DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/16/2025 has been entered.
Response to Amendment
The office action is in response to Applicant’s amendment filed 12/16/2025 which has been entered and made of record. Claims 1, 4-8, 11-12 and 17-21 have been amended. No claim has been newly added. Claims 1, 3-9, 11, 12 and 16-22 are pending in the application.
Response to Arguments
Applicant’s arguments, filed 12/16/2025, with respect to the rejection(s) under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection under Yang in view of Gao and Kosmonaut has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Yang, SDF and Kosmonaut, as fully explained below.
Applicant argues Yang and Gao do not teach the newly amended limitation of independent claims.
Examiner agrees. Yang and Gao do not explicitly teach the target image specifying a shape of effect screen. However, upon further consideration, a new ground(s) of rejection is made in view of Yang, SDF and Kosmonaut.
Applicant argues Yang’s Figure 4 shows particles with same coordinate systems. Those skills in the art have no motivation to combine Yang with Kosmonaut.
Examiner respectfully disagrees.
First, Kosmonaut and Yang are both in the field of computer graphics, especially in the field of using signed distance field as texture to drive particles for animation, it is the same field as the amended claim 1;
Second, Kosmonaut teaches the use of world matrix to transform vertices (particles) to the signed distance field volume texture of a target shape on Page 5 and Page 13 as their implementation details, even though Yang’s Figure 4 does not show two different coordinate systems, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Kosmonaut with Yang.
Furthermore, “world coordinate system” is the only coordinate system defined in the claim language, the world coordinate system can be the same as the coordinate system used by the particle in the geometry shape.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3, 7-9, 11-12, 16 and 20-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over NPL Yang et al. (“A unified smoke control method based on signed distance field”), hereinafter as Yang, in view of NPL Signed distance function, (“Signed distance function -Wikipedia”), hereinafter as SDF, further in view of NPL Kosmonaut’s Blog (“Signed Distance Field Rendering Journey pt.1”), hereinafter as Kosmonaut.
Regarding claim 1, Yang teaches An effect processing method (Yang Page 775, Left column, first and third paragraph, “Path control algorithms enable smoke to follow given paths, and shape control methods make smoke form the target shapes……we propose a unified control algorithm to integrate shape control, path control, and mixed control into the same framework.”), comprising: obtaining …… comprising target motion attributes of at least two positions (Yang teaches the determination of signed distance field on Page 2, right column, 3.2 “Precomputation includes determination of the signed distance field”, further teaches the two positions on the smoke target shape, and generating boundary control force and shape control force based on a signed distance function as the target motion attributes. Yang Figure 1, Page 777, Right column, first paragraph, “As shown in Fig. 1, H and G are two points on the smoke boundary, and the red arrows indicate the shape feedback force on them. H is located out of the path influence area, and the shape feedback force on it points to the negative gradient direction of the signed distance function of the path influence area, which is orthogonal to the path.”), the target motion attribute of each position being used for forming particles into a target shape after motion (Yang Page 775, right column, second paragraph, “The contributions of our work include: (a) a unified control framework, which integrates path control, shape control, and mixed control of both, (b) two new control forces, i.e., the boundary force restricting the smoke to appointed regions and the shape control force making the smoke form target shapes, (c) an adaptive strategy for the divergence field adjustment used in the shape control,”); during motion process of at least two particles, adjusting the motion attribute of the particles at the current position (Yang teaches the position and velocity vector as the motion attribute of smoke particles. Page 779, Figure 4, “Dual identities of hybrid vortex particles. Red and green points all stand for hybrid vortex particles among which the red ones have the identity of Langevin particles, and the green ones possess the identity of vortex particles, and the dashed arrows show the trajectory of each hybrid vortex particle. (a) indicates