DETAILED ACTION
This is in response to application filed on March 28th, 2025 in which claims 1-18 were presented for examination, amended by preliminary amendment 3/28/25 to present claims 19-38 for examination.
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 .
Specification
The disclosure is objected to because of the following informalities:
[0015] “EC” is an abbreviation without previously defining the term; to correct without adding new matter, the support for the definition would have to be pointed out from within the original disclosure
[0016] “like.)).” should read “like).”
[0016] “like.).” should read “like).”
[0018] “department.).” should read “department).”
[0054] “like.).” should read “like).”
[0088] “patterned or grader” needs review whether it should read “patterner or grader”
Appropriate correction is required.
Claim Objections
Claim(s) 23, 26, 32 is/are objected to because of the following informalities:
For consistency, Claim 23 Line 1 delete “of” and substitute –according to—
Claim 26 Line 4 before “seam allowance” delete “a” and substitute –the—for proper antecedent basis with Claim 26 Line 3
Claim 32 Line 6 before “seam allowance” delete “a” and substitute –the—for proper antecedent basis with Claim 26 Line 3, on which Claim 32 depends
Disagreement with any of the aforementioned may warrant at least a 112(b) indefiniteness rejection without constituting a new rejection
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claim(s) 19-38 is/are rejected under U.S.C. 112(b).
The term “pattern paper data” in Claim 19 Lines 4-5 is unclear and therefore renders the claim indefinite. It is unclear how the term differs from the term “pattern paper data” in Claim 19 Line 1. For the purposes of applying art and providing rejections, especially in light of Claim 32 and other indefiniteness surrounding terms involving “pattern paper data,” both Claim 19 Line 1 and Claim 19 Lines 4-5 will be interpreted as being the final pattern paper data.
The term “a size indicated by the size information” in Claim 19 Line 5 is unclear and therefore renders the claim indefinite. It is unclear how “size” is different from the word “size” in “size information.” For the purposes of applying art and providing rejections, the term will be interpreted “the size information”.
The term “trained model including a model obtained” in Claim 19 Line 6 is unclear and therefore renders the claim indefinite. It is unclear how “model” differs from the word “model” in “trained model.” For the purposes of applying art and providing rejections, the term will be interpreted “trained model obtained”.
The term “pattern paper data” in Claim 19 Line 7 is unclear and therefore renders the claim indefinite. It is unclear how this term relates to that in Line 1 and that in Lines 4-5. For the purposes of applying art and providing rejections, the term will be interpreted as referring to different pattern paper data (such as the 10 pieces in the example of [0032]).
The term “plurality of pieces of clothing” in Claim 19 Line 7 is unclear and therefore renders the claim indefinite. It is unclear how the term clothing relates to “pattern paper data of clothing” in Claim 19 Line 5. For the purposes of applying art and providing rejections, Claim 19 Line 1 will be interpreted as referring to final pattern paper data of user-requested clothing, and so will Claim 19 Lines 4-5, such that Claim 19 Line 7 is of other related clothing to determine the user-requested clothing, such as in the example of [0032].
The term “type same” in Claim 19 Line 7 is unclear and therefore renders the claim indefinite. It is unclear how this term differs from “same type”, which is specifically defined in [0009]. For the purposes of applying art and providing rejections, the term will be considered the same.
The term "specific" in claim 19 Line 8 is a relative term which renders the claim indefinite. The term "specific" is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is not clear what constitutes the metes of bounds of the term.
The term “specific clothing” in Claim 19 Line 8 is unclear and therefore renders the claim indefinite. It is unclear how this clothing relates to that in Claim 19 Line 5 and Claim 19 Line 7. For the purposes of applying art and providing rejections, the term will be considered the same as target clothing, such that the only difference between Claim 19 and 20 is that the reception means includes clothing identification information.
The term “target clothing” in Claim 20 Line 3 is unclear and therefore renders the claim indefinite. It is unclear how this term differs from “clothing” in Claim 19 Line 5, Claim 19 Line 7, and Claim 19 Line 8. For the purposes of applying art and providing rejections, the term will be considered as referring to [0008], “clothing to be graded,” or that of the user request.
The term “size information” in Claim 20 Line 2 is unclear and therefore renders the claim indefinite. It is unclear how this size information differs from “size information” in Claim 19 Line 3. For the purposes of applying art and providing rejections, the terms will be considered the same.
The term “pattern paper data of clothing” in Claim 20 Line 5 is unclear and therefore renders the claim indefinite. The term is rejected for reasons similar to Claim 19. Further, it is unclear how the data or the clothing relate to similar terms aforementioned. For the purposes of applying art and providing rejections, the term will be considered the same as Claim 19 Lines 4-5.
Claim 20 recites the limitation "the same type" in Line 5. There is insufficient antecedent basis for this limitation in the claim.
