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 .
Response to Amendment
This action is in response to the amendment filed 06/22/2026. Claims 1-20 remain pending in the application. Applicant’s amendments overcome all objections and the 35 U.S.C. 112 rejection but fail to overcome the 35 U.S.C. 101 and 35 U.S.C. 103 rejections as set forth in the Non-Final Office Action dated 02/20/2026
Response to Arguments
Applicant's arguments filed 06/22/2026 regarding the 101 and 103 rejections have been fully considered but they are not persuasive.
Applicant argues the claimed operations are integrated into a practical application of computer generation and rendering linework that corresponds to 3-D scene data and camera perspective.
Examiner replies see MPEP 2106.05, the claimed operations are well-understood, routine, conventional abstract ideas applied to a processor to implement the method. This does not amount to an improvement to a technology but an application of existing technology. Therefore, the application does not amount to significantly more than the abstract idea. Applicant's arguments have been fully considered but they are not persuasive.
Applicant argues amended claims cannot be characterized as abstract ideas, i.e. mental processes or pen-and-paper activity. The amended claims recite technical computer-graphics operations performed on digital data structures, not steps practically performed in the human mind.
Examiner replies see MPEP 2106.04, As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer"). Therefore, a limitation that recites a mental process but is performed by a processor, may still be categorized as an abstract idea. Applicant's arguments have been fully considered but they are not persuasive.
Applicant argues the amended claims integrate any alleged mathematical or analytical concepts into a practical application.
Examiner replies see MPEP § 2106.04(d), while the claim does recite additional elements, the additional elements of the claim that do not fall under an abstract idea recite a generic computer implemented method using data gathering executed by a processor. By adding a processor to the limitations that recite mathematical and analytical concepts, the amended claims fail to integrate the mathematical and analytical concepts into a practical application because an abstract idea with a processor is still and abstract idea. Applicant's arguments have been fully considered but they are not persuasive.
Applicant argues Ferrari de Goes does not teach the claimed camera-location-based linework pipeline. Ferrari de Goes is materially different than the claimed invention and does not teach the amended claim language.
Examiner replies Applicant's arguments have been fully considered but they are not persuasive. In response to applicant's argument that the disclosure of Ferrari de Goes is materially different from the claimed invention, the fact that the inventor has recognized another advantage which would flow naturally from following the suggestion of the prior art cannot be the basis for patentability when the differences would otherwise be obvious. See Ex parte Obiaya, 227 USPQ 58, 60 (Bd. Pat. App. & Inter. 1985). Further, one cannot show non-obviousness by attacking references individually where the rejection is made based on the combination of references.
Applicant argues Seymour does not cure the deficiencies of Ferrari de Goes. It is insufficient to state that Seymour implies camera locations are know because training data includes different angles because different views or angles do not teach the claimed use of camera locations included in scene data to calculate camera angle relative to a 3-D mesh and to drive parsing and analysis of potential line locations. Further, an artist nudge after a machine learning prediction fails to teach secondary lines on top of generates base curves based on user input.
Examiner replies Applicant's arguments have been fully considered but they are not persuasive. See MPEP § 2111.01, claims must be given their broadest reasonable interpretation in light of the specification. Within the broadest reasonable interpretation of the claim language: “receiving, by a processor, scene data including locations of cameras capturing scene data”, Seymour does satisfy the limitation. Seymour, [Image 7], discloses training data, which is received scene data, where camera angle is a feature of the scene data. Under broadest reasonable interpretation, the camera angle of a camera capturing scene data is a location of a camera as it is the relative orientation of a camera in relation to its subject. Further, Bickerstaff is relied upon for the claimed intended use of the camera’s location data and Ferrari de Goes is relied upon for the claimed intended use for the parsing and analysis. Additionally, within broadest reasonable interpretation of the claim language: “generating, by a processor, secondary lines on top of the base curves based on a user input to generate stylized curves”, Seymour satisfies the limitation with describing the nudging technique by artists. Seymour, [Image 5], teaches the nudging technique adjusts/corrects the drawing, generating secondary lines, on top of base curves, the machine learning prediction, based on user input, where the user input would be the artist’s nudges.
Applicant argues Bickerstaff is redirected to re-projection and occlusion recovery, not linework generation.
