METHOD FOR DIGITALLY RENDERING SKIN OR LIKE MATERIALS

• US 20090174713A1
• Filed: 03/12/2009
• Published: 07/09/2009
• Est. Priority Date: 11/15/2002
• Status: Active Grant

• Current Assignee: George Borshukov, J.P. Lewis
• Original Assignee: George Borshukov, J.P. Lewis
• Inventors: Lewis, J.P., Borshukov, George
• Granted Patent: US 8,515,157 B2
• Time in Patent Office: Days
• US Class Current: 345/426
• CPC Class Codes: G06T 13/80 2D [Two Dimensional] animation, e.g. using sprites
• CPC Class Codes: G06T 15/20 Perspective computation
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 2200/08 involving all processing steps from image acquisition to 3D model generation
• CPC Class Codes: G06T 2210/61 Scene description
• CPC Class Codes: G06T 7/55 from multiple images
• CPC Class Codes: H04N 5/262 Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects

Abstract

A computationally efficient method for rendering skin tissue to achieve lifelike results includes application of a blurring algorithm to a two-dimensional light map. The algorithm is compact and is not derived from complex mathematical models of subsurface scattering in translucent materials, and yet achieves results similar to more complex models. The method includes receiving three-dimensional surface geometry relating to a digital object and other information for defining modeled light reflected from the surface, generating a two-dimensional matrix of light intensity values mapped to the surface geometry, blurring the matrix using a compact algorithm, and rendering the object using the blurred light intensity values.

Claims

1-20. -20. (canceled)

21. A computer-implemented method, comprising:

generating a first matrix of light intensity values representing diffuse light reflection from a color-neutral surface of an object, the first matrix excluding any representation of subsurface light scattering and specular reflection;

blurring the first matrix of light intensity values to define a blurred matrix;

generating pixel values for an image of the object using the blurred matrix of light intensity values in combination with a color map representing specular surface colors of the object to provide a rendered image simulating subsurface scattering near a surface of the object; and

storing in a computer memory the pixel values of the image.

22. The method of claim 21, wherein blurring the first matrix further comprises convolving the light intensity matrix.

23. The method of claim 21, wherein blurring the first matrix further comprises processing the light intensity matrix using a Fast Fourier Transform function.

24. The method of claim 21, wherein blurring the first matrix further comprises executing a blurring algorithm of the form e⁻

(x^2+y2)/σ

, where x and y are the horizontal and vertical widths, respectively, of the blur kernel in number of lumels, e is the base of the natural logarithm, and σ

is a spreading parameter.

25. The method of claim 21, further comprising generating the color map as one or more matrices of values representing the specular surface reflection from the object.

26. The method of claim 25, wherein generating the color map further comprises generating separate matrices for each of three color separation channels.

27. The method of claim 26, wherein blurring the first matrix further comprises blurring the first matrix for each of the three color separation channels according to the general expression

I_x,y=V_x,y·

I_0,0;

where I_x,y is a blurred value of each (x,y)_th lumel, V_x,y is an attenuation factor for each (x,y)_th defining a blur kernel having a predetermined width, and I_0,0 is an unblurred value of each (x,y)_th lumel of the first matrix.

28. The method of claim 27, wherein blurring the first matrix further comprises computing the blur kernel

V_x,y=1/(√

{square root over (x²+y²)}+1)^PRGB

separately for each channel, wherein x and y are computed over the range of −

h_RGB to h_RGB, h_RGB is a corresponding h_R, h_G, or h_B halfwidth of the blur kernel for each channel, and P_RGB is a corresponding P_R, P_G, or P_B power factor for each channel.

29. The method of claim 28, wherein blurring the first matrix further comprises computing V_x,y using a corresponding value of P_R, P_G, and P_B for each respective color channel within a range of 2 to 4.

30. The method of claim 28, wherein blurring the first matrix further comprises computing V_x,y over a halfwidth h_RGB determined by

$h_{\mathrm{RGB}}=\frac{K_{\mathrm{RGB}}·}{}$

W a + b

where W is the width or largest dimension of the first matrix, in number of lumels, K_RGB is a corresponding kernel size factor K_R, K_G, and K_B for each respective color channel within a range of 5 to 20, a is within a range of 1000 to 2000, and b is within a range of 0 to 1.

31. A system for rendering an appearance of subsurface scattering in an object, comprising:

a computer memory storing a blurred two dimensional matrix of light intensity values representing diffuse reflection from a color-neutral surface and excluding representation of subsurface light scattering and specular reflection; and

a processing unit in communication with the computer memory, wherein the processing unit is programmed with instructions for rendering the object using the blurred two dimensional matrix of light intensity values in combination with a color map representing specular surface colors of the object to provide a rendered image simulating subsurface scattering near a surface of the object.

32. The system of claim 31, wherein the processing unit is programmed with instructions for generating the blurred two dimensional matrix of light intensity values from an unblurred two dimensional matrix of light intensity values.

33. The system of claim 32, wherein the processing unit is programmed with instructions for generating the blurred two dimensional matrix of light intensity values by executing a blurring algorithm of the form e⁻

(x^2+y2)/σ

, where x and y are the horizontal and vertical widths, respectively, of the blur kernel in number of lumels, e is the base of the natural logarithm, and σ

is a spreading parameter.

34. The system of claim 31, further comprising the color map stored in a computer memory as a two dimensional matrix of values representing specular surface reflection from the object.

35. The system of claim 32, wherein the processing unit is programmed with instructions for generating the color map as one or more matrices of values representing specular surface reflection from the object.

36. The system of claim 32, wherein the processing unit is programmed with instructions for generating the color map comprising separate matrices for each of three color separation channels.

37. The system of claim 36, wherein the processing unit is programmed with instructions for generating the blurred two dimensional matrix of light intensity values for each of the three color separation channels according to the general expression

I_x,y=V_x,y·

I_0,0;

where I_x,y is a blurred value of each (x,y)_th lumel, V_x,y is an attenuation factor for each (x,y)_th defining a blur kernel having a predetermined width, and I_0,0 is an unblurred value of each (x,y)_th lumel of the first matrix.

38. The system of claim 37, wherein the processing unit is programmed with instructions for generating the blurred two dimensional matrix of light intensity values further by computing the blur kernel

V_x,y=1/(√

{square root over (x²+y²)}+1)^PRBG

separately for each channel, wherein x and y are computed over the range of −

h_RGB to h_RGB, h_RGB is a corresponding h_R, h_G, or h_B halfwidth of the blur kernel for each channel, and P_RGB is a corresponding P_R, P_G, or P_B power factor for each channel.

39. The system of claim 38, wherein the processing unit is programmed with instructions for generating the blurred two dimensional matrix of light intensity values comprising computing V_x,y using a corresponding value of P_R, P_G, and P_B for each respective color channel within a range of 2 to 4.

40. The system of claim 38, wherein the processing unit is programmed with instructions for computing V_x,y over a halfwidth h_RGB determined by

$h_{\mathrm{RGB}}=\frac{K_{\mathrm{RGB}}·}{}$

W a + b

where W is the width or largest dimension of the first matrix, in number of lumels, K_RGB is a corresponding kernel size factor K_R, K_G, and K_B for each respective color channel within a range of 5 to 20, a is within a range of 1000 to 2000, and b is within a range of 0 to 1.