The term “the same type” in Claim 20 Line 5 is unclear and therefore renders the claim indefinite. It is unclear whether the antecedent basis is found in Claim 19 Line 7. For the purposes of applying art and providing rejections, the term will be considered the same.
The term “a size suitable for a size indicated by the size information” in Claim 20 Lines 6-7 is unclear and therefore renders the claim indefinite. The terms are rejected for reasons similar to Claim 19. Furthermore, it is unclear how the term differs from similar terms in Claim 19. For the purposes of applying art and providing rejections, the terms will be considered the same.
The term “a model obtained by learning a relationship between pieces of pattern paper data of a plurality of pieces of clothing” in Claim 20 Lines 7-9 is unclear and therefore renders the claim indefinite. The terms are rejected for reasons similar to Claim 19. Furthermore, it is unclear how the term differs from similar terms in Claim 19. For the purposes of applying art and providing rejections, the terms will be considered the same.
The term “a relationship between the pieces of pattern paper data of the plurality of pieces of clothing” in Claim 21 Lines 4-5 is unclear and therefore renders the claim indefinite. It is unclear how this relationship differs from “relationship” in Claim 20 Line 8, let alone “relationship” in Claim 19 Line 6, on which Claim 21 eventually depends. For the purposes of applying art and providing rejections, the term will be considered the same.
The term “pattern paper data of clothing” In Claim 25 Line 2 is unclear and therefore renders the claim indefinite. It is unclear how this term differs from “pattern paper data” aforementioned in the claims, let alone “pattern paper data of clothing” in Claim 19 Lines 4-5. Especially as [0089]-[0091] indicates that data can be re-learned or that new data can be learned, it is further unclear which scenario the term refers to.
The term “pattern paper data” in Claim 32 Line 2 is unclear and therefore renders the claim indefinite. It is unclear how the term relates to similar terms aforementioned in the claims. For the purposes of applying art and providing rejections, the term will be considered of the final pattern paper data.
The term “pattern paper data” in Claim 32 Line 8 is unclear and therefore renders the claim indefinite. It is unclear how the term relates to similar terms aforementioned in the claims. For the purposes of applying art and providing rejections, the term will be considered of the final pattern paper data.
The term “a point in the latent space representing corresponding pattern paper data, each pattern paper data..” in Claim 34 Lines 2-3 is unclear and therefore renders the claim indefinite. Claim seems to only want to establish a single point for a single paper data, but then establishes a plurality of pattern paper data with each.” It is unclear if claim was meant to only refer to a single data, or meant to establish each point.
The term “reliability” in Claim 34 Line 3 is unclear and therefore renders the claim indefinite. It is unclear how this term differs from Claim 24 Line 2.
The term “corresponding” in Claim 34 Line 2 and Line 4 is unclear and therefore renders the claim indefinite. It is unclear how the terms are meant to be interpreted (same? differently?) in the two instances.
The term “point…representing corresponding …data, each …data having reliability according to a position in the latent space…reliability corresponding to a position by specifying the position of the…data in the latent space” in Claim 34 Lines 2-5 is unclear and therefore renders the claim indefinite. As best understood, the recitation of “reliability corresponding to a position” is redundant.
The term “means for manufacturing…includes a machine for clothing manufacturing, or a cutting machine and a sewing machine” in Claim 36 is unclear and therefore renders the claim indefinite. It is unclear how the terms relate to one another—are cutting and sewing specific machines for clothing manufacturing such that it should read “includes cutting or sewing machine for clothing manufacturing”? Is the claim indicating that there are three mutually exclusive options for means? For the purposes of applying art and providing rejections, the term will be interpreted as the former.
Claim 37 is rejected for reasons similar to Claim 19.
Claim 38 is rejected for reasons similar to Claim 19.
Dependent claims are rejected at the least for depending on rejected claims.
Examiner Notes
Best effort has been made to identify all indefinite language with the pending claims. However, since the claims are replete with indefinite language, Examiner notes the above listing 35 U.S.C. § 112 rejections may not be conclusive and Applicant is required to review every claim for compliance to 35 U.S.C. § 112(b) so as to facilitate a clear understanding of the claimed invention and proper application of the prior art. Due to the plethora of issues, any resulting 112(b) rejections that could have been indicated herein that are instead found after applicant amendments will not be considered a new rejection.