Examiner replies Applicant's arguments have been fully considered but they are not persuasive. In response to applicant's argument that Bickerstaff is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, Bickerstaff is relied on for the mathematical operation of calculating a camera angle using the locations of cameras, relative to an object, Bickerstaff, on pg. 13 lines 8-30, a process that can calculate a new camera angle using at least two cameras. Because Bickerstaff discloses the limitation, it would have been obvious to apply this process to output a predictable result, therefore making the reference reasonably pertinent to the particular problem with which the inventor was concerned.
Applicant argues The proposed combination would require hindsight reconstruction
Examiner replies Applicant's arguments have been fully considered but they are not persuasive. In this case, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Ferrari de Goes in view of Seymour and Bickerstaff, because the combination teaches parts of the whole computer-graphics process. It would have been obvious to apply the teachings of both Seymour and Bickerstaff to then create the instant invention. In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
Regarding arguments to Claims 2-9, 11-16, and 18-20, they directly/indirectly depend on independent Claims 1, 10, and 17 respectively. Applicant does not argue anything other than Claims 1, 10, and 17. The limitations in those claims, in conjunction with combination, was previously established as explained.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 6 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 6 recites “The method of Claim 1, further comprising rendering the stylized curves”, however, the amendment to Claim 1 has added the limitation: “…; and rendering, by the processor, the stylized curves as linework corresponding to scene data.”. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 101
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 1 is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to the judicial exception.
For Claim 1:
Step 1: The claim(s) as a whole fall within one or more statutory categories
Claim 1 is directed to a computer implemented method, which is a process.
Step 2A, Prong 1: Is/Are the claim(s) directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea)?
Claim 1 is directed to an abstract idea, see rationale below.
Claim 1 recites:
calculating, by the processor, 3-D mesh of the scene data; → Mathematical concepts because calculating a mesh using data involves computational geometry
calculating, by the processor, camera angle relative to the 3-D mesh using the locations of the cameras; → Mathematical concepts because calculating a camera angle relative to an object involves trigonometry and vector math
parsing, by the processor, the scene data and analyzing potential line locations based on the camera angle relative to the 3-D mesh; → Mental process because a person can mentally analyze a scene and visualize how something could be drawn (potential line locations) based on a camera angle relative to the 3-D mesh (a field of view)
generating, by the processor, base curves for the potential line locations; → Mental process that can be performed by a human using a pen and paper; or mathematical concepts because a person can draw on paper base curves at potential line locations
generating, by the processor, secondary lines on top of the base curves based on a user input to generate stylized curves. → Mental process that can be performed by a human using a pen and paper; or mathematical concepts because a person can draw on paper secondary lines on top of base curves, based on their own input (their drawing), therefore generating stylized curves
and rendering, by the processor, the stylized curves as linework corresponding to the scene data → Mental process that can be performed by a human using a pen and paper because a person can draw line work on paper corresponding to a scene they have analyzed.
The claim recites a "processor" to perform these abstract ideas. However, the processor is recited in such high level without any details, so it can only be considered as a generic computer component. According to MPEP 2106.04(a)(2) III.C, a claim that requires a computer may still recite a mental process. Here, the mental processes are merely performed using a processor, as part of a generic computer, in a computer environment, or as a tool. Therefore, they are still mental processes.
Step 2A, Prong 2: Do they claim(s) recite additional elements that integrate the exception into a practical application of the exception?
No, the additional elements do not integrate the exception into a practical application of the exception.
receiving, by a processor, scene data including locations of cameras capturing the scene data; → Data gathering
…, by a/the processor, … → applying a generic computer component
Although Claim 1 recites “receiving, by a processor, scene data including locations of cameras capturing the scene data;” and “by a processor”, the claim does not amount to significantly more than a generic process to perform the mental processes with or without pen and paper and mathematical processes.
Therefore, the judicial exception is not integrated into a practical application because the additional elements recited in the claim fail to amount to significantly more than a generic computer process to perform the abstract idea.
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception? I.e. Are there any additional elements (features/limitations/steps) recited in the claim beyond the abstract idea?
The claims do not include additional elements that amount to significantly more than the abstract idea. The step “receiving, by a processor, scene data including locations of cameras capturing the scene data;” is a data gathering, “calculating, by the processor, 3-D mesh of the scene data; calculating, by the processor, camera angle relative to the 3-D mesh using the locations of the cameras;” are mathematical concepts, “parsing, by the processor, the scene data and analyzing potential line locations based on the camera angle relative to the 3-D mesh; generating, by the processor, base curves for the potential line locations; generating, by the processor, secondary lines on top of the base curves based on a user input to generate stylized curves; and rendering, by the processor, the stylized curves as linework corresponding to the scene data” are categorized as mental processes, and “…, by a processor, …” is a general application of a computer element. An abstract idea with a processor is still an abstract idea.