the old locations and identity of the hybrid vortex particles, and (b) shows the new locations and identities of these hybrid vortex particles in the next moment.”) according to target motion attributes corresponding to the current position of the particles in the image (Yang teaches a simulation loop of using the boundary and shape control force, the boundary and shape control forces are precomputed and stored in the target image, particles move to new location in each iteration, in the next iteration, a new boundary and shape control forces are applied based on the current position of the particles in the target image. Page 779, left column, third paragraph, “1: Add the boundary control force; 2: Add the shape control force if needed; 3: Add the path control force if needed…… 7: Solve pressure equation to ensure fluid incompressibility; 8: Advect the hybrid vortex particles and update the vorticities of particles if needed”), the adjustment being used for reducing a difference between the motion attribute and the target motion attribute (Yang teaches smoke particle following fluid equation with boundary control force to stay in path and forming target shape, further teaches implicitly the velocity and position of smoke particle follow the direction of boundary control force, and getting closer to the target shape boundary. Page 777, Left column, third paragraph, “The signed distance function
φ
m
i
x
x
will be used to determine the boundary control force which pulls the smoke that is outside the path influence region and/or the target shape back”); and displaying the particles according to the adjusted motion attribute to obtain the effect screen, the particles being geometric display objects (Yang Page 781-782, right column, last paragraph, “For the proposed unified framework, the grid resolution is taken to be 64 X 64 X64, and the path radius is set to 0.04. At intervals of every 2 simulation steps, we positioned one hybrid vortex particle respectively at the start and end of the path. The obtained result is given in Fig. 12(a).”); wherein adjusting the motion attribute of the particles at the current position according to target motion attributes corresponding to the current position of the particles in the image comprises: ……and according to the target motion attribute ……, adjusting the motion attribute of the particles at the current position (Yang teaches a simulation loop of using the boundary and shape control force, the boundary and shape control forces are precomputed and stored in the target image, particles move to new location in each iteration, in the next iteration, a new boundary and shape control forces are applied, this implies the current position of the particles in the target image. Page 779, left column, third paragraph, “1: Add the boundary control force; 2: Add the shape control force if needed; 3: Add the path control force if needed…… 7: Solve pressure equation to ensure fluid incompressibility; 8: Advect the hybrid vortex particles and update the vorticities of particles if needed”).
Yang fails to teach an image, the image specifying a shape of an effect screen…… converting the current position of the particles in a world coordinate system to a second position of the particles in a geometry, wherein the target shape is located in the geometry; …… corresponding to the second position of the particles in the image……
SDF teaches an image, the image specifying a shape of an effect screen…… (SDF Page 3, top right figure, teaches using signed distance field as an image, representing a shape of a duck, “Signed distance fields stored as raster images can be used to represent shapes”, Yang teaches the precomputation of a signed distance field, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of SDF with the method of Yang to store the signed distance field as an image defining the target shape. Yang, Page 776, right column, last paragraph, “we will discuss below how to determine the signed distance field for each of the three controls. For shape control, we load CG models, ……and obtain the following signed distance function:
φ
s
h
a
p
e
x
=
-
d
t
x
i
f
x
i
s
i
n
s
i
d
e
t
h
e
m
o
d
e
l
d
t
x
o
t
h
e
r
w
i
s
e
where
d
t
(
x
)
expresses the shortest Euclidean distance from the spatial point to the triangle meshes constituting the target shape. Note that, the CG model must be a closed mesh.”).
Yang and SDF are in the same field of endeavor, namely computer graphics. SDF teaches signed distance field can be saved as an image of shape to improve rendering efficiency and result. Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of SDF with the method of Yang to improve rendering efficiency and result.