Claim Interpretation
Specific Definitions
The following terms have specific definitions from the specification:
“type same” defined in [0009] as “same model number, product number, model type, model, or the like” applied to Claim 19 Line 7; Claim 20 Lines 6, 9; Claim 37 Line 7; Claim 38 Line 9
“Target clothing” defined in [0008] as “clothing to be graded” applied to Claim 20 Lines 3, 6, 9
U.S.C. 112(f)
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“means for manufacturing clothing” in Claim 28 Line 3, wherein the structure for the term is found in Claim 36, and therefore [0013] “manufactured by cutting with a round blade, a straight blade cutting machine, sewing with a sewing machine” and its equivalents
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function. Such claim limitation(s) is/are:
“reception means” in Claim 19 Line 3
“generation means” in Claim 19 Line 4
“output means” in Claim 19 Line 9
reception means in Claim 20 Line 2
generation means in Claim 20 Line 4
“calculation means” in Claim 24 Line 2
output means in Claim 24 Line 3
“learning means” in Claim 25 Lines 1-2
generation means in Claim 26 Line 4
The terms of Claim 19 as applied to Claim 28
generation means in Claim 32 Line 1
calculation means in Claim 34 Line 4
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
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.
FIRST REJECTION: As best understood in light of the 112(b) rejections-- Claim(s) 19, 20, 30, 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap.
Regarding Claim 19, Surville teaches a system for pattern data (it is noted that a recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus satisfying the claimed structural limitations; abstract "means for automatically generating grading rules"; Col. 1 Lines 3-4 "computer system for grading garments"; Col. 13 Lines 50-54 "On the basis of this data, the grading software 12 works out grading 9 for the garment file 8. This step is entirely automatic, insofar as the software computes and/or applies the rules to the various characteristic points"; Col. 13 Lines 41-48 "grader selects the garment to be graded. The grading software 13 loads…with the shapes 7 of all of the pieces of the garment to be graded. The grader selects the garment scale 10 that is to be applied, corresponding to the intended population and/or to the garment in question, together with the taxonomy 11 corresponding to trousers", wherein Fig. 7 shows pattern data), the system comprising:
a reception means that receives size information (Col. 13 Lines 41-48 "grader selects the garment to be graded. The grading software 13 loads…with the shapes 7 of all of the pieces of the garment to be graded. The grader selects the garment scale 10 that is to be applied, corresponding to the intended population"; wherein garment scale indicates size info);
a generation means that generates, based on the size information, pattern data of clothing having a size suitable for a size indicated by the size information using automation (see Fig. 10; generate-- Col. 16 Lines 15-18 "Increments for a point and for all sizes are computed, thereby enabling the grading rule 30 for the point to be worked out. Thus, the set of grading rules for all of the characteristic points of the garment are worked out"; Col. 13 Lines 50-54 "On the basis of this data, the grading software 12 works out grading 9 for the garment file 8. This step is entirely automatic, insofar as the software computes and/or applies the rules to the various characteristic points"),
using a computer to determine a relationship between pieces of pattern paper data of a plurality of pieces of clothing of a type same as a specific clothing (relationship between claimed pieces-- Col. 16 Lines 15-18 "Increments for a point and for all sizes are computed, thereby enabling the grading rule 30 for the point to be worked out. Thus, the set of grading rules for all of the characteristic points of the garment are worked out"; wherein all sizes is claimed pieces).
Surville does not explicitly teach that the pattern data is pattern paper data,
an output means that outputs the generated pattern paper data.
Nomura teaches pattern paper data (abstract "paper pattern shape changed so as to satisfy the constraint condition is outputted from an outputting means M4"; [0001] "invention relates to a pattern making method and apparatus…for automatically grading (enlarging/reducing) data of a...pattern...according to the body size"; [0013] “by modifying the shape data…possible to create patterns for clothing with different designs”; [0032] "computer program for the pattern making method of the present invention can also be provided on a medium such as a CD-ROM"),
an output means that outputs the generated pattern paper data (see above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville’s pattern data to be of paper and to have output means as taught by Nomura as a known arrangement to provide pattern shape for clothing after size change/grading, which both Surville and Nomura are directed to.
Surville does not explicitly teach that the automation/computer is using a trained model.
