrm{\&pi;}{d}_v^3}$

Wherein ${\mathrm{\&sigma;}}_{\mathrm{tr}}=\sqrt{3{\mathrm{\&sigma;}}_a{\mathrm{\&sigma;}}_t^{\&prime;}}$ Be effective transfer coefficient (effective transport coefficient), ${\mathrm{\&sigma;}}_t^{\&prime;}={\mathrm{\&sigma;}}_a+\mathrm{\&sigma;}$ Be impairment coefficient (reduced extinction coefficient), σ _aWith

Be respectively absorption coefficient (absorption coefficient) and dispersion coefficient (scattering coefficient); R=‖ x _o-x _i‖; $d_v=\sqrt{r^2+z_v^2}$ With $d_r=\sqrt{r^2+z_r^2}$ Be subjected to the influence power of two magnetic poles for the point of giving surface magnetic force; $Z_r=1/{\mathrm{\&sigma;}}_t^{\&prime;}$ Be the positive correlation coefficient of true light source (positive pole) to body surface; Z _v=Z _r+ 4AD is the negative correlation coefficient of virtual light source (negative pole) to body surface, $D=\frac{1}{3{\mathrm{\&sigma;}}_t^{\&prime;}}$ Be scattering constant, and definition A=(1+F _Dr)/(1-F _Dr) F wherein _DrBe the Fresnel light reflected value (diffuse Fresnel reflectance) of scattered portion, we remove approximate F with following formula _Dr

Wherein η is the refraction ratio (index of refraction) of object material.At last, in the BSSRDF model, we can summarize the pixel depth S of synthetic translucent material object _iNeeded reflection parameters P _MFor: σ _a(absorption coefficient), σ _s(dispersion coefficient) and η (the refraction ratio of material).Therefore by above-mentioned response parameter P _M, can clearer understanding by translucent model, for example be two-way Subsurface Scattering reflection distribution function model, can be so that the translucent portion of resultant image more approaches the entity image.

Ensuing optimization procedures step S142～S149, then similar in appearance to step 132～139 of synthesizing mirror material model, its main difference be employed model difference with and the reflection parameters difference adjusted, then similar as for optimized process to step 132～139 to algorithm principle, do not add at this and to give unnecessary details, after via optimization procedures, just can obtain the resultant image (step S160) of best translucent material.

In addition, it should be noted that, ((the optimization step of step S132～S139) can repeat the Phong model, utilizes littler default value or stricter standard to come the optimization image, makes the more approaching actual image of its image for step S132～S139) and BSSRDF model.It should be noted that, adopt Phong model or BSSRDF model to set up resultant image no matter be, all can compare the poor of resultant image and actual image, then can carry out optimized process again to set up resultant image comparatively true to nature if both differ by more than default value.In addition, for having the various material object of (comprising mirror material and translucent material), then can use two kinds of models to carry out optimization in regular turn, adopt the Phong model to carry out optimization earlier, and then use the BSSRDF model to carry out optimization, vice versa, and present embodiment does not limit its optimization order.Further instruction please refer to second embodiment.

Second embodiment

Fig. 2 is the method flow diagram that the 3 d surface model of the object of another embodiment of the present invention is rebuild.Because actual object has mirror part and translucent portion usually simultaneously, therefore compared to first embodiment, second embodiment does optimized adjustment for the object of wanting resultant image in regular turn for considering the mirror material part and translucent material part of object simultaneously.It should be noted that owing in different models, be used for describing the reflected by objects parameter and may represent different parameters, therefore be the differentiation reflection parameters that desire is adjusted in different models.In the following description, present embodiment reflection parameters that desire in the Phong model is adjusted is (as scattering coefficient k _d, the mirror coefficient k _sWith brightness α) be called first reflection parameters, with reflection parameters (as the absorption coefficient) σ of desire adjustment in the BSSRDF model _a, dispersion coefficient

And the refraction ratio η of material) is referred to as with second reflection parameters.

