U.S. patent application number 13/953285 was filed with the patent office on 2015-01-29 for visualization method.
This patent application is currently assigned to X-RITE EUROPE GMBH. The applicant listed for this patent is Marc S. Ellens, Beat Frick, Adrian Kohlbrenner, Francis Lamy, Martin Rump. Invention is credited to Marc S. Ellens, Beat Frick, Adrian Kohlbrenner, Francis Lamy, Martin Rump.
Application Number | 20150032430 13/953285 |
Document ID | / |
Family ID | 51022220 |
Filed Date | 2015-01-29 |
United States Patent
Application |
20150032430 |
Kind Code |
A1 |
Rump; Martin ; et
al. |
January 29, 2015 |
Visualization Method
Abstract
The present invention provides a method of digitally generating,
via the use of a computer, data indicative of a synthesized
appearance of a simulated material having physically plausible
appearance attributes. The method includes determining a set of
data indicative of the synthesized appearance of the simulated
material based at least in part on data associated with the
physically tangible source material and at least in part on data of
measured attributes of the physically tangible reference
material.
Inventors: |
Rump; Martin; (Winterscheid,
DE) ; Ellens; Marc S.; (Grand Rapids, MI) ;
Kohlbrenner; Adrian; (Thalwil, CH) ; Lamy;
Francis; (Wollerau, CH) ; Frick; Beat; (Buchs,
CH) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Rump; Martin
Ellens; Marc S.
Kohlbrenner; Adrian
Lamy; Francis
Frick; Beat |
Winterscheid
Grand Rapids
Thalwil
Wollerau
Buchs |
MI |
DE
US
CH
CH
CH |
|
|
Assignee: |
X-RITE EUROPE GMBH
Regensdorf
CH
|
Family ID: |
51022220 |
Appl. No.: |
13/953285 |
Filed: |
July 29, 2013 |
Current U.S.
Class: |
703/6 |
Current CPC
Class: |
G01J 3/463 20130101;
G01J 3/504 20130101; G01J 3/027 20130101; G06F 30/20 20200101; G01N
21/47 20130101; G06T 11/001 20130101 |
Class at
Publication: |
703/6 |
International
Class: |
G06F 17/50 20060101
G06F017/50 |
Claims
1. A method of digitally generating, via a computer, data
indicative of a synthesized appearance of a simulated material
having physically plausible appearance attributes, with the
synthesized appearance being based on a physically tangible
reference material and at least one value of a selected appearance
attribute of a physically tangible source material different from
the reference material, comprising the steps of: (a) accessing, via
the computer, a first set of data indicative of the values of
measured appearance attributes of the reference material, with the
measured appearance attributes being measured at a plurality of
locations on the reference material and for a plurality of
illumination directions or a plurality of viewing directions
relative to each of the locations; (b) accessing, via the computer,
a second set of data indicative of a value of at least one measured
appearance attribute of the source material, wherein the appearance
attribute of the source material includes at least one, but not
all, of the appearance attributes being measured on the reference
material; (c) determining, via the computer, a third set of data
indicative of the synthesized appearance of the simulated material
based at least in part on data from the second set of data
associated with the physically tangible source material and at
least in part on data from the first set of data of measured
appearance attributes of the physically tangible reference material
different from that of the second set of data; and (d) displaying
an image generated from the third set of data of the synthesized
appearance of the simulated material.
2. The method of claim 1, further comprising measuring appearance
attributes of the physically tangible reference material at a
plurality of locations on the reference material by illuminating
each of the locations on the reference material with EM radiation
in the range of near IR, UV or humanly detectable frequency spectra
from a plurality of illumination directions and measuring the EM
radiation reflected from or transmitted through the reference
material, and determining values of the appearance attributes of
the reference material based on the reflected or transmitted EM
radiation to form the first set of data.
3. The method of claim 1, further comprising measuring appearance
attributes of the physically tangible reference material at a
plurality of locations on the reference material by illuminating
each of the locations on the reference material with EM radiation
in the range of near IR, UV or humanly detectable frequency spectra
and measuring the EM radiation reflected from or transmitted
through the reference material from a plurality of viewing
directions, and determining values of the appearance attributes of
the reference material based on the reflected or transmitted EM
radiation to form the first set of data.
4. The method of claim 1, wherein step (c) comprises: (i)
determining a third set of data indicative of the synthesized
appearance of the simulated material based at least in part on the
values of the measured appearances attributes of the source
material and the values of the measured appearance attributes of
the reference material, (ii) determining an error value consisting
of (a) the difference between a parameter of a measured appearance
attribute of the source material and the same parameter of the
corresponding appearance attribute in the third set of data, (b) a
physical plausibility value based on the difference between a
parameter of a measured appearance attribute of the reference
material and the same parameter of the corresponding measured
appearance attribute in the third set of data and (iii) if the
error value is greater than a predetermined threshold, then
revising the determining of the third set of data indicative of the
synthesized appearance of the simulated material, (iv) repeating
steps (i) through (iii) until (i) the error value is less than the
predetermined threshold or (ii) the change of the error value is
less than a second, predetermined threshold.
5. The method of claim 1, wherein the first set of data constitutes
a Bidirectional Texture Function (BTF), a Bi-Directional
Scattering-Surface Reflectance Distribution Function (BSSRDF),
Spatially Varying Bi-Directional Transmission Distribution Function
(SVBTDF), or a Spatially Varying Bi-Directional Reflectance
Distribution Function (SVBRDF).