Hadap teaches that the generation of data of clothing having a size suitable for a size indicated by the size information using automation uses a trained model (for size information-- Col. 5 Lines 1-4 "body 302 may be generated from newly provided body measurements of a particular customer who is interested in purchasing a custom fitted garment"; for using size information into a trained model to generate -- see Fig. 3; Col. 4 Line 65-Col. 5 Line 1 "resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 5 Lines 9-17 "reference bodies 310, 312, and 314 may have previously had custom designed garment patterns 320, 322, and 324, respectively, designed to fit them...a new custom garment pattern 350 may then be generated by the system by blending or interpolating garment parameters...of the selected sample patterns 320, 322, and 324"; for Fig. 3 being from a trained model-- Col. 5 Lines 19-21 "Fig. 4A is a flow diagram of an illustrative method 400A for selecting reference sample bodies for creation of associated garment patterns"; Col. 5 Lines 25, 49-53 "illustrative method 400A begins at block 402... the set of bodies may be generated using the SMPL model based in part on captured body measurements of real customers (e.g., in order to reflect the general range of body measurements, BMI, weight, height, etc. of a given customer base)"; Col. 5 Lines 63-65 "SMPL model enables training its entire model from aligned 3D meshes of different people in different poses");
the trained model including a model obtained by learning a relationship between pieces of pattern data of a plurality of pieces of clothing of a type same as a specific clothing (see Fig. 3; Col. 4 Line 65-Col. 5 Line 1 "resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 5 Lines 1-4 "body 302 may be generated from newly provided body measurements of a particular customer who is interested in purchasing a custom fitted garment"; Col. 5 Lines 9-17 "reference bodies 310, 312, and 314 may have previously had custom designed garment patterns 320, 322, and 324, respectively, designed to fit them...a new custom garment pattern 350 may then be generated by the system by blending or interpolating garment parameters...of the selected sample patterns 320, 322, and 324"; for plurality-- see 320, 322, 324 that are same type/design as the desired garment; for Fig. 3 being from a trained model—see aforementioned).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's computer to be a trained model as taught by Hadap as known to utilize a trained model to generate pattern data in order for more accurate fits across a larger variety of sizes (Col. 1 Lines 6-23; Col. 2 Lines 7-14).
Regarding Claim 20, modified Surville teaches all the claimed limitations as discussed above in Claim 19.
Surville further teaches the reception means is further configured to receive clothing identification information for identifying target clothing and size information (Col. 13 Lines 41-48 "grader selects the garment to be graded. The grading software 13 loads…with the shapes 7 of all of the pieces of the garment to be graded. The grader selects the garment scale 10 that is to be applied, corresponding to the intended population and/or to the garment in question, together with the taxonomy 11 corresponding to trousers"; wherein garment scale is size information; wherein taxonomy is target clothing);
the generation means is further configured to generate, based on the clothing identification information and the size information, pattern paper data of clothing of the same type as the target clothing and having a size suitable for a size indicated by the size information using the trained model (see aforementioned rejection of claim 1),
the trained model including a model obtained by learning a relationship between pieces of pattern paper data of a plurality of pieces of clothing of the same type as the target clothing (see aforementioned rejection of claim 1).
Regarding Claim 30, modified Surville teaches all the claimed limitations as discussed above in Claim 19.
Modified Surville further teaches wherein the pieces of pattern paper data and the generated pattern paper data include dimensions of each part (Surville Col. 15 Line 14, 24-28 "taxonomy 11 comprises…information about the orientation of variation in the dimensions of the garment piece…this information is given by a vector"; “Col. 13 Lines 45-48 “The grader selects the garment scale 10 that is to be applied, corresponding to the intended population and/or to the garment in question, together with the taxonomy 11 corresponding to trousers", wherein the above is for pattern paper data, and therefore the generated would also include/be based on dimensions of each part).
Regarding Claim 37, Surville teaches a method for pattern data (if a prior art, in its normal and usual operation, would necessarily describe a device capable of performing the steps of the method or process, then the device claimed will be considered to be inherent by the prior art process or method. When the prior art process or method is the same as a process or method described in the specification for describing the claimed device, it can be assumed the process or method will inherently describe the claimed device capable of performing the different steps of the process or method. In re King, 801 F.2d 1324, 231 USPQ 136 (Fed. Cir. 1986). MPEP 2112.02; as such, for structure for the method, abstract "means for automatically generating grading rules"; Col. 1 Lines 3-4 "computer system for grading garments"; Col. 13 Lines 50-54 "On the basis of this data, the grading software 12 works out grading 9 for the garment file 8. This step is entirely automatic, insofar as the software computes and/or applies the rules to the various characteristic points"; Col. 13 Lines 41-48 "grader selects the garment to be graded. The grading software 13 loads…with the shapes 7 of all of the pieces of the garment to be graded. The grader selects the garment scale 10 that is to be applied, corresponding to the intended population and/or to the garment in question, together with the taxonomy 11 corresponding to trousers", wherein Fig. 7 shows pattern data), the method comprising:
receiving size information (Col. 13 Lines 41-48 "grader selects the garment to be graded. The grading software 13 loads…with the shapes 7 of all of the pieces of the garment to be graded. The grader selects the garment scale 10 that is to be applied, corresponding to the intended population"; wherein garment scale indicates size info);
generating, based on the size information, pattern data of clothing having a size suitable for a size indicated by the size information using automation (see Fig. 10; generate-- Col. 16 Lines 15-18 "Increments for a point and for all sizes are computed, thereby enabling the grading rule 30 for the point to be worked out. Thus, the set of grading rules for all of the characteristic points of the garment are worked out"; Col. 13 Lines 50-54 "On the basis of this data, the grading software 12 works out grading 9 for the garment file 8. This step is entirely automatic, insofar as the software computes and/or applies the rules to the various characteristic points"),
using a computer to determine a relationship between pieces of pattern paper data of a plurality of pieces of clothing of a type same as a specific clothing (relationship between claimed pieces-- Col. 16 Lines 15-18 "Increments for a point and for all sizes are computed, thereby enabling the grading rule 30 for the point to be worked out. Thus, the set of grading rules for all of the characteristic points of the garment are worked out"; wherein all sizes is claimed pieces).