Therefore, Claim 1 is not eligible subject matter under 35 U.S.C. 101.
Claims 10 and 17 are similar in scope to Claim 1, and are directed to an abstract idea. Claim 10 recites a system using the process of Claim 10, the claim does not amount to significantly more than a generic system with a memory, processor, and data gathering to perform the abstract ideas in the claim. Claim 17 recites a non-transitory computer-readable storage medium storing a computer program comprising executable instructions using the method of Claim 1, the claim does not amount to significantly more than a generic non-transitory computer-readable storage medium storing a computer program to perform the abstract ideas in the claim.
Claims 2 and 3 are directed to further limit generating the stylized curves of Claim 1. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception of mental process that could be performed a human using a pen and paper.
Claims 11, 12, and 18 are similar in scope to Claims 2 and 3, and are directed to an abstract idea.
Claim 4 is supplemental to the method of Claim 1 and is directed to determining whether a redraw rate corresponds to character’s movement. This step is part of a mental process that could be performed in the human mind, and therefore does not amount to significantly more than the abstract idea.
Claim 5 is directed to limit Claim 4 and does not include additional elements that are sufficient to amount to significantly more than the judicial exception of mental process that could be performed a human using a pen and paper.
Claims 13 and 19 are similar in scope to Claims 4 and 5, and are directed to an abstract idea.
Claim 6 is supplemental to the method of Claim 1 and is directed to rendering the stylized curves. This step is part of a mental that could be performed a human using a pen and paper, and therefore does not amount to significantly more than the abstract idea.
Claim 7 is supplemental to the method of Claim 1 and is directed to adding hand-drawn lines to the stylized curves. This step is part of a mental that could be performed a human using a pen and paper, and therefore does not amount to significantly more than the abstract idea.
Claim 14 is similar in scope to Claim 7, and is directed to an abstract idea.
Claim 8 is directed to further limit Claim 7, and does not include additional elements that are sufficient to amount to significantly more than the judicial exception of mental process that could be performed a human using a pen and paper.
Claim 15 is similar in scope to Claim 8, and is directed to an abstract idea.
Claim 9 is directed to further limit Claim 8 and does not include additional elements that are sufficient to amount to significantly more than the judicial exception of mental process that could be performed a human using a pen and paper.
Claim 16 is similar in scope to Claim 9, and is directed to an abstract idea.
Claim 20 is in similar scope to Claims 7-9, and is directed to an abstract idea.
Claim Rejections - 35 USC § 103
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.
Claims 1-2, 6-7, 10-11, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Ferrari de Goes et al. (US 2023/0125292 A1), hereinafter referenced as Ferrari de Goes in view of Seymour (“Ink Lines and Machine Learning”, 2019), hereinafter referenced as Seymour in further view of Bickerstaff et al. (GB 2582393 A), hereinafter referenced as Bickerstaff.
Regarding Claim 1, Ferrari de Goes discloses a computer implemented method of generating lineworks (Ferrari de Goes, [0006], describes a method for rendering volumetric objects with contours <where rendered objects with contours is interpreted as lineworks>), comprising:
receiving, by a processor, scene data (Ferrari de Goes, [0034], describes receiving an object model <where object model reads on scene data> as input; [0044-0045], discloses the method implemented by a computer system or in a processor);
calculating, by the processor, 3-D mesh of the scene data (Ferrari de Goes, [0046], describes an object modeling system that can generate a polygonal mesh defining a surface of an object <where object reads on scene data>; [0044-0045], discloses the method implemented by a computer system or in a processor);
parsing, by the processor, the scene data and analyzing potential line locations based on the camera angle relative to the 3-D mesh (Ferrari de Goes, [0007], teaches identifying one or more points of contour lines; Ferrari de Goes, [0008], teaches the contour lines are generated based on a location of the virtual camera relative to the object; [0044-0045], discloses the method implemented by a computer system or in a processor);
generating, by the processor, base curves for the potential line locations (Ferrari de Goes, [0008], teaches generated contour lines <where contour lines reads on base curves>; Ferrari de Goes, [Figs. 6A and 6B]; [0044-0045], discloses the method implemented by a computer system or in a processor);
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generating, by the processor, secondary lines on top of the base curves (Ferrari de Goes, [0088], describes modifying already visible lines and marking points as visible that weren’t already visible based on spotlights <where a combination of marked visible points that weren’t already visible makes up a secondary line>; Ferrari de Goes , [Fig. 8], reference characters 802 and 810 read as secondary lines which create curves that are stylized; [0044-0045], discloses the method implemented by a computer system or in a processor);
and rendering, by the processor, the stylized curves as linework corresponding the scene data (Ferrari de Goes: [Fig. 8], shows rendered stylized curves as a contour drawing <linework> based on the input object model <scene data>; [0044-0045], discloses the method implemented by a computer system or in a processor).