6. The method of claim 1, wherein the second set of data is
indicative of values of a plurality of measured appearance
attributes of the source material, and wherein the appearance
attributes of the source material include some, but not all, of the
appearance attributes being measured on the reference material.
7. The method of claim 1, wherein the appearance attributes are
selected from the group consisting of lightness, saturation, hue,
gloss, specularity, distinctness of image, haze, subsurface
scattering, translucency, turbidity, texture, surface height
variation and normal maps.
8. The method of claim 1, wherein the appearance attribute is
measurable via EM radiation in the near IR, UV or humanly
detectable frequency spectra reflected from or transmitted through
the reference material or the source material of the simulated
material.
9. The method of claim 1, further comprising processing the third
set of data to form an image representative of the synthesized
appearance of the simulated material.
10. The method of claim 9, wherein the image is three
dimensional.
11. The method of claim 1, further comprising processing the third
set of data to print a physically tangible object having the
synthesized appearance of the simulated material.
12. The method of claim 1, further comprising processing the third
set of data to form a haptic display representative of the
synthesized appearance of the simulated material.
13. The method of claim 1, further comprising accessing a fourth
set of data indicative of standardized values of appearance
attributes representative of a family of generally similar
physically tangible materials of which the reference material or
the source material is a member, and determining the third set of
data based at least in part from data from the fourth set of
data.
14. The method of claim 1, where the number of appearance
attributes represented in the second set of data is less than 1% of
the number of appearance attributes represented in the first set of
data.
15. A data set of values of appearance attributes for a synthesized
appearance of a simulated material having physically plausible
appearance attributes generated by the method of claim 1.
16. An image generated from a data set of values of appearance
attributes for a synthesized appearance of a simulated material
having physically plausible appearance attributes generated by the
method of claim 1.
17. A system for digitally generating data indicative of a
synthesized appearance of a simulated material having physically
plausible appearance attributes, with the synthesized appearance
being based on a physically tangible reference material and at
least one value of a selected appearance attribute of a physically
tangible source material different from the reference material, the
system comprising: (a) memory for storing a first set of data
indicative of the values of measured appearance attributes of the
reference material, with the measured appearance attributes being
measured at a plurality of locations on the reference material and
for a plurality of illumination directions or a plurality of
viewing directions relative to each of the locations; (b) an
instrument for measuring at least one appearance attribute of the
source material and generating a second set of data indicative of a
value of the measured appearance attribute, wherein the appearance
attribute of the source material includes at least one, but not
all, of the appearance attributes being measured on the reference
material; (c) a computer configured to receive the first and second
sets of data and configured to determine a third set of data
indicative of the synthesized appearance of the simulated material
based at least in part on data from the second set of data
associated with the physically tangible source material and at
least in part on data from the first set of data of measured
appearance attributes of the physically tangible reference material
different from that of the second set of data; and (d) a display in
communication with the computer.
18. The system of claim 17, further comprising a processor
configured to receive data from the third set of data and
configured to form an image representative of the synthesized
appearance of the simulated material based at least in part on the
data from the third set of data.
19. The system of claim 17, further comprising a processor
configured to receive data from the third set of data and
configured to produce an object having the synthesized appearance
of the simulated material based at least in part on the data from
the third set of data.
20. The system of claim 17, wherein at least a portion of the
memory for storing the first set of data is carried on the
computer.
21. The system of claim 17, wherein the computer and the instrument
are combined in a single integral device.
22. The system of claim 18, wherein the computer and the processor
are combined in a single integral device.
23. The system of claim 17, wherein data from the first and second
sets of data are transmitted via media selected from the group
consisting of a hardware connection, a wireless connection or a
portable memory device.
24. The system of claim 17, wherein the instrument constitutes a
first instrument comprising at least one source of EM radiation in
the range of near IR, UV or humanly detectable frequency
spectra.
25. The system of claim 24, wherein the instrument source emits the
full spectra of EM radiation in the range of near IR, UV and
humanly detectable frequency spectra.
26. The system of claim 24, wherein the instrument source emits a
selected spectrum of EM radiation from the range of near IR, UV and
humanly detectable frequency spectra.
27. The system of claim 24, wherein the first instrument further
comprises at least one detector for measuring EM radiation
reflected from or transmitted through the source material when
illuminated by the source of EM radiation, and determining values
of the appearance attributes of the source material.
28. The system of claim 24, further comprising a second instrument
for measuring appearance attributes of the physically tangible
reference material at a plurality of locations on the reference
material by illuminating each of the locations on the reference
material with EM radiation in the range of near IR, UV or humanly
detectable frequency spectra from a plurality of illumination
directions and measuring the EM radiation reflected from or
transmitted through the reference material from a plurality of
viewing directions, and determining values of the appearance
attributes of the reference material based on the reflected or
transmitted EM radiation for data of the first set of data.
Description
BACKGROUND
[0001] The present invention relates to the general field of
visualization of materials or surfaces on a monitor by using
computer graphic techniques. In general, a digital representation
of a real material or surface is rendered, mapped onto a target
object of arbitrary shape, and the simulated appearance of the
target object is then visualized under user selected illumination
conditions and viewing directions.
[0002] From the start, it should be understood that the field of
this invention is not image creation or manipulation, which
typically includes only 2- and 3-dimensions and does not require
that the result resemble reality, much less be renderable in
reality. The field here is visualization of simulated materials
that are renderable in reality--they are physically plausible
materials.