Surville does not explicitly teach that the pattern data is pattern paper data,
outputting the generated pattern paper data,
and therefore the method for outputting pattern paper data.
Nomura teaches pattern paper data (abstract "paper pattern shape changed so as to satisfy the constraint condition is outputted from an outputting means M4"; [0001] "invention relates to a pattern making method and apparatus…for automatically grading (enlarging/reducing) data of a...pattern...according to the body size"; [0013] “by modifying the shape data…possible to create patterns for clothing with different designs”; [0032] "computer program for the pattern making method of the present invention can also be provided on a medium such as a CD-ROM"),
an output means that outputs the generated pattern paper data (see above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville’s pattern data to be of paper and to have output means as taught by Nomura as a known arrangement to provide pattern shape for clothing after size change/grading, which both Surville and Nomura are directed to.
Surville does not explicitly teach that the automation/computer is using a trained model.
Hadap teaches that the generating pattern data of clothing having a size suitable for a size indicated by the size information using automation uses a trained model (for size information-- Col. 5 Lines 1-4 "body 302 may be generated from newly provided body measurements of a particular customer who is interested in purchasing a custom fitted garment"; for using size information into a trained model to generate -- see Fig. 3; Col. 4 Line 65-Col. 5 Line 1 "resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 5 Lines 9-17 "reference bodies 310, 312, and 314 may have previously had custom designed garment patterns 320, 322, and 324, respectively, designed to fit them...a new custom garment pattern 350 may then be generated by the system by blending or interpolating garment parameters...of the selected sample patterns 320, 322, and 324"; for Fig. 3 being from a trained model-- Col. 5 Lines 19-21 "Fig. 4A is a flow diagram of an illustrative method 400A for selecting reference sample bodies for creation of associated garment patterns"; Col. 5 Lines 25, 49-53 "illustrative method 400A begins at block 402... the set of bodies may be generated using the SMPL model based in part on captured body measurements of real customers (e.g., in order to reflect the general range of body measurements, BMI, weight, height, etc. of a given customer base)"; Col. 5 Lines 63-65 "SMPL model enables training its entire model from aligned 3D meshes of different people in different poses");
the trained model including a model obtained by learning a relationship between pieces of pattern data of a plurality of pieces of clothing of a type same as a specific clothing (see Fig. 3; Col. 4 Line 65-Col. 5 Line 1 "resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 5 Lines 1-4 "body 302 may be generated from newly provided body measurements of a particular customer who is interested in purchasing a custom fitted garment"; Col. 5 Lines 9-17 "reference bodies 310, 312, and 314 may have previously had custom designed garment patterns 320, 322, and 324, respectively, designed to fit them...a new custom garment pattern 350 may then be generated by the system by blending or interpolating garment parameters...of the selected sample patterns 320, 322, and 324"; for plurality-- see 320, 322, 324 that are same type/design as the desired garment; for Fig. 3 being from a trained model—see aforementioned).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's computer to be a trained model as taught by Hadap as known to utilize a trained model to generate pattern data in order for more accurate fits across a larger variety of sizes (Col. 1 Lines 6-23; Col. 2 Lines 7-14).
As such, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that modified Surville teaches a method for outputting pattern paper data.
As best understood in light of the 112(b) rejections-- Claim(s) 21-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap, as applied to the FIRST REJECTION above, further in view of Kuehn (USPN 11969041).
Regarding Claim 21, modified Surville teaches all the claimed limitations as discussed above in Claim 20.
Surville does not explicitly teach wherein the target clothing and the plurality of pieces of clothing include components whose number varies according to sizes of the target clothing and the plurality of pieces of clothing,
and the trained model learns a relationship between the pieces of pattern paper data of the plurality of pieces of clothing by aligning the number of the components in the pieces of pattern paper data of the plurality of pieces of clothing.