At first, as described in step S210, use the three-dimensional structure photosystem to obtain the initial 3 D stereo position of object, in step S220, the technology and the Lambertian reflection model that see through the shadow reconstructed surface are obtained the synthetic 3 D stereo position and the initial value of reflection parameters, next as described in the step S230, come synthetic body mirror material part according to 3 D stereo position and Phong model, to set up resultant image.By resultant image and actual image, can define the optimization parameter and be:

$C\left(Z\right)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}[{(S^i-R^i)}^2+w\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}{(r_j-z_i)}^2]$

This optimization parameter is same as first embodiment, and its detail section does not add tired stating at this.Then, in step 240, adjust first reflection parameters and the optimization parameters C (Z) of Phong model, above-mentioned first reflection parameters then for example is scattering coefficient k _d, the mirror coefficient k _sWith brightness α.Next, in step S250, whether judge optimization parameters C (Z) less than first default value, if not, then repeating step S240 continues to adjust first reflection parameters; If, determine that then described first reflection parameters is best, then enter step S260, adjust the depth parameter and the optimization parameters C (Z) of 3 D stereo position according to first reflection parameters in the Phong model after the optimization.Then, in step S270, judge that the optimization parameter whether less than second default value, if not, then gets back to step S260, continue to adjust depth parameter; If, determine that then described depth parameter is best, and according to obtaining the resultant image (step S280) that best reflection parameters and optimum depth parameter obtain mirror material object in the above-mentioned adjustment process.

In the mirror part back of adjusting object (is step S210～S280), then will adjust the translucent portion of object.In step S231, be casually arranged with distribution function model adjustment resultant image according to 3 D stereo position that has the mirror characteristic after adjusting and two-way subsurface.Then, in step S241, adjust the reflection parameters in the BSSRDF model, to adjust resultant image and optimization parameter, the reflection parameters in the BSSRDF model then for example is σ _a(absorption coefficient),

(dispersion coefficient) and η (the refraction ratio of material).

Next, in step S251, whether judge optimization parameters C (Z) less than the 3rd default value, if not, then repeating step S250 continues to adjust the reflection parameters in the BSSRDF model; If, determine that then described second reflection parameters is best, then enter step S261, adjust 3 D stereo depth parameter and optimization parameters C (Z) according to second reflection parameters of the best.Then, in step S271, whether judge the optimization parameter less than the 4th default value, if not, then repeating step S261 continues to adjust depth parameter; If, then enter among the step S281, determine that then described depth parameter is best, whether the difference of further judging resultant image and actual image is less than the 5th default value.If then enter step S282, according to obtaining best second reflection parameters and optimum depth parameter, the object resultant image that obtains to have mirror material characteristic and translucent material characteristic in the above-mentioned adjustment process.

The above-mentioned first, second, third and the 4th default value mainly is corresponding to the demand of user for the resultant image degree of verisimilitude, and its setting value can be decided according to the needed specification of user, and present embodiment is not limited.

In sum, the present invention's geometric data of bodies that the structured light positioning system is obtained is combined with the resulting meticulous geological information of the technology of shadow reconstruction method, and utilizes mirror model and translucent model to solve known tool part mirror and translucent object 3 d surface model that can't accurate reconstruction.Except rebuilding the three-dimensional model of object, the present invention also can obtain the optimized reflection parameters characteristic of object, for the development in science and technology of entity object digitizing and computer vision sizable help is arranged.Simultaneously, utilize optimization parameter of the present invention can shorten the time of image optimumization and obtain the object model and the image of high degree of verisimilitude.

More than be preferred embodiment of the present invention, all changes of doing according to technical solution of the present invention when the function that is produced does not exceed the scope of technical solution of the present invention, all belong to protection scope of the present invention.

Claims (10)

1, a kind of method of reconstructing three-dimensional surface model is characterized in that: may further comprise the steps:

(1) a 3 D stereo position of obtaining an object with a three-dimensional structure photosystem and a plurality of reflection parameters corresponding to described object;

(2) set up a resultant image according to described 3 D stereo position and described a plurality of reflection parameters;

(3) adjust described a plurality of reflection parameters to adjust described resultant image, up to an optimization parameter less than one first default value;

Wherein, described optimization parameter is corresponding to the difference of the brightness of the brightness of a plurality of first pixels in the adjusted described resultant image and a plurality of second pixels in the actual image.