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the 3-D mesh (Ferrari de Goes: [0046], discloses a polygonal mesh defining a surface of an object)
Ferrari de Goes fails to disclose
scene data including locations of cameras capturing scene data
calculating, by the processor, camera angle relative to the 3-D mesh using the locations of the cameras;
However, Seymour discloses a method of generating lineworks (Seymour, [Image 2-Image 8] recites SPI using ML to generate linework, solving their problem, this series of operations recites a process) comprising: parsing the scene data and analyzing potential line locations based on the camera angle relative to the 3-D mesh (Seymour, [Image 7], describes GradientBoostingRegressor analyzing potential line locations based on the training data which includes both the mesh and camera angle); generating base curves for the potential line locations (Seymour, [Image 6], Figure described as “Learning spaces”); and further teaches
scene data including locations of cameras capturing the scene data (Seymour: [Image 7], discloses using an arbitrary turntable animation from different angles for training data, where features of this training data include camera angle, this not only implies camera locations are known but the camera angle of a camera capturing scene data is a location of a camera as it is the relative orientation of a camera in relation to its subject)
and generating secondary lines on top of the base curves based on a user input to generate stylized curves (Seymour: [Images 4-5], describes artists using a “nudging” technique <based on user input> involving a digital nudging brush to make adjustments and correct the drawing after the machine learning prediction <base curve generation>, where the added nudges generate the stylized curves)
It would have been obvious for one having ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method disclosed by Ferrari de Goes by including camera locations in scene data and basing secondary lines on top of the base curves based on user input as taught by Seymour. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated to make these modifications to efficiently render scenes. By including camera locations in the scene data, the regressor could predict the best based curves on perspective of the audience. By using the nudging technique from the manual mode on the predicted output of the machine learning mode, artists could quickly and easily adjust their drawings.
The combination of Ferrari de Goes and Seymour fail to disclose
calculating, by the processor, camera angle relative to the 3-D mesh using the locations of the cameras;
However, Bickerstaff teaches scene data including locations of cameras capturing the scene data (Bickerstaff: [Fig. 6], illustrates obtaining a camera pose <locations of camera for each image captured by a different camera <interpreted as collecting scene data, see below)
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and Bickerstaff further discloses
calculating, by the processor, camera angle relative to the contents of the scene using the locations of the cameras (Bickerstaff: [pg. 13, lns 8-30], discloses a method that can be applied to calculating, a new camera angle using the locations of at least two cameras; [pg. 22, lns 20-29], discloses the method being implemented by a processor; see [Fig. 6]);
It would have been obvious for one having ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method disclosed by Ferrari de Goes and Seymour by calculating camera angle relative to the 3-D mesh using the locations of the cameras as taught by Bickerstaff. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated to make these modifications to create more realistic 3D models with accurate depth and detailed shading. Multiple perspectives would also improve structural detail and reduce deformations.
Regarding Claim 10, it recites limitations similar in scope to Claim 1, but as a system. As shown in the rejection, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the limitations of Claim 1. Additionally, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose
a system for generating lineworks (Ferrari de Goes, [0006], a system for rendering volumetric objects with contours <the drawings with contour lines are interpreted as lineworks>), comprising: …
Regarding Claim 2 and 11, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the method and system of Claims 1 and 10 respectively. They further disclose wherein generating the stylized curves includes
assigning properties to achieve a natural look (Ferrari de Goes, [0092], teaches tapering the ends of contour ribbons; Ferrari de Goes, [Fig. 10b], illustrating tapered ends of contour ribbons, 1054).
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Regarding Claim 6, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the method and system of Claims 1 and 10 respectively. They further disclose
rendering the stylized curves (Ferrari de Goes, [Fig. 8], shows rendered stylized curves; <not relied upon but: Seymour, [Image 6], shows rendered stylized curves>).