Kuehn teaches wherein the target clothing and the plurality of pieces of clothing include components whose number varies according to sizes of the target clothing and the plurality of pieces of clothing (Col. 13 Lines 36-39 "hosting system 136 may include one or more machine learning trained models stored on servers 138 to perform one or more instructions of the apparel patternmaking application 128"; Col. 28 Lines 54-64 "the code associated with creating the sloper for the suit jacket 1500 shown in FIG. 15 may be adjusted in many ways, including to provide only two buttons 1502, 1504 on the front 1301 of the suit jacket 1500 rather than the three buttons 1304a, 1304b, and 1304c used for the basic jacket 1300 for a taller person. The height difference may thus be taken into account with a design change that can be selected", wherein taller person indicates related to size of target clothing),
and the trained model learns a relationship between the pieces of pattern paper data of the plurality of pieces of clothing by aligning the number of the components in the pieces of pattern paper data of the plurality of pieces of clothing (for learning -- Col. 4 Line 56-Col. 5 Line 14 "the apparel patternmaking application as described herein includes a machine learning trained module configured to identify errors in the one or more selections provided by a user for the list of conditional results, including to identify errors for the provided different outcomes or changes other than the default pre-defined design details and changes for the one or more conditions from the list of conditional results, and the provided new additional conditions with the new outcomes or changes to be applied to the first sloper as provided by the user", wherein sloper of learning includes aligning/adjusting number of components in the data--Col. 13 Lines 36-39 "hosting system 136 may include one or more machine learning trained models stored on servers 138 to perform one or more instructions of the apparel patternmaking application 128"; see Figs. 13, 15; Col. 28 Lines 54-64 "the code associated with creating the sloper for the suit jacket 1500 shown in FIG. 15 may be adjusted in many ways, including to provide only two buttons 1502, 1504 on the front 1301 of the suit jacket 1500 rather than the three buttons 1304a, 1304b, and 1304c used for the basic jacket 1300 for a taller person. The height difference may thus be taken into account with a design change that can be selected"; for between--wherein such learning is relationship between pieces -- height differences).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville to take into account the components as taught by Kuehn in order to make accurate pieces (Col. 28 Lines 54-64).
Regarding Claim 22, modified Surville teaches all the claimed limitations as discussed above in Claim 21.
Kuehn further teaches wherein the generation means is further configured to delete one or more of the components from the generated pattern paper data output from the trained model according to the size indicated by the size information (Col. 13 Lines 36-39 "hosting system 136 may include one or more machine learning trained models stored on servers 138 to perform one or more instructions of the apparel patternmaking application 128"; see Figs. 13, 15; Col. 28 Lines 54-64 "the code associated with creating the sloper for the suit jacket 1500 shown in FIG. 15 may be adjusted in many ways, including to provide only two buttons 1502, 1504 on the front 1301 of the suit jacket 1500 rather than the three buttons 1304a, 1304b, and 1304c used for the basic jacket 1300 for a taller person. The height difference may thus be taken into account with a design change that can be selected", wherein taller person indicates related to size of target clothing; wherein there are two buttons rather than three indicates deleting component, and therefore affecting pattern paper data output from trained model of modified Surville, according to size of a less tall person).
Regarding Claim 23, modified Surville teaches all the claimed limitations as discussed above in Claim 22.
Kuehn further teaches wherein the components include at least one of a button, a button-hole, a loop, a tack, a dart or a pleat (for button-- Col. 13 Lines 36-39 "hosting system 136 may include one or more machine learning trained models stored on servers 138 to perform one or more instructions of the apparel patternmaking application 128"; Col. 28 Lines 54-64 "the code associated with creating the sloper for the suit jacket 1500 shown in FIG. 15 may be adjusted in many ways, including to provide only two buttons 1502, 1504 on the front 1301 of the suit jacket 1500 rather than the three buttons 1304a, 1304b, and 1304c used for the basic jacket 1300 for a taller person. The height difference may thus be taken into account with a design change that can be selected").
As best understood in light of the 112(b) rejections-- Claim(s) 31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap, and Kuehn (USPN 11969041), as applied to the FIRST REJECTION above, further in view of Krivonosova (US Publication 2019/0008226).
Regarding Claim 31, modified Surville teaches all the claimed limitations as discussed above in Claim 21.
Modified Surville does not explicitly teach wherein the generated pattern paper data includes an estimated value of the number of the components.
Krivonosova teaches wherein the generated pattern data includes an estimated value of the number of the components ([0125] "when a garment tailoring instruction is generated...components of the instruction can include...[0128] "recommended fabric"; [0132] "specifications of the recommended fabric …are determined following an algorithm analysis performed by the system, including….[0135] "number and percentage estimate of…presence of plackets in anthropometric areas (…presence of a ...button or placket in this area)", wherein instructions indicate generated pattern data).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville’s specification data of components, as provided by Kuehn, to include number estimate of components as taught by Kirvonosova as known arrangement for garment design (abstract).
As best understood in light of the 112(b) rejections-- Claim(s) 24, 25, 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap, as applied to the FIRST REJECTION above, further in view of Natsui (US Publication 2023/0186092).
Regarding Claim 24, modified Surville teaches all the claimed limitations as discussed above in Claim 19.
Modified Surville does not explicitly teach further comprising a calculation means that calculates reliability of the generated pattern paper data,
wherein the output means outputs a notification or does not output the generated pattern paper data in a case where the reliability is lower than a predetermined threshold.