[0003] Getting an accurate visualization of a simulated appearance
is, for most materials and surfaces occurring in the real world, an
extremely challenging technological problem. Consequently, much
effort has been expended on finding approximations that are both of
aesthetically pleasing appearance and quickly computed, albeit
without concern that the resultant appearance is representative of
a material that is physically plausible, such as required by a
product designer.
[0004] Further, in creative applications like product design, large
databases of materials are required. Various functions have been
developed, such as the Bidirectional Texture Function (BTF), which
is a material representation fitting a large number of complex
materials of many different types. However, to measure a
sufficiently representative BTF for a given real material requires
relatively complex measuring equipment and the measurements are
very time consuming. A representative surface area of the material
must be measured pixel by pixel for a large number of illumination
directions and viewing directions, typically by using a number of
digital color cameras and a complex illumination system with
hundreds of spot-type lamps distributed over the hemisphere above
the material being measured.
[0005] With the BTF measured, the visualization itself, i.e. the
graphical representation of the material on the monitor under any
desired illumination condition and any desired viewing direction
and applied or mapped to any object of any shape, is realized by
digital rendering techniques which use the BTF database as input
data. Suitable rendering techniques and software are well known in
the computer graphics art and are not subject of the present
invention. Such rendering techniques or software can retrieve color
reflectance values from the BTF database for each given pixel of
the real material for each given illumination direction and for
each given viewing direction. Intermediate values can be calculated
by interpolation from the actual values stored in the BTF
database.
[0006] Unfortunately, the creation of such databases usually
containing thousands of materials requires substantial technical
effort both in terms of measurement time and device sophistication
and is therefore often not practicable and often prohibitively
expensive.
[0007] As an alternative to producing databases for a large number
of individual materials a set of basis materials with corresponding
BTFs might be provided from which the designer can chose a sample
and then modify or edit the BTF on-the-fly to meet his
requirements. Here, an intuitive and fast editing approach is
necessary to maintain efficiency in the creative process. Moreover,
the goal of the editing process is to generate physically plausible
results that represent simulated materials that may be
manufactured.
[0008] One common approach is to fit analytical reflectance models
to the data (McAllister 2002, Daubert 2001) and to perform a
modification of model parameters afterwards. For efficient
parameter changes additional methods might be used which simplify
propagation of parameters across the material surface (An 2008).
While using reflectance models guarantees physical plausibility to
a certain degree, manually finding new parameters to match a
desired target appearance is a tedious task. Moreover, this
approach is limited to materials that can be faithfully described
by simple reflectance models. Most complex materials, especially
those exhibiting special features like glittering or significant
and large surface structures, cannot be reproduced by such an
approach with high accuracy.
[0009] Other methods do not rely on analytical models but modify
reflectance data in a more direct way. Lawrence 2006 used inverse
shade trees and an optimization scheme coined ACLS to decompose the
spatially varying material properties of planar samples from dense
hemispherical samplings in a collection of 1D curves and 2D
textures. This approach factorized the material into multiple,
low-dimensional parts, which could be edited separately, causing
certain reflectance changes on the whole material when
reconstructing from the factorized representation. While this
approach allows for a high-accuracy representation of the source
material, editing of the single parts still remains a manual
process and a desired target appearance is therefore difficult to
achieve. Moreover, the method is only applicable for flat
materials.
[0010] In Kautz 2007 a first set of editing operators for generic
BTF data was proposed. While those operators can deal with
arbitrarily complex materials, their heuristic nature means that
the physical plausibility of the final result may be low.
Additionally, a given target material is very difficult to match as
the operator parameters have to be specified manually.
[0011] A combination of the edit propagation algorithm (An 2008)
and the editing operators defined in Kautz 2007 was made by Xu
2009. While this simplifies the usage of the edit operators, it
does not overcome the basic problems of physical implausibility and
manual work.
[0012] Using measured reflectance on both the source and target
side of the editing process was proposed in An 2011. This algorithm
can transfer reflectance data from one material to match the
spatial reflectance distribution of a second material allowing for
very intuitive editing with minimal manual effort. While the method
allows enrichment of sparsely captured representations (even single
images) with highly detailed reflectance data, the other way around
is not possible as the edited material is always represented by
reflectance samples from the target material.
[0013] There is a need to easily and quickly develop a synthesized
appearance of a simulated material that not only "looks good," but
is physically plausible to enable product designers to evaluate a
wide range of simulated materials, knowing that any material
selected by the designer from the range of materials is physically
plausible for making real world products.
SUMMARY
[0014] The present invention provides a method of digitally
generating, via the use of a computer, data indicative of a
synthesized appearance of a simulated material having physically
plausible appearance attributes.
[0015] The present invention provides a method for the
visualization of real materials that doesn't require individually
measured BTF databases for all individual materials to be
visualized and thus considerably reduces the amount of pre-captured
BTF data.
[0016] The present invention also provides a data set of values of
appearance attributes for a synthesized appearance of a simulated
material having physically plausible appearance attributes
generated by the method of the present invention.
[0017] In some embodiments, the present invention also provides an
image generated from a data set of values of appearance attributes
for a synthesized appearance of a simulated material having
physically plausible appearance attributes generated by the method
of the present invention.
[0018] In some embodiments, the present invention also provides a
system for digitally generating data indicative of a synthesized
appearance of a simulated material having physically plausible
appearance attributes.