Regarding Claim 7, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the method and system of Claims 1 and 10 respectively. They further disclose
adding hand-drawn lines to the stylized curves (Seymour, [Images 4-5], describes how artists can use the “nudging” workflow on ML predictions <stylized lines> to make corrections, wherein the nudging workflow has an artist adds nudges using a brush in a 2D space <interpreted as hand drawn, because even though the artist is working digitally, the artist uses physical hand movements to create>)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method disclosed by the combination of Ferrari de Goes, Seymour, and Bickerstaff by adding hand-drawn lines to the stylized curves as further taught by Seymour. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make this modification to add authenticity to the art/animation frame they create.
Regarding Claim 14, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the system of Claim 10. The combination of Ferrari de Goes, Seymour, and Bickerstaff disclose(s) the processor further configured to
add sets of hand-drawn drawings to the stylized curves (Seymour, [Images 4-5], describes how artists can use the “nudging” workflow on ML predictions <stylized lines> to make corrections, wherein the nudging workflow has an artist adds nudges using a brush in a 2D space <interpreted as hand drawn, because even though the artist is working digitally, the artist uses physical hand movements to create>)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method disclosed by the combination of Ferrari de Goes, Seymour, and Bickerstaff by adding hand-drawn lines to the stylized curves as further taught by Seymour. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make this modification to add authenticity to the art/animation frame they create.
Claims 3 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, and Bickerstaff in view of Blender (“Blender Manual - Geometry”, 2023), hereinafter referenced as Blender.
Regarding Claims 3 and 12, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the method and system of Claims 2 and 11 respectively. They further disclose tapering as mentioned above, but they do not disclose all of the limitations of Claims 3 and 12. However, Blender discloses wherein the properties (Blender, [Image 1], “Properties > Geometry”) include
varying tapering and offsetting (Blender, [Image 1], shows different settings <varying> for offset, it shows Offset at 0m in “Geometry Panel” and “1 offset” in “Bezier Circle”; Blender, [Images 7-9], show different tapering settings; Blender, [Image 9], Fig. “Taper example 3” shows irregular <varying> taper curve applied to an object).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, and Bickerstaff by varying tapering and offsetting as taught by Blender. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because tapering and offsetting add dimension to line work, making it look more dynamic and natural.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, and Bickerstaff in view of Lv et al. (CN 118075247 A), hereinafter referenced as Lv.
Regarding Claim 4, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the method and system of Claims 1 and 10 respectively. The combination of Ferrari de Goes, Seymour, and Bickerstaff fail to explicitly disclose the limitations of Claim 4, however, Lv discloses
determining, using motion data for a character represented in scene data whether a redraw rate of the base curves corresponds to screen-space movement of the character (Lv: [0063], discloses the movement speed <motion data> for a character represented in a scene <scene data>, identified by a facial recognition rectangle, whether the refresh rate <interpreted as redraw rate of the base curves, because the frame, comprising the background image, a shape made up of base curves> is written, or redrawn to the next frame> of the frames corresponds to the character’s movement speed <screen-space movement of the character>).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method or system disclosed by the combination of Ferrari de Goes, Seymour, and Bickerstaff by determining the frame refresh rate does not correspond to the movement speed as taught by Lv. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make this modification for determining visual coherence.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, Bickerstaff, and Lv in view of MediBang Paint (“nao-comic – How to use the pen setting”, 2022), hereinafter referenced as MediBang.
Regarding Claims 5, the combination of Ferrari de Goes, Seymour, Bickerstaff, and Lv disclose the method and system of Claims 1 and 10 respectively. The combination of Ferrari de Goes, Seymour, Bickerstaff, and Lv further disclose
adjusting the frame rate <redraw rate> when the redraw rate does not correspond to the screen-space movement of the character (Lv: [0063], discloses if the motion speed is less than 60 pixels, the frame rate <redraw rate is adjusted> is reduced to correspond with the person’s <character’s> movement speed).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method or system disclosed by the combination of Ferrari de Goes, Seymour, Bickerstaff, and Lv by dynamically adapting frame refresh rate to correspond to movement speed as taught by Lv. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make this modification for visual coherence.
The combination of Ferrari de Goes, Seymour, Bickerstaff, and Lv fail to explicitly disclose
generating and fading in and out multiple sets of base curves when a condition is met
However, MediBang discloses
generating and fading in and out multiple sets of base curves when the “Force Fade In/Out” box is checked (MediBang, [Image 4], discloses lines that fade in and out; MediBang, [Image 6], illustrates sets of curves using a fade in/out effect <where every couple of illustrated lines is read as a set>; MediBang, [Images 8 and 9], teaches to create sets of lines that fade in and out, the checkbox for “Force Fade In/Out” must be checked and the pen tool will have the effect automatically)
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It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, and Bickerstaff, and Lv by conditionally generating base curves that fade in and out as taught by MediBang. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because base curves fading in and out generate a softer and lighter effect, giving a more sketched-out or comic book style appearance.