Yang in view of SDF fail to teach converting the current position of the particles in a world coordinate system to a second position of the particles in a geometry, wherein the target shape is located in the geometry; …… corresponding to the second position of the particles in the image……
Kosmonaut teaches converting the current position of the particles in a world coordinate system to a second position of the particles in a geometry (Kosmonaut teaches a matrix transformation, the second position of the particle is the location of particle in the target shape geometry after transformation. Page 5, fifth paragraph, “In a first step I extracted all the vertices from our geometry and transformed them with the sponza’s world matrix to match their actual location.” And Page 13, third paragraph, “we just transform these 6 edge points with the model’s world matrix to make it align to the mesh’s rotation, size and position.”), wherein the target shape is located in the geometry (Kosmonaut teaches a bounding box or bounding sphere of the meshes, Kosmonaut, page 13, second paragraph, “The first thing I wanted to do is to finally make the volume texture directly dependent on the entity’s rotation, size etc. to efficiently use space. So the first thing I had to do was to create bounding boxes for the mesh. Per default bounding spheres are generated when importing meshes to the engine, but bounding boxes are pretty easy to do, too – find min/max values for all vertices in a mesh and store these 2 coordinates.”, Yang Page 781, right column, third paragraph, “ Using a dragon model as the target shape and taking the grid resolution to be 128 X 128 X 128”) …… corresponding to the second position of the particles in the image ……(Kosmonaut teaches a matrix transformation, the second position of the particle is the location of particle in the target shape after transformation, further teaches a signed distance field for the mesh. Yang in view of SDF further teaches the boundary control force and shape control force based on signed distance field as the target image, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Kosmonaut with the method of Yang and SDF).
Yang, SDF and Kosmonaut are in the same field of endeavor, namely computer graphics. Kosmonaut teaches a matrix transformation to convert particles to geometry coordinate and representing the signed distance field as volume textures to improve rendering efficiency and result (Kosmonaut page 3, paragraph 3, “Then during runtime you can sample the current location in this volume texture and have the mini‐mum distance at the cost of a texture read!”). Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Kosmonaut with the method of Yang in view of SDF to have a better rendering result.
Regarding claim 3, Yang in view of SDF and Kosmonaut teach the method of claim 1, The method of claim 1, wherein converting the current position of the particles in the world coordinate system to the second position of the particles in the geometry comprises: and further teach converting the current position of the particles in the world coordinate system to the second position of the particles in the geometry according to attributes of the geometry (Kosmonaut teaches a transformation of vertices based on model matrix. It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Kosmonaut with the smoke particle of Yang. Kosmonaut, page 5, fifth paragraph, “In a first step I extracted all the vertices from our geometry and transformed them with the sponza’s world matrix to match their actual location.”), wherein the attributes of the geometry comprise at least one of the following: a size of the geometry, a center position of the geometry, or an angle of the geometry relative to the world coordinate system (Kosmonaut teaches the model matrix related to the size of the mesh, rotation(angle) and position of the geometry model. Kosmonaut, Page 13, third paragraph, “we just transform these 6 edge points with the model’s world matrix to make it align to the mesh’s rotation, size and position.”).
Yang, SDF and Kosmonaut are in the same field of endeavor, namely computer graphics. Kosmonaut teaches a matrix transformation to convert particles to geometry coordinate and representing the signed distance field as volume textures to improve rendering efficiency and result (Kosmonaut page 3, paragraph 3, “Then during runtime you can sample the current location in this volume texture and have the mini‐mum distance at the cost of a texture read!”). Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Kosmonaut with the method of Yang in view of SDF to have a better rendering result.
Regarding claim 7, Yang in view of SDF and Kosmonaut teach the method of claim 1, The method of claim 1, and further teach wherein obtaining the image comprises: obtaining a target model corresponding to the target shape (Kosmonaut Page 5-6, last figure, “In a first step I extracted all the vertices from our geometry and transformed them with the sponza’s world matrix to match their actual location …… Before tackling large objects I’ve tried with this simple transparent sphere.”), the target model comprising at least two points (Kosmonaut Page 5, “then generated a list of triangles, based on the information from index and vertex buffer. I created normals based on clockwise arrangement of the triangle’s edges to note where outside and inside is”); and converting a position of each point in the target model to the target motion attribute of the position in the image (Kosmonaut teaches generating the SDF volume texture for a mesh. Yang in view of SDF teaches the boundary control force and shape control force based on signed distance field as the target image, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Kosmonaut with the method of Yang and SDF. Page 5, “For each sample point Go through all triangles and determine the minimum distance. I used the “Triangle Unsigned” function from Mr. Quilez. Determine the closest triangle and it’s distance (squared). Compute if we are “inside” or “outside” by calculating the dot product of the distance vector to the normal. Adjust the sign based on this (negative means inside). If we found the minimum value actually take the square root to get the actual euclidian distance ( sqrt(abs(value)) * sign(value) )”).