DESCRIPTION OF DRAWINGS
[0019] FIG. 1 is a flow diagram of one embodiment of the inventive
method.
[0020] FIG. 2 is a flow diagram of one embodiment of a method for
selecting pixels to be edited.
[0021] FIG. 3 is a flow diagram of a generic iteration procedure
for minimizing an error function used in the method of the
invention.
[0022] FIG. 4 is a flow diagram of a procedure for determining
parameters of editing operators used in the iteration procedure
shown in FIG. 3.
[0023] FIG. 5 is a flow diagram of a sub procedure of the procedure
shown in FIG. 4.
DESCRIPTION OF EMBODIMENTS
[0024] The following abbreviations are used herein:
[0025] BTF denotes a Bidirectional Texture Function or database.
The BTF is a six dimensional function containing a color
reflectance value (e.g. but not necessarily RGB) for every point
(pixel) on a surface area of the material (2 spatial dimensions,
i.e. x,y-coordinates) as well as for a large number of viewing and
illumination directions (2*2 spatial direction dimensions, i.e. 2
elevation and 2 azimuth angles). Due to its discrete nature the BTF
is a collection of data or database rather than a continuous
function in the strict mathematical sense. In the following the
terms BTF, BTF function and BTF database will be used
synonymously.
[0026] B denotes a (densely populated) BTF measured for a reference
material also referred to as target material. For each pixel of the
measured area of the reference material and for a large number of
illumination and viewing directions B holds a set of reflectance
values which can be e.g. RGB color values or spectral values. In
the following sets of reflectance values will be referred to
shortly as reflectance values or color values.
[0027] D denotes the totality of sparsely captured reflectance
values of one measuring point or spot of a source material (i.e., a
material other than the reference or target material). The sparsely
captured reflectance values D actually consist of a single set or a
plurality of sets of e.g. RGB values or other color values or
spectral values. If the source material is measured under one
specific illumination condition and in one specific viewing
direction only a single set of reflectance values results. If the
source material is measured under several illumination directions
and/or viewing directions a plurality s of sets Ds results
according to the number of combinations of illumination and viewing
directions. A typical color measuring device suitable for capturing
sparse reflectance values is a portable multi-angle
spectrophotometer such as the device MA98 of X-Rite, Inc., Grand
Rapids, Mich., USA. This device features multi-angle illumination
and multi-angle measuring light pick-up and produces 19 sets of
reflectance values for each measuring spot. In the following sets
of reflectance values will be referred to simply as reflectance
values or color values. A measuring device for capturing said
sparse reflectance values is referred to hereinafter also as a
simple scanner. For the sake of completeness it is to be mentioned
that the reflectance values D may also be taken, in practical use,
from a database or from a suitable color chart or the like.
[0028] B' denotes a (densely populated) BTF database derived from B
by modifying the original BTF B with sparse reflectance values D.
Modifying a BTF is also referred to as editing a BTF. The modified
BTF B' represents a simulated material that combines appearance
properties of both the reference material and the source
material.
[0029] As reflectance values D will be transferred to B, the
reflectance values D have to be of the same type as those of B,
i.e. RGB color values or spectral values or any other suitable
color values. Otherwise either the reflectance values of B or
preferably those of D have to be converted correspondingly.
[0030] The following definitions are used herein:
"Synthesized appearance" means an appearance which is generated
from the appearance attributes of both the source and reference
materials. It need not have identical size or format to either
reference or source materials. The synthesized appearance will look
more like the reference material than the source material. Suitable
appearance attributes include, for example, lightness, saturation,
texture, color, hue, gloss, specularity, distinctness of image,
haze, subsurface scattering, turbidity, translucency, surface
height variation and normal maps, etc.
[0031] "Reference material" means a material which has been
extensively measured to densely populate a data set of a plurality
of appearance attributes.
[0032] "Source material" means a material which has been measured
to sparsely populate a data set of one or more appearance
attributes. In some embodiments, the source and reference materials
are related (e.g. both may have one or more of the same appearance
attributes such as gloss, surface, color, etc.). In other
instances, they may differ (i.e. they may have no similar
appearance attributes).
[0033] "Physically plausible" means that the simulated material is
typically capable of being created in the physical, real world. The
term "Physically plausible" is used in contrast to that of
"physically feasible." A "physically feasible" appearance is one
that one can imagine constructing physically, but the real-world
construction of such materials may not be possible. The present
invention enables creation of physically plausible simulated
materials because the first and second data sets are physically
measured from tangible source and reference materials.
[0034] FIG. 1 shows one embodiment of the method according to the
invention. Data is acquired for both the source and reference
materials.
[0035] A sufficiently large surface area of a reference material
M.sub.R is measured using a complex reflectance scanner (11) to
provide a set of reflectance values for each pixel of the scanned
surface area under a large number of illumination directions (at
least 5, more preferably at least 10) and a large number of viewing
directions (at least 5, more preferably at least 10). The result is
a first set of data indicative of the values of measured appearance
attributes of the M.sub.R. This first set of data is also referred
to herein as the densely populated original BTF database B (12) for
the M.sub.R.
[0036] In some embodiments, the first set of data constitutes a
Bidirectional Texture Function (BTF), a Bi-Directional
Scattering-Surface Reflectance Distribution Function (BSSRDF),
Spatially Varying Bi-Directional Transmission Distribution Function
(SVBTDF), or a Spatially Varying Bi-Directional Reflectance
Distribution Function (SVBRDF).