Claims 8-9 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, and Bickerstaff in view of Github Freestyle SVG Exporter (“folkertdev – Freestyle SVG Exporter”, 2016), hereinafter referenced as Github.
Regarding Claim 8, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the method of Claim 7. They do not disclose the limitations of Claim 8. However, Github discloses wherein
exporting vector data from a digital content creation application to produce sets of drawings (Github, [Images 1-3], disclose a Blender <digital content creation application> addon that exports sets of drawings under the “Animation” mode as SVGs <inherently vector data>; Blender [Images 4 and 5], show an example of an exported SVG that produces a set of drawings).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, and Bickerstaff by exporting an SVG from Blender to produce an animation as taught by Github. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because this addon provides independent high-resolution graphics and enables 3D-to-2D workflows.
Regarding Claim 9, the combination of Ferrari de Goes, Seymour, Bickerstaff, and Github disclose the method of Claim 8. They further disclose
interpolating and merging sets of drawings with the stylized curves (Seymour, [Image 1], illustrates sets of drawings combined with stylized curves, shown below using the Figure: “Machine Learning gave SPI the natural look they needed for a comic book illustrative style in CG animation”; Seymour, [Images 4 and 5], teach supplementing the machine learning mode with the manual mode, combining the generated prediction <drawings> with nudges <stylized curves> from manual mode; Seymour, [Image 4], teaches artist’s nudges were automatically keyed and interpolated, “We projected the curves directly onto the geometry and interpolated the nudges in screen-space or an arbitrary UV space (in case of machine learning interpolations)”, further teaching not only the nudges can be interpolated but the machine learning predictions as well)
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It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, Bickerstaff, and Github by interpolating and merging frames as taught by Seymour. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification to impart smooth motion and higher frame raters on visual content.
Regarding Claim 15, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the system of Claim 14. The combination of Ferrari de Goes, Seymour, and Bickerstaff fail to explicitly disclose the limitations of Claim 15, however, Github discloses wherein the processor is further configured to
export vector data from a digital content creation application to produce sets of drawings (Github, [Images 1-3], disclose a Blender <digital content creation application> addon that exports sets of drawings under the “Animation” mode as SVGs <inherently vector data>; Blender [Images 4 and 5], show an example of an exported SVG that produces a set of drawings).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, and Bickerstaff by exporting an SVG from Blender to produce an animation as taught by Github. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because this addon provides independent high-resolution graphics and enables 3D-to-2D workflows.
Regarding Claim 16, the combination of Ferrari de Goes, Seymour, Bickerstaff, and Github disclose the system of Claim 15. The combination of Ferrari de Goes, Seymour, Bickerstaff, and Github further discloses the processor further configured to
interpolate and merge the sets of drawings with the stylized curves interpolating and merging sets of drawings with the stylized curves (Seymour, [Image 1], illustrates sets of drawings combined with stylized curves, shown below using the Figure: “Machine Learning gave SPI the natural look they needed for a comic book illustrative style in CG animation”; Seymour, [Images 4 and 5], teach supplementing the machine learning mode with the manual mode, combining the generated prediction <drawings> with nudges <stylized curves> from manual mode; Seymour, [Image 4], teaches artist’s nudges were automatically keyed and interpolated, “We projected the curves directly onto the geometry and interpolated the nudges in screen-space or an arbitrary UV space (in case of machine learning interpolations)”, further teaching not only the nudges can be interpolated but the machine learning predictions as well)
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It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, Bickerstaff, and Github by interpolating and merging frames as taught by Seymour. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification to impart smooth motion and higher frame raters on visual content.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, and Bickerstaff in view of Lv, and in further view of MediBang.