2, the method for reconstructing three-dimensional surface model according to claim 1, it is characterized in that: described optimization parameter comprises one first and one second, the difference of the brightness of a plurality of first pixels in described first described resultant image of correspondence and the brightness of a plurality of second pixels in the described actual image square, described second difference corresponding to the degree of depth of the degree of depth of each first pixel in the described resultant image and corresponding a plurality of surrounding pixels, the equation of described optimization parameter is expressed as follows:

$C\left(Z\right)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}[{(S^i-R^i)}^2+w\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}{(r_j-z_i)}^2]$

Wherein, the described optimization parameter of C (Z) expression; S ⁱRepresent the brightness of first pixel in the described resultant image; R ⁱRepresent the brightness of second pixel in the described actual image; Z _iThe degree of depth of representing first pixel in the described resultant image; r _jExpression is corresponding to Z _iThe degree of depth of surrounding pixel; N represents the sum of all pixels in the described resultant image; M represents the sum of described a plurality of surrounding pixels; I is shown in the index value of the pixel in the described resultant image; J represents the index value of described a plurality of surrounding pixels; W represents weights.

3, the method for reconstructing three-dimensional surface model according to claim 1, it is characterized in that: in step (1), also comprise: utilize a Lambertian reflection model and a shadow reconstructed surface technology to obtain the 3 D stereo position of described object and the initial value of a plurality of reflection parameters; Described reflection parameters comprise a scattering coefficient and a normal vector at least one of them.

4, the method for reconstructing three-dimensional surface model according to claim 1 is characterized in that: in step (2), also comprise: utilize a mirror material model and described a plurality of reflection parameters to set up described resultant image; Described reflection parameters comprises a scattering coefficient, a mirror coefficient and a gloss coefficient, and described mirror material model is a Phong model, and the equation of described Phong model is expressed as follows:

S _i＝k _d*N _i·L+k _s*(F _i·V) ^α

Wherein, S _iBrightness for pixel; k _dBe scattering coefficient; k _sBe the mirror coefficient; N _iBe this surface normal, can be by contiguous z _iSlope obtain; L is the incident light vector; F _iBe complete mirror reflection vector, can be by N _i, L obtains; V is the visual angle vector; α is the gloss coefficient.

5, the method for reconstructing three-dimensional surface model according to claim 1 is characterized in that: in step (2), also comprise: utilize half transparent material model and described a plurality of reflection parameters to set up described resultant image; Described reflection parameters comprises a dispersion coefficient, an absorption coefficient and a refractive index, described translucent material model is a two-way Subsurface Scattering reflection distribution function (Bidirectional surface scattering distribution function, BSSRDF) model, the equation of described two-way Subsurface Scattering reflection distribution function model is as follows:

$S_d(x_i,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_i,x_o,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_o)=\frac{1}{\mathrm{\&pi;}}{F}_t(x_i,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_i)P_d\left({\left|\right|x_i-x_o\left|\right|}_2\right)F_t(x_o,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_o)$

Wherein, S _dBrightness for pixel; F _tBe the Fresnel transfer function; x _iEnter the incoming position of object for light; x _oLeave the refraction position of object for light;

Be incident angle;

Be refraction angle; P _dScattered quantum varied curve letter formula for object.

6, the method for reconstructing three-dimensional surface model according to claim 1 is characterized in that: in step (3), also comprise: recomputate described optimization parameter to readjust described a plurality of reflection parameters according to adjusted described resultant image.

7, the method for reconstructing three-dimensional surface model according to claim 1 is characterized in that: also comprise:

Adjust a depth parameter in the described 3 D stereo position according to adjusted described a plurality of reflection parameters, up to described optimization parameter less than one second default value; And

Repeat to adjust described a plurality of reflection parameters and described 3 D stereo position up to the difference of described resultant image and described actual image less than one the 3rd default value.