[0037] A measuring spot of a source material M.sub.S is measured
using a simple reflectance scanner or color measuring device (13)
to provide sparse reflectance values D (14). The result is a second
set of data indicative of a value of at least one measured
appearance attribute of the M.sub.S. The appearance attribute of
the M.sub.S includes at least one, but not all, of the appearance
attributes measured on the M.sub.R. The second set of data is also
referred to herein as the "sparsely populated" data set. "Sparse"
means less than at least 50% the amount in the densely populated
BTF database B for the M.sub.R. In some embodiments, the number of
appearance attributes in the data collected from the M.sub.S is
less than 1% of the number of appearance attributes represented in
the BTF of the M.sub.R.
[0038] The data acquisition steps are known per se and can be
implemented by any suitable measurement equipment (including, for
example, a spectrophotometer). The materials can be illuminated
with electromagnetic (EM) radiation in the range of near IR, UV or
humanly detectable frequency spectra.
[0039] The BTF data B can be acquired at the same time or a
different time than the BTF data B' for the M.sub.S. The BTF data B
for the M.sub.R can be stored on the same computer or different
computer used to store the data from the M.sub.S.
[0040] Next, a third set of data indicative of the synthesized
appearance of the simulated material is determined based at least
in part on data from the second set of data associated with the
M.sub.S and at least in part on data from the first set of data
associated with the M.sub.R. In some embodiments, the original BTF
B of the M.sub.R is edited (modified) by transferring the sparse
reflectance values D of the M.sub.S into the BTF B (15). In this
editing step, a modified BTF B' is produced which is populated as
densely as B but has reflectance values that make B' resemble the
source material M.sub.S, i.e. the reflectance values of B' are as
similar as possible to reflectance values which would have been
obtained if the BTF of the source material had been actually
measured. The method of the present invention results in a third
set of data indicative of physically plausible appearance
attributes.
[0041] In some embodiments, the third set of data is determined
based at least in part from data from the first and second data as
well as data from a fourth set of data indicative of standardized
values of appearance attributes representative of a family of
generally similar physically tangible materials of which the
reference material or the source material is a member.
[0042] The third set of data can be corrected to increase its
physical plausibility. In some embodiments, an error value is used
to correct the data. In some embodiments, the error value consists
of (a) the difference between a parameter of a measured appearance
attribute of the source material and the same parameter of the
corresponding appearance attribute in the third set of data and (b)
a physical plausibility value based on the difference between at
least one, preferably at least two, parameter(s) of between at
least one, preferably at least two, measured appearance
attribute(s) of the reference material and the same parameter(s) of
the corresponding measured appearance attribute(s) in the third set
of data. In some embodiments, if the error value is greater than a
predetermined threshold, then the third set of data is revised
until the error value is less than the predetermined threshold
value.
[0043] The third set of data may optionally be processed to form an
image representative of the synthesized appearance of the simulated
material. In some embodiments, the image may be 3-dimensional. FIG.
1 shows the third set of data (e.g., the edited BTF B') (16) can be
fed as input data to a conventional rendering engine (17) and
visualized on a display (18). Rendering and displaying a BTF are
known in the art and are not subjects of the present invention per
se.
[0044] The present invention also provides a data set of values of
appearance attributes for a synthesized appearance of a simulated
material having physically plausible appearance attributes
generated by the method of the present invention.
[0045] The present invention also provides an image generated from
a data set of values of appearance attributes for a synthesized
appearance of a simulated material having physically plausible
appearance attributes generated by the method of the present
invention.
[0046] The present invention also provides a system for digitally
generating data indicative of a synthesized appearance of simulated
material having physically plausible appearance attributes, with
the synthesized appearance being based on a physically tangible
reference material and at least one value of a selected appearance
attribute of a physically tangible source material different from
the reference material.
[0047] In some embodiments, the system comprises (a) memory for
storing a first set of data indicative of the values of measured
appearance attributes of the reference material, with the measured
appearance attributes being measured at a plurality of locations on
the reference material and for a plurality of illumination
directions or a plurality of viewing directions relative to each of
the locations; (b) an instrument for measuring at least one
appearance attribute of the source material and generating a second
set of data indicative of a value of the measured appearance
attribute, wherein the appearance attribute of the source material
includes at least one, but not all, of the appearance attributes
being measured on the reference material; and (c) a computer
configured to receive the first and second sets of data and
configured to determine a third set of data indicative of the
synthesized appearance of the simulated material based at least in
part on data from the second set of data associated with the
physically tangible source material and at least in part on data
from the first set of data of measured attributes of the physically
tangible reference material different from that of the second set
of data.
[0048] In some embodiments, the system further includes a processor
configured to receive data from the third set of data and
configured either (i) to form an image representative of the
synthesized appearance of the simulated material based at least in
part on the data from the third set of data or (ii) to produce an
object having the synthesized appearance of the simulated material
based at least in part on the data from the third set of data.
[0049] In some embodiments, the image representative of the
synthesized appearance is two- or three-dimensional. In some
embodiments, the third set of data is used to print a physically
tangible object having the synthesized appearance of the simulated
material. In some embodiments, the printed object is two- or
three-dimensional. In some embodiments, third set of data to form a
haptic display representative of the synthesized appearance of the
simulated material. In some embodiments, at least a portion of the
memory for storing the first set of data is carried on the
computer.