Natsui teaches a calculation means that calculates reliability of the generated pattern paper data ([0032] "control unit 20 executes information processing in the learning device 10. The control unit 20 includes…accuracy estimation unit 20E"; [0071] "accuracy estimation unit 20 estimates the accuracy of the untrained model 30B generated by the model generation unit 20A"; [0072] "accuracy estimation unit 20E estimates the accuracy of the untrained model 30B by using the trained model 30A"; for calculating -- [0073]-[0080], especially with the mathematical expressions, wherein accuracy is reliability),
wherein the output means outputs a notification or does not output the generated pattern paper data in a case where the reliability is lower than a predetermined threshold (for not outputting-- see Fig. 9; [0167] "output control unit 20F makes a negative determination (No at Step S128) when the receiving unit 20G receives information indicating that the performance and accuracy are not desired ones"; [0169] "by contrast, the output control unit 20F makes a positive determination (Yes at Step S128) when the receiving unit 20G receives the information indicating that the performance and accuracy are desired ones"; no output occurs in step S132 as the process goes back to step S118 as shown in Fig. 9).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville with reliability calculations as taught by Natsui in order to provide accuracy ([0032]).
Regarding Claim 25, modified Surville teaches all the claimed limitations as discussed above in Claim 24.
Natsui further teaches further comprising a learning means that causes the trained model to learn pattern paper data of clothing having the size in a case where the reliability is lower than the predetermined threshold (see Fig. 9; training S120 occurs on iteration if S128 accuracy/reliability is NO; [0167] "output control unit 20F makes a negative determination (No at Step S128) when the receiving unit 20G receives information indicating that the performance and accuracy are not desired ones. Thereafter, the process proceeds to Step S130"; [0168] "at step S310, the model generation unit 20A generates a new untrained model 30B of a size different from the size of the learning model 30...thereafter, the process returns to step S102 above"; which would then result in [0163] "at step S120, the training unit 20H trains the learning model").
Regarding Claim 34, modified Surville teaches all the claimed limitations as discussed above in Claim 24.
Modified Surville further teaches wherein the trained model forms a latent space (Hadap Col. 6 Lines 22-25 "at block 404, the computing system may learn an embedding function configured to generate a low-dimensional embedding for any high-dimensional body representation that is provided as input to the embedding function"; Col. 9 Lines 22-25 "this low-dimensional embedding may be derived, in some embodiments, from higher-dimensional body parameters in conjunction with dimensionality reduction techniques such as t-SNE”; see Fig. 3; Col. 4 Lines 61-65 Fig. 3…in the low-dimensional embedding space", wherein such reduction is referring to latent space, see extrinsic evidence IBM NPL),
a point in the latent space representing corresponding pattern paper data (see Hadap Fig. 3; point represents the pattern data; Col. 5 Lines 1-4 "body 302 may be generated from newly provided body measurements of a particular customer who is interested in purchasing a custom fitted garment"; Col. 4 Line 65-Col. 5 Line 1 "resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 5 Lines 9-17 "reference bodies 310, 312, and 314 may have previously had custom designed garment patterns 320, 322, and 324, respectively, designed to fit them...a new custom garment pattern 350 may then be generated by the system by blending or interpolating garment parameters...of the selected sample patterns 320, 322, and 324"; for Fig. 3 being from a trained model-- Col. 5 Lines 19-21 "Fig. 4A is a flow diagram of an illustrative method 400A for selecting reference sample bodies for creation of associated garment patterns"; Col. 5 Lines 25, 49-53 "illustrative method 400A begins at block 402... the set of bodies may be generated using the SMPL model based in part on captured body measurements of real customers (e.g., in order to reflect the general range of body measurements, BMI, weight, height, etc. of a given customer base)"; Col. 5 Lines 63-65 "SMPL model enables training its entire model from aligned 3D meshes of different people in different poses"; wherein Nomura indicated that the pattern data is of paper),
each pattern paper data having reliability according to a position in the latent space (see Hadap Fig. 3; wherein reliability is based on position inasmuch as based on nearness to the embedding; Col. 4 Lines 61-Col. 5 Line 1 "FIG. 3 is an illustrative visualization of a new body representation 302 (shown as embedding 318 in the lower-dimensional embedding space) and its neighboring reference bodies (illustrated as embeddings 310, 312, and 314 in the low-dimensional embedding space), along with a resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"),
wherein the calculation means calculates the reliability corresponding to a position by specifying the position of the generated pattern paper data in the latent space (Natsui calculates accuracy of model, and Hadap is of the model; and therefore Natsui calculation means calculates its reliability corresponding to the Hadap model's position of generated pattern data (350) in the latent space, which is of pattern paper based on Nomura).