Regarding Claim 13, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the system of Claim 10. The combination of Ferrari de Goes, Seymour, and Bickerstaff fail to disclose the limitations of Claim 13, however, Lv discloses the processor further configured to
determine, using motion data for a character represented in the scene data, whether a redraw rate of the base curves corresponds to screen-space movement of the character (Lv: [0063], discloses the movement speed <motion data> for a character represented in a scene <scene data>, identified by a facial recognition rectangle, whether the refresh rate <interpreted as redraw rate of the base curves, because the frame, comprising the background image, a shape made up of base curves> is written, or redrawn to the next frame> of the frames corresponds to the character’s movement speed <screen-space movement of the character>),
and adjusting the frame rate <redraw rate> when the redraw rate does not correspond to the screen-space movement of the character (Lv: [0063], discloses if the motion speed is less than 60 pixels, the frame rate <redraw rate is adjusted> is reduced to correspond with the person’s <character’s> movement speed).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method or system disclosed by the combination of Ferrari de Goes, Seymour, and Bickerstaff by dynamically adapting frame refresh rate to correspond to movement speed as taught by Lv. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make this modification to identify and adapt redraw/refresh rates for visual coherence.
The combination of Ferrari de Goes, Seymour, Bickerstaff, and Lv fail to disclose
and generate and fade in and out multiple sets of base curves when … .
However, MediBang discloses
and generate and fade in and out multiple sets of base curves when the “Force Fade In/Out” box is checked (MediBang, [Image 4], discloses lines that fade in and out; MediBang, [Image 6], illustrates sets of curves using a fade in/out effect <where every couple of illustrated lines is read as a set>; MediBang, [Images 8 and 9], teaches to create sets of lines that fade in and out, the checkbox for “Force Fade In/Out” must be checked and the pen tool will have the effect automatically)
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It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, Bickerstaff, and Lv by conditionally generating base curves that fade in and out as taught by MediBang. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because base curves fading in and out generate a softer and lighter effect, giving a more sketched-out or comic book style appearance.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Ferrari de Goes in view of Seymour, in further view of Bickerstaff, and in further view of MeLinand et al. (US 2017/0103032 A1), hereinafter referenced as MeLinand.
Regarding Claim 17, it recites limitations similar in scope to Claims 1 and 10, but as a non-transitory computer readable storage medium. As shown in the rejection, the combination of Ferrari de Goes, Seymour, and Bickerstaff disclose the limitations of Claims 1 and 10. The combination of Ferrari de Goes, Seymour, and Bickerstaff further disclose:
storing a computer program to generate lineworks, the computer program comprising executable instructions that cause a computer to: … (Ferrari de Goes, [0125-0125], discloses program code stored in a memory subsystem; Ferrari de Goes, [0132], discloses the executed code including the contour generation <linework generation> method)
The combination of Ferrari de Goes, Seymour, and Bickerstaff fail to disclose
A non-transitory computer-readable storage medium storing a computer program
However, MeLinand discloses
A non-transitory computer-readable storage medium storing a computer program (MeLinand, [0010], discloses a computer program with a non-transitory computer readable medium with a computer readable program code embodied therein adapted to be executed to implement the method)
It would have been obvious for one having ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, and Bickerstaff by claiming a non-transitory computer-readable storage medium storing a computer program as taught by MeLinand. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated to apply this because a non-transitory computer-readable storage medium provides tangible, persistent storage for instructions that remain available to a processor without needing internet connection
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, Bickerstaff, Melinand in view of Blender.
Regarding Claim 18, the combination of Ferrari de Goes, Seymour, and Bickerstaff, and MeLinand disclose the non-transitory computer-readable medium of Claim 17. The combination of Ferrari de Goes, Seymour, and Bickerstaff fail to explicitly disclose the limitations of Claim 18, however, Blender discloses wherein the executable instructions that cause the computer to generate the stylized curves include executable instructions that cause the computer to
assign properties including varying tapering and offsetting (Blender: [Image 1], “Properties > Geometry”; [Image 1], shows different settings <varying> for offset, it shows Offset at 0m in “Geometry Panel” and “1 offset” in “Bezier Circle”; [Images 7-9], show different tapering settings; [Image 9], Fig. “Taper example 3” shows irregular <varying> taper curve applied to an object).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, Bickerstaff, and MeLinand by varying tapering and offsetting as taught by Blender. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because tapering and offsetting add dimension to line work, making it look more dynamic and natural.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, Bickerstaff, and MeLinand in view of Lv, and in further view of MediBang.