Yang, SDF and Kosmonaut are in the same field of endeavor, namely computer graphics. Kosmonaut teaches a matrix transformation to convert particles to geometry coordinate and representing the signed distance field as volume textures to improve rendering efficiency and result (Kosmonaut page 3, paragraph 3, “Then during runtime you can sample the current location in this volume texture and have the mini‐mum distance at the cost of a texture read!”). Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Kosmonaut with the method of Yang in view of SDF to have a better rendering result.
Regarding claim 8, Yang in view of SDF and Kosmonaut teach the method of claim 7, The method of claim 7, and further teach wherein the target motion attribute, the position in the image, and the motion attribute of the particles are all three-dimensional vectors (Yang teaches a method to control smoke particles in a 3D model, the position and the velocity vector of the smoke particles are all 3D vectors; the boundary control force and shape control force based on SDF are all 3D vectors. First page, right column, first paragraph, “Our control algorithm translates 3D surface geometry models and space curves representing paths into a signed distance field. Through the signed distance field, we provide two novel control forces: boundary control force and shape control force based on medial axis point clouds. The boundary control force restricts the smoke to the appointed regions, and the shape control force is used to drive the smoke into given shapes.”), and wherein the target model is a three-dimensional model (Yang Page 781, right column, third paragraph, “ Using a dragon model as the target shape and taking the grid resolution to be 128 X 128 X 128”).
Regarding claim 9, Yang in view of SDF and Kosmonaut teach the method of claim 7, The method of claim 7, and further teach wherein the target shape is an inscribed shape of the geometry (Yang teaches a cuboid grid size for each target shape, Fig. 12 is based on a cuboid size of 64X64X64, Fig. 13 is based on a cuboid of 128x128x128, Page 776, Table 1).
Regarding claim 11, it recites similar limitations of claim 1 but in an electronic device form. The rationale of claim 1 rejection is applied to reject claim 11. In addition, Yang in view of SDF and Kosmonaut further teach An electronic device comprising: at least one processor and a memory, wherein the memory stores computer executable instructions, the at least one processor executes the computer executable instructions stored in the memory, causing the electronic device to (an electronic device with processors and memory are inherent features used by the system and method taught by Yang in view of SDF and Kosmonaut).
Regarding claim 12, it recites similar limitations of claim 1 but in a non-transitory computer-readable storage medium form. The rationale of claim 1 rejection is applied to reject claim 12. In addition, Yang in view of SDF and Kosmonaut teach A non-transitory computer-readable storage medium, wherein the computer-readable storage medium stores computer executable instructions, and when a processor executes the computer executable instructions, causing a computing device to (the non-transitory computer-readable storage medium with instructions that can be executed by a processor, are inherent features used by the system and method taught by Yang in view of SDF and Kosmonaut).
Regarding claim 16, claim 16 has similar limitations as claim 3, therefore it is rejected under the same rationale as claim 3.
Regarding claim 20, claim 20 has similar limitations as claim 7, therefore it is rejected under the same rationale as claim 7.
Regarding claim 21, claim 21 has similar limitations as claim 8, therefore it is rejected under the same rationale as claim 8.
Regarding claim 22, claim 22 has similar limitations as claim 9, therefore it is rejected under the same rationale as claim 9.
Claim(s) 4 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over NPL Yang et al. (“A unified smoke control method based on signed distance field”), hereinafter as Yang, in view of NPL Signed distance function, (“Signed distance function -Wikipedia”), hereinafter as SDF, and further in view of NPL Kosmonaut’s Blog (“Signed Distance Field Rendering Journey pt.1”), hereinafter as Kosmonaut, and NPL Wikipedia1 (“Linear interpolation”), hereinafter as LinearInterpolation.