[0050] In some embodiments, the computer and the instrument are
combined in a single integral device. In some embodiments, the
computer and the processor are combined in a single integral
device.
[0051] In some embodiments, data from the first and second sets of
data are transmitted via media selected from the group consisting
of a hardware connection, a wireless connection or a portable
memory device.
[0052] In some embodiments, the instrument constitutes a first
instrument comprising at least one source of EM radiation in the
range of near IR, UV or humanly detectable frequency spectra. In
some embodiments, the instrument source emits the full spectra of
EM radiation in the range of near IR, UV and humanly detectable
frequency spectra. In some embodiments, the instrument source emits
a selected spectrum of EM radiation from near IR, UV and visible EM
frequencies.
[0053] In some embodiments, the first instrument further comprises
at least one detector for measuring EM radiation reflected from or
transmitted through the source material when illuminated by the
source of EM radiation, and determining values of the appearance
attributes of the source material.
[0054] In some embodiments, the system further comprises a second
instrument for measuring appearance attributes of the physically
tangible reference material at a plurality of locations on the
reference material by illuminating each of the locations on the
reference material with EM radiation in the range of near IR, UV or
visible EM frequencies from a plurality of illumination directions
and measuring the EM radiation reflected from or transmitted
through the reference material from a plurality of viewing
directions, and determining values of the appearance attributes of
the reference material based on the reflected or transmitted EM
radiation for data of the first set of data.
[0055] The methods, images and systems of the present invention can
be used to bring variety, sophistication and accuracy to the
virtual world. Designers, 3D artists, material specifiers and
marketers can use the inventions described herein to visualize
their designs with unmatched realism, using digital information
measured from real materials. The present methodology enables the
characterization of the full appearance of materials used in
computer-aided design. Materials which can be simulated using the
present invention include, but are not limited to, flooring
materials (wood, concrete, vinyl, carpets, etc.), building
materials (siding, shingles, etc.), paints (especially automotive),
textiles (silks, hand-made fabrics, rugs, etc.), etc.
Example
[0056] Embodiments will now be further described with reference to
the following non-limiting Example. It should be understood that
this Example, while indicating embodiments, are given by way of
illustration only. From the above discussion and these Examples,
one skilled in the art can ascertain the essential characteristics
of this invention, and without departing from the spirit and scope
thereof, can make various changes and modifications of the
invention to adapt it to various usages and conditions. Thus,
various modifications of the invention in addition to those shown
and described herein will be apparent to those skilled in the art
from the foregoing description. Such modifications are also
intended to fall within the scope of the appended claims. All
documents referenced herein are incorporated by reference.
[0057] For an easier understanding, a simple practical example will
make clear the goal of the invention. Assume a designer wishes to
know what different designs of upholstery would look like in a real
car. He has a relatively large variety of individual seat cover
materials that are all made of the same textile fabric and,
therefore, have the same or at least a very similar surface
structure. The only difference between the individual materials may
consist in their color patterns. All materials may have colored
spots. One particular material may have white spots, another one
may have red spots, a third one may have green spots, and so on. To
visualize all these individual materials on a computer monitor
according to the present invention only one of the materials needs
to be densely scanned to produce a full reference BTF. The BTFs for
the remaining materials can then be generated on the fly from the
reference BTF by editing or modifying whereby the editing procedure
requires information on which pixels of the material to be
visualized are different and in what aspect (e.g. color) they are
different from the reference material. Accordingly, the first,
preparatory step of the editing procedure is to select those pixels
of the source material M.sub.S that are different from the
respective pixels of the reference material M.sub.R, or in other
words to select the pixels of which the corresponding reflectance
values are to be edited (shortly pixels to be edited).
[0058] Theoretically, the pixels to be edited could be specified
manually via their spatial coordinates. This, however, would be
rather tedious, particularly if a large number of pixels are
involved. Therefore, a software-assisted procedure is used as
outlined in FIG. 2.
[0059] Selecting a pixel means that it is assigned a non-zero
weight so that it is fully or at least partly considered in
subsequent calculations. Pixels with zero weight are not considered
in subsequent calculations. The weights build a selection mask.
[0060] In a first step of the pixel selection procedure one image
of the scanned surface of the reference material M.sub.R is
displayed on a computer monitor using a subset of data of the BTF B
(21). The user then has to mark in the image displayed a surface
region he wants to edit later, e.g. a spot of a certain color (22).
Marking can be performed manually or by any suitably designed
interactive routine known in the art.
[0061] Afterwards all similar surface regions can be located either
manually or by applying an algorithm (such as, e.g., the AppProp
algorithm described in An 2008, incorporated herein by reference in
its entirety) (23). The AppProp algorithm works on the basis of
self-similarities and calculates the weights so that all similar
regions on the whole material surface get a high weight equal to or
near one and all other regions receive a low weight equal to or
near zero.
[0062] The AppProp algorithm is based on the minimization of an
error function to propagate weights for selected pixels along
similar appearance, leading to an intuitive continuation of
selection. In some embodiments of the present invention, all
weights of a set of pixels below a certain threshold are set to
zero, i.e. only pixels with non-zero weights pertain to the set of
pixels to be edited and will be considered for further calculations
(24).
[0063] This optional modifying procedure of the inventive method
needs to know what the selected pixels to be edited should finally
look like. This information is provided by the sparse reflection
values D captured from the corresponding measuring spot of the
source material M.