Regarding Claim 19, the combination of Ferrari de Goes, Seymour, Bickerstaff, and MeLinand disclose the non-transitory computer-readable medium of Claim 17. The combination of Ferrari de Goes, Seymour, Bickerstaff, and MeLinand fail to explicitly disclose the limitations of Claim 19, however, Lv discloses wherein the executable instructions that cause the computer to
determine, using motion data for a character represented in the scene data, whether a redraw rate of the base curves corresponds to screen-space movement of the character (Lv: [0063], discloses the movement speed <motion data> for a character represented in a scene <scene data>, identified by a facial recognition rectangle, whether the refresh rate <interpreted as redraw rate of the base curves, because the frame, comprising the background image, a shape made up of base curves> is written, or redrawn to the next frame> of the frames corresponds to the character’s movement speed <screen-space movement of the character>),
and adjusting the frame rate <redraw rate> when the redraw rate does not correspond to the screen-space movement of the character (Lv: [0063], discloses if the motion speed is less than 60 pixels, the frame rate <redraw rate is adjusted> is reduced to correspond with the person’s <character’s> movement speed).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method or system disclosed by the combination of Ferrari de Goes, Seymour, Bickerstaff, and MeLinand by dynamically adapting frame refresh rate to correspond to movement speed as taught by Lv. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make this modification to identify and adapt redraw/refresh rates for visual coherence.
The combination of Ferrari de Goes, Seymour, Bickerstaff, MeLinand, and Lv fail to disclose
and generate and fade in and out multiple sets of base curves when … .
However, MediBang discloses
and generate and fade in and out multiple sets of base curves when the “Force Fade In/Out” box is checked (MediBang, [Image 4], discloses lines that fade in and out; MediBang, [Image 6], illustrates sets of curves using a fade in/out effect <where every couple of illustrated lines is read as a set>; MediBang, [Images 8 and 9], teaches to create sets of lines that fade in and out, the checkbox for “Force Fade In/Out” must be checked and the pen tool will have the effect automatically)
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It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, Bickerstaff, MeLinand, and Lv by conditionally generating base curves that fade in and out as taught by MediBang. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because base curves fading in and out generate a softer and lighter effect, giving a more sketched-out or comic book style appearance.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Ferrari de Goes, Seymour, Bickerstaff, Melinand in view of Github.
Regarding Claim 20, the combination of Ferrari de Goes, Seymour, Bickerstaff, and MeLinand disclose the non-transitory computer-readable medium of Claim 17. The combination of Ferrari de Goes, Seymour, Bickerstaff, and MeLinand further disclose wherein the executable instructions that cause the computer to:
add hand-drawn lines to the stylized curves (Seymour, [Images 4-5], describes how artists can use the “nudging” workflow on ML predictions <stylized lines> to make corrections, wherein the nudging workflow has an artist adds nudges using a brush in a 2D space <interpreted as hand drawn, because even though the artist is working digitally, the artist uses physical hand movements to create>);
interpolate and merge the sets of drawings with the stylized curves (Seymour, [Image 1], illustrates sets of drawings combined with stylized curves, shown below using the Figure: “Machine Learning gave SPI the natural look they needed for a comic book illustrative style in CG animation”; Seymour, [Images 4 and 5], teach supplementing the machine learning mode with the manual mode, combining the generated prediction <drawings> with nudges <stylized curves> from manual mode; Seymour, [Image 4], teaches artist’s nudges were automatically keyed and interpolated, “We projected the curves directly onto the geometry and interpolated the nudges in screen-space or an arbitrary UV space (in case of machine learning interpolations)”, further teaching not only the nudges can be interpolated but the machine learning predictions as well).
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It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, Bickerstaff, and MeLinand by adding hand drawn lines and interpolating and merging frames as taught by Seymour. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification to impart smooth motion and higher frame raters on visual content.
The combination of Ferrari de Goes, Seymour, Bickerstaff, and MeLinand fail to disclose
export vector data from a digital content creation application to produce sets of drawings; and
However, Github discloses
export vector data from a digital content creation application to produce sets of drawings (Github, [Images 1-3], disclose a Blender <digital content creation application> addon that exports sets of drawings under the “Animation” mode as SVGs <inherently vector data>; Blender [Images 4 and 5], show an example of an exported SVG that produces a set of drawings); and
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the method and system disclosed by Ferrari de Goes, Seymour, and Bickerstaff by exporting an SVG from Blender to produce an animation as taught by Github. One of ordinary skill in the art before the effective filing of the claimed invention would have been motivated make this modification because this addon provides independent high-resolution graphics and enables 3D-to-2D workflows.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Qingping et al. (CN 101246547 A) discloses classification according to motion character point, then updating the rate based on the classification result.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/I.O./Examiner, Art Unit 2618
/DEVONA E FAULK/Supervisory Patent Examiner, Art Unit 2618
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