Regarding claim 4, Yang in view of SDF and Kosmonaut teach the method of claim 1, The method of claim 1, further teach …… and wherein according to the target motion attribute corresponding to the second position of the particles in the image, adjusting the motion attribute of the particles at the current position comprises: ……and according to target motion attribute corresponding to …… of each particle in the image, adjusting the motion attribute of the particles at the current position (Yang teaches a simulation loop of using the boundary and shape control force, the boundary and shape control forces are precomputed and stored in the target image, particles move to new location in each iteration, in the next iteration, a new boundary and shape control forces are applied, this implies the current position of the particles in the target image. Page 779, left column, third paragraph, “1: Add the boundary control force; 2: Add the shape control force if needed; 3: Add the path control force if needed…… 7: Solve pressure equation to ensure fluid incompressibility; 8: Advect the hybrid vortex particles and update the vorticities of particles if needed”).
Yang in view of SDF and Kosmonaut fail to teach wherein each position in the image is a normalized position …… normalizing the second position to obtain a third position, wherein each coordinate of the third position is greater than or equal to 0 and less than or equal to 1…… the third position.
LinearInterpolation teaches wherein each position in the image is a normalized position (LinearInterpolation teaches a normalized distance for point x as the normalized position. Page 2, second paragraph, “Thus, the weights are
x
-
x
0
x
1
-
x
0
and
x
1
-
x
x
1
-
x
0
, which are normalized distances between the unknown point and each of the end points.)…… normalizing the second position to obtain a third position, wherein each coordinate of the third position is greater than or equal to 0 and less than or equal to 1 (LinearInterpolation teaches unknown point (x, y) as the second position between points (
x
0
,
y
0
)
and (
x
1
,
y
1
)
, further teaches determining normalized distance,
x
-
x
0
x
1
-
x
0
,
y
-
y
0
y
1
-
y
0
, both weights are greater or equal to zero, less than or equal to 1. Page 1, First Figure and Page 2, second paragraph, “these sum to 1”)…… the third position (LinearInterpolation teaches
x
-
x
0
x
1
-
x
0
,
y
-
y
0
y
1
-
y
0
as the third position of the particle).
Yang, SDF, Kosmonaut and LinearInterpolation are in the same field of endeavor, namely computer graphics. LinearInterpolation teaches using normalized distance to represent the location of in between particles to improve computation result. Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of LinearInterpolation with the method of Yang, SDF and Kosmonaut to have a better computation result.
Regarding claim 17, claim 17 has similar limitations as claim 4, therefore it is rejected under the same rationale as claim 4.
Claim(s) 5 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over NPL Yang et al. (“A unified smoke control method based on signed distance field”), hereinafter as Yang, in view of NPL Signed distance function, (“Signed distance function -Wikipedia”), hereinafter as SDF, further in view of NPL Kosmonaut’s Blog (“Signed Distance Field Rendering Journey pt.1”), hereinafter as Kosmonaut, and NPL Game Development Stack Exchange (“mathematics - How do I linearly interpolate between two vectors?”), hereinafter as GD1.
Regarding claim 5, Yang in view of SDF and Kosmonaut teach the method of claim 1, The method of claim 1,wherein adjusting the motion attribute of the particles at the current position according to target motion attributes corresponding to the current position of the particles in the image comprises: but fails to teach performing a weighted summation to the target motion attributes corresponding to the current position of the particles in the image and the motion attributes of the particles at the current position, to obtain adjusted motion attributes, wherein a weighting coefficient of the target motion attributes and a weighting coefficient of the motion attributes are both greater than 0, and a sum of the weighting coefficient of the target motion attributes and the weighting coefficient of the motion attributes is 1. GD1 teaches performing a weighted summation to the target motion attributes corresponding to the current position of the particles in the image and the motion attributes of the particles at the current position, to obtain adjusted motion attributes (GD1 teaches a weighted sum between two vectors. Yang in view of SDF teaches vectors of particle velocity, vectors of boundary control force and shape control force. It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of GD1 with the two vectors of Yang. Page 2, last figure, “AB is the red vector from A to B. Say P is 25% of the way from A to B. The basic way to get to P from the origin is
3
4
A
+
1
4
B
. So 3/4 A and 1/4 B. Another way to find that is saying you want a vector 75% "close" to A, and 25% "close" to B. (A vector that is 100% "close" to A is just the A vector.)), wherein a weighting coefficient of the target motion attributes and a weighting coefficient of the motion attributes are both greater than 0, and a sum of the weighting coefficient of the target motion attributes and the weighting coefficient of the motion attributes is 1 (GD1 teaches the two weighting coefficient t and (1-t), t represents how close the point p is to the vector location of A. The sum of the two weights is 1, and each of them are greater than 0, Page 3, first equation, “A*t+(1-t)*B”).