[0064] The modifying procedure basically comprises an optimization
procedure that minimizes an error function E(B'). This error
function measures two different kinds of errors: a first part
measures the (appearance) difference between a simulated material
represented by the modified BTF B' and the sparse reflectance
values D of the source material and a second part measures the
(appearance) difference between the reference material as
represented by its BTF B and the simulated material represented by
the modified BTF 8'. The first error part makes the edited
(simulated) material look like the source material and the second
error part ensures minimal deviation of the edited (simulated)
material from the known reference material, therefore ensuring
physical plausibility.
[0065] To measure a sensible difference between B' and D, the first
part of the error function includes a simulated measurement of the
simulated material represented by B' with the simple reflectance
scanner used for measuring the sparse reflectance values D. For
this purpose a rendering of B' under the illumination and viewing
conditions of the simple reflectance scanner is computed with
standard methods from the area of computer graphics and the
difference of the result to D is computed. The simulated
measurement requires knowledge of the internal lighting and the
detectors inside of the simple reflectance scanner, which are
either known by design of the instrument or can be measured. a (
)
[0066] The difference between reference and source colors in the
first part can be measured using conventional color distance
measures such as e.g. CIE .DELTA.E* or simpler measures such as L1
errors.
[0067] The difference between reference and source measure
reflectance data in the first part of E(B') can be minimized,
making the respective part of the target material look like the
source material. The similarity of the edited BTF with the original
one can also be determined to ensure and therefore physical
plausibility of the result.
[0068] Weighting factors can be used to compensate for scale
differences between the two different parts of error measures. The
weighting w factors can be chosen by the user to put more emphasis
on either part of the error compensation.
[0069] As already mentioned above the modifying or editing
procedure is implemented by optimizing (i.e. minimizing the above
error function (E(B')) with B' as represented by its reflection
values as variables). In other words, B' or its reflection values
B' have to be modified in such a way that the error function E(B')
becomes minimal. This task is achieved by iteration starting with
the reflection values of B as zero-order approach (B'=B).
[0070] First it is explained how to minimize the error function
E(B') in the most general case, where little can be assumed about
the BTFs B and B'. Further below two special representations for B
and B' will be discussed that are suitable for certain material
classes, namely near-homogeneous, near-flat materials and
automotive paint materials. Such special representations are much
more compact and allow for easier optimization of error functions
specifically designed for them.
[0071] Many materials are too complex to be faithfully represented
by simple models so that no assumption about the internal
representation of their BTFs can be made. In order to minimize the
error function, according to a further important aspect of the
present invention, a heuristic approach based on BTF editing
operators defined in Kautz 2007 is used for modifying the BTF and
thereby minimizing the error function E(B').
[0072] The BTF editing operators of Kautz 2007 basically comprise
four operators which, when applied to a BTF, allow for modification
of the BTF with respect to gray scaling, color change (both
saturation and hue) and gloss or specularity change. Each operator
comprises one parameter only. By setting these parameters to higher
or lower values and applying the operators to a BTF, a desired
scaling, color, or specularity (gloss) change can be performed.
Using these operators the problem of minimizing the error function
E(B') is considerably reduced because only a few parameters have to
be estimated so as to minimize the error function.
[0073] The iterative minimizing procedure for minimizing the error
function E(B') is shown schematically in the flow diagram of FIG.
3.
[0074] After defining the pixels x to be edited, and after
computing and assigning weights w.sub.x to them as outlined in FIG.
2, an iterative algorithm is used to transfer the sparse
reflectance data D into B'. At the beginning, as mentioned already,
B' is initialized with the values of B (31). Then the error
function E(B') is calculated (32) and its value is compared with a
preset threshold value (33). The values resulting from the
simulated measurement of B', S.sub.S, are stored for later use. If
the error function value is below the threshold value or
convergence has been detected the iteration procedure is
terminated. Otherwise, parameters for the Kautz et al editing
operators are calculated (34) and with these parameters the Kautz
et al editing operators are applied to B' to produce a new BTF B''
(35). For the selected pixels x the values of this new BTF B' are
than mixed with the values of the original BTF B according to
B'''.sub.x=w.sub.xB'''.sub.x+(1-w.sub.x)B.sub.x wherein w.sub.x are
the weights assigned to the selected pixels x and B'''.sub.x are
the values of an intermediate modified B''' for the pixels x (36).
Then B' is reinitialized by setting B'=B''' (37). Afterwards the
iteration procedure starts over at box 32 so as to iteratively
modify B'.
[0075] In the following the (sub) procedure of estimating
parameters for the Kautz et al editing operators and of applying
these operators to the current B' (boxes 34 and 35 of FIG. 3) will
be explained in the context of the flow diagram of FIG. 4.
[0076] The (sub) procedure uses D.sub.S and the current states of
B' and S.sub.S as input data (41).
[0077] At first a scaling is applied to B' by multiplying all
reflectance values of B' with a scale factor F.sub.scale (42).
Since light transport is linear, scaling all reflectance values of
B' with the same scale factor is a physically plausible operation.
The scale factor F.sub.scale is determined by comparison of the
real measurements D.sub.S of the source material and the virtual
measurements S.sub.S of the edited (simulated) material. Then this
scale factor F.sub.scale is applied to the reflectance values of
all selected pixels of B'.