8, a kind of method of reconstructing three-dimensional surface model is characterized in that: may further comprise the steps:

(1) obtains a 3 D stereo position of an object with a three-dimensional structure photosystem;

(2) according to described 3 D stereo position and a Phong modelling one resultant image;

(3) adjust a plurality of first reflection parameters in the described Phong model to adjust described resultant image, up to an optimization parameter less than one first default value;

(4) adjust a depth parameter in the described 3 D stereo position according to adjusted described a plurality of first reflection parameters, up to described optimization parameter less than one second default value;

(5) adjust described resultant image according to an adjusted described 3 D stereo position and a two-way Subsurface Scattering reflection distribution function model;

(6) adjust a plurality of second reflection parameters in the described two-way Subsurface Scattering reflection distribution function model to adjust described resultant image, up to described optimization parameter less than one the 3rd default value;

(7) adjust described depth parameter in the described 3 D stereo position according to adjusted described a plurality of second reflection parameters, up to described optimization parameter less than one the 4th default value;

Wherein, described optimization parameter comprises one first and one second, the difference of the brightness of a plurality of first pixels in described first described resultant image of correspondence and the brightness of a plurality of second pixels in the actual image square, described second difference corresponding to the degree of depth of the degree of depth of described a plurality of first pixels in the described resultant image and corresponding a plurality of surrounding pixels.

9, the method for reconstructing three-dimensional surface model according to claim 8 is characterized in that:

In step (1), also comprise: utilize a Lambertian reflection model and a shadow reconstructed surface technology to obtain 3 D stereo position, a scattering coefficient and a normal vector of described object;

Described a plurality of first reflection parameters comprises a scattering coefficient, a mirror coefficient and a gloss coefficient;

Described a plurality of second reflection parameters comprises a dispersion coefficient, an absorption coefficient and a refractive index;

The equation of described optimization parameter is expressed as follows:

$C\left(Z\right)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}[{(S^i-R^i)}^2+w\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}{(r_j-z_i)}^2]$

Wherein, the described optimization parameter of C (Z) expression; S ⁱRepresent the brightness of first pixel in the described resultant image; R ⁱRepresent the brightness of second pixel in the described actual image; Z _iThe degree of depth of representing first pixel in the described resultant image; r _jExpression is corresponding to Z _iThe degree of depth of surrounding pixel; N represents the sum of all pixels in the described resultant image; M represents the sum of described a plurality of surrounding pixels; I is shown in the index value of the pixel in the described resultant image; J represents the index value of described a plurality of surrounding pixels; W represents weights;

The equation of described Phong model is expressed as follows:

S _i＝k _d*N _i·L+k _s*(F _i·V) ^α

Wherein, S _iBrightness for pixel; k _dBe scattering coefficient; k _sBe the mirror coefficient; N _iBe this surface normal, can be by contiguous z _iSlope obtain; L is the incident light vector; F _iBe complete mirror reflection vector, can be by N _i, L obtains; V is the visual angle vector; α is the gloss coefficient;

The equation of described two-way Subsurface Scattering reflection distribution function model is as follows:

$S_d(x_i,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_i,x_o,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_o)=\frac{1}{\mathrm{\&pi;}}{F}_t(x_i,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_i)P_d\left({\left|\right|x_i-x_o\left|\right|}_2\right)F_t(x_o,{\stackrel{\&RightArrow;}{\mathrm{\&omega;}}}_o)$

Wherein, S _dBrightness for pixel; F _tBe the Fresnel transfer function; x _iEnter the incoming position of object for light; x _oLeave the refraction position of object for light;

Be incident angle; Be refraction angle; P _dScattered quantum varied curve letter formula for object.

10, the method for reconstructing three-dimensional surface model according to claim 8 is characterized in that: also comprise:

Repeat to adjust described first reflection parameters, second reflection parameters, depth parameter and 3 D stereo position, up to the difference of described resultant image and described actual image less than one the 5th default value.

Images