Yang, SDF, Kosmonaut and GD1 are in the same field of endeavor, namely computer graphics. GD1 teaches using weighted sum to interpolate between two vectors to get better result. Yang teaches path control force, boundary control force and shape control forces as vectors in 3D grid. Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of GD1 with the method of Yang in view of SDF and Kosmonaut to have a better rendering result.
Regarding claim 18, claim 18 has similar limitations as claim 5, therefore it is rejected under the same rationale as claim 5.
Claim(s) 6 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over NPL Yang et al. (“A unified smoke control method based on signed distance field”), hereinafter as Yang, in view of NPL Signed distance function, (“Signed distance function -Wikipedia”), hereinafter as SDF, further in view of NPL Kosmonaut’s Blog (“Signed Distance Field Rendering Journey pt.1”), hereinafter as Kosmonaut, and NPL Joy (“Numerical Methods for Particle Tracing in Vector Fields”), hereinafter as Joy.
Regarding claim 6, Yang in view of SDF and Kosmonaut teach the method of claim 1, The method of claim1, but fail to teach wherein after adjusting the motion attribute of the particles at the current position according to target motion attributes corresponding to the current position of the particles in the image, the method further comprises: updating the current position of the particles according to the adjusted motion attribute, and entering a step of adjusting the motion attribute of the particles at the current position according to the target motion attribute corresponding to the current position of the particles in the image. Joy teaches wherein after adjusting the motion attribute of the particles at the current position according to target motion attributes corresponding to the current position of the particles in the image (Joy Page 1, Last paragraph and Page 2, First Figure and paragraph, “Consider a point p inside one cell of our rectilinear volume. This cell has four corner points p0;0, p1;0, p0;1, and p1;1, each of which has an associated vector. ~v0;0, ~v1;0, ~v0;1, and ~v1;1, respectively. We can calculate the vector at p by using the values u and v and bilinearly interpolating the vectors at the corners. ”), the method further comprises: updating the current position of the particles according to the adjusted motion attribute (Joy Page 3, First Figure and first paragraph, “Calculate
v
i
→
by bilinearly interpolating the vectors at the corners of the cell (Note: You first have to determine the cell in which pi lies.), and Calculate pi+1 = pi + Δt
v
i
→
”), and entering a step of adjusting the motion attribute of the particles at the current position according to the target motion attribute corresponding to the current position of the particles in the image (Joy Page 3, First Figure and first paragraph, “This figure suggests the following strategy: (1) Select a ”step size” Δt; (2) Starting with the point pi , where p0 = pi”).
Yang, SDF, Kosmonaut and Joy are in the same field of endeavor, namely computer graphics. Joy teaches tracing the path of particles in a three-dimensional vector fields to improve rendering result. Yang teaches the boundary control force and shape control force as 3D vectors. Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Joy with the method of Yang in view of SDF and Kosmonaut to have a better rendering result.
Regarding claim 19, claim 19 has similar limitations as claim 6, therefore it is rejected under the same rationale as claim 6.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to XIAOMING WEI whose telephone number is (571)272-3831. The examiner can normally be reached M-F 8:00-5:00.
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/XIAOMING WEI/ Examiner, Art Unit 2611
/KEE M TUNG/ Supervisory Patent Examiner, Art Unit 2611