[0078] Next a color change in both saturation and hue is calculated
and a corresponding color transformation is applied to B' using the
Kautz et al color change operator (43). The color change operator
operates in HSV color space (hue, saturation, value) and can change
the hue and saturation of BTF pixels in a physically plausible way.
The color changes .DELTA.Hue and .DELTA.Sat in hue and saturation
are calculated by comparison of the real measurements Ds of the
source material and the virtual measurements S.sub.S of the edited
material.
[0079] Hue and saturation values are calculated from the
reflectance values D.sub.S and S.sub.S by known standard conversion
formulas.
[0080] .DELTA.Hue and .DELTA.Sat are additive changes to be applied
to the hue and saturation of B. The color change operator from
Kautz 2007 is run on all selected pixels of B' using .DELTA.Hue and
.DELTA.Sat as parameters.
[0081] If the simple reflectance scanner and thus the values D
support for estimating the materials specularity, a specularity
change from source to target material is calculated and applied to
B' (44). For this purpose the angular sharpening or angular
blurring operators from Kautz 2007 are used. The specularity change
sub-procedure (in 44) is shown in more detail in FIG. 5.
[0082] First the specularity of the source material is determined
from the sparse reflectance values D (51). For this an analytical
BRDF (Bidirectional Reflectance Distribution Function) model such
as the Cook-Torrance model described in Cook 1982 is fit to D by
minimizing an error function which is based on the analytical BRDF
model used and the set of parameter values for the model.
[0083] The error function is minimized using any standard
non-linear optimization algorithm like Levenberg-Marquardt.
[0084] Otherwise, the specularity of the simulated target material
is determined from the reflectance values in B' (53). For this the
same analytical BRDF (Bidirectional Reflectance Distribution
Function) model such as the Cook-Torrance model described in
Cook1982 is fit to B' by minimizing an error function based on the
analytical BRDF model used and the set of parameter values for the
model. Again, the error function is minimized using any standard
non-linear optimization algorithm like Levenberg-Marquardt.
[0085] In the next step (54) a ratio of the specularity parameters
is calculated.
[0086] In a final step (55), either the angular blurring or the
angular sharpening operator from Kautz 2007 is run on (applied to)
all selected pixels of B'.
Example 2
Near-Homogenous, Near-Flat Materials
[0087] The present invention is especially suitable for certain
classes of materials to be visualized; in particular the classes of
near-homogeneous, near-flat materials such as paint materials,
particularly automotive paint materials. In case of
near-homogeneous, near-flat materials, a much more efficient
representation of materials can be chosen, so that the parameters
of B and B' contain already more semantic information. One example
of this is the Spatially-Varying Bidirectional Reflectance
Distribution Function (SVBRDF), especially in combination with a
normal- or height-map to model the surface height variations.
Reducing a measured BTF to such a representation is well known and
not part of the present invention.
[0088] In a representation like the SVBRDF, the material is
described by a BRDF model and a local coordinate frame per pixel.
Since we assume that no spatial information is provided by the
simple reflectance scanner, we cannot change the surface structure
and therefore have to keep the local coordinate frames fixed.
[0089] To find new per-pixel parameter values for the BRDF
model(s), we again employ optimization of the energy function
E(B'). The difference to the generic case discussed above is, that
we have much less unknown parameters for the energy function and
that all parameters have a semantic, physical meaning. This makes
the evaluation of the first part of the energy function very
efficient. Furthermore, the second part--the physical plausibility
term--is now well defined, since simple bounds can be given on the
model parameters to ensure physical plausibility of the model
result.
Example 3
Automotive Paint
[0090] Car paint materials typically are homogeneous up to the
distortion by the sparkling due to certain pigments or flakes
incorporated in the paints. Since car paints are near-homogeneous
materials, the whole measured surface area of the reference
material can be included into the editing process by setting P to
the set of all pixels.
[0091] The BRDF of the surface is represented using the
Cook-Torrance BRDF model (Cook1982) and an angular-dependent color
table. The residual contains the local effects caused by the
flakes, e.g. sparkling, and is represented by a specially encoded
BTF.
[0092] This whole BTF is then edited in three steps: (1) new
parameters for the BRDF model are calculated by matching the
gray-scale reflectances with the given sparse reflectance values D;
(2) the entries of color table C are recomputed to match the colors
to the sparse measured reflectance values D; and (3) the colors in
all pixels of the flake BTF are changed to match the edit performed
on C and the angular distribution of the images is changed
according to the edit. Since no spatial information is given in D,
no sensible changes to the distribution of the flake effects within
one image of the flake BTF are possible.
[0093] More specifically in the first step, new values for the
diffuse and specular coefficients as well as the roughness
parameters of the Cook-Torrance model are determined using
optimization. For the second step, the original color table is
first warped in angular domain based on the average surface
roughness change. Since the bi-angular color change of metallic
paints depends on the alignment of the flake particles, and since
the roughness parameter reflects the degree of misalignment, this
operation corrects for the difference in flake alignment between
the source and target paint. Also in the second step, a color
operator is applied to the entries of the original color table to
match the colors from D. This color operator depends on the color
or spectral space in which the color table is defined. A typical
transformation has just a few parameters. An example would be a hue
and saturation change operator. In the third step, a modified flake
BTF is created by applying the same angular warping and color
transformation from the second step to all pixels of the flake
BTF.
[0094] When these three steps have been performed, the new car
paint already matches the reflectance samples in D. No further
iterations as in the general case explained further above are
necessary.
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