As best understood in light of the 112(b) rejections-- Claim(s) 26, 32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap, as applied to the FIRST REJECTION above, further in view of Collins et al (USPN 4916634), herein Collins.
Regarding Claim 26, modified Surville teaches all the claimed limitations as discussed above in Claim 19.
Surville does not explicitly teach wherein the pieces of pattern paper data of the plurality of pieces of clothing do not include a seam allowance, and
the generation means is configured to add a seam allowance to the generated pattern paper data output from the trained model.
Collins teaches wherein the pattern data does not include a seam allowance (Col. 80 Lines 57-63 "in the preferred fitting preparation process 116 in the section entitled Seam Allowance Removal, a seam allowance portion was removed from each part of a project"), and
means configured to add a seam allowance to the generated pattern data (Col. 80 Lines 57-63 "in the preferred fitting preparation process 116 in the section entitled Seam Allowance Removal, a seam allowance portion was removed from each part of a project. At this time, in the preferred embodiment, the seam allowance portion is typically replaced so that the resulting lines of each part represent cut lines").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville to add seam allowance as taught by Collins in order to have proper patterns (Col. 80 Lines 61-63).
As such, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that modified Surville teaches wherein the pieces of pattern paper data of the plurality of pieces of clothing do not include a seam allowance (it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that as the recitation applies to each pattern data as taught by Collins would therefore apply to each piece of pattern data in modified Surville), and
the generation means is configured to add a seam allowance to the generated pattern paper data output from the trained model (it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that the means would be of the generation means as Collins affects the final product and so does the generation means, and therefore be to the generated pattern paper data output from the trained model).
Regarding Claim 32, modified Surville teaches all the claimed limitations as discussed above in Claim 26.
Modified Surville further teaches wherein the generation means is configured to obtain pattern paper data to which the seam allowance is added by (see Collins Col. 80 Line 57-Col. 81 Line 23):
converting the generated pattern paper data output into an image (Collins Col. 80 Lines 64-66 "process to replace seam allowance essentially reverses the process that removed seam allowance as illustrated in Figs. 42A, 42B, and 42C"; see Fig. 42A which is an image; Col. 31 Lines 34-36 "seam allowance removal…patterns are digitized and subsequently represented in electronic pattern data 100");
obtaining a signed distance function by an image processing-based method on the image (Collins method of removal Col. 31 Lines 34-Col. 32 Line 24, which is reversed; see Hadap Fig. 3; Col. 4 Lines 61-Col. 5 Line 1 "FIG. 3 is an illustrative visualization of a new body representation 302 (shown as embedding 318 in the lower-dimensional embedding space) and its neighboring reference bodies (illustrated as embeddings 310, 312, and 314 in the low-dimensional embedding space), along with a resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 2 Lines 22-25 "specific unique body shape of the customer or other input body can then be represented as an interpolation of its nearest neighboring reference body shapes", wherein nearest neighbors indicate signed distance function, see extrinsic evidence Engineer Fix NPL),
specifying a line equidistant outside from an outline of pattern paper in the image to set a region between the outline and the line as a seam allowance (Collins method of removal Col. 31 Lines 34-Col. 32 Line 24, which is reversed; Col. 32 Lines 2-21; Col. 31 Lines 57-61 "when removing seam allowance…a portion of each cut line 874 that forms a corner may extend beyond the new outside boundaries of the part after seam allowance is removed"; Col. 80 Line 66-Col. 81 Line 24); and
converting the image with the seam allowance added into pattern paper data (Collins Fig. 1; outputs the image with seam allowance into data, and Nomura teaches outputting data into pattern paper data).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's data, including the seam allowance addition as provided by Collins, to be determined via Hadap's method, in order for more accurate fits across a larger variety of sizes (Col. 1 Lines 6-23; Col. 2 Lines 7-14).
As best understood in light of the 112(b) rejections-- Claim(s) 27, 35 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap, as applied to the FIRST REJECTION above, further in view of Harvill (US Publication 2024/0112232).
Regarding Claim 27, modified Surville teaches all the claimed limitations as discussed above in Claim 19.
Surville does not explicitly teach wherein the generated pattern paper data is represented using a parametric curve.
However, Hadap of modified Surville discloses utilizing t-SNE for the generated pattern data (Col. 6 Lines 22-25 "at block 404, the computing system may learn an embedding function configured to generate a low-dimensional embedding for any high-dimensional body representation that is provided as input to the embedding function"; Col. 9 Lines 22-25 "this low-dimensional embedding may be derived, in some embodiments, from higher-dimensional body parameters in conjunction with dimensionality reduction techniques such as t-SNE").
Harvill teaches wherein the generated pattern data is represented using a parametric curve (see Fig. 5; abstract; [0001] "techniques for …parametric-based fitting….and displaying customized products using digital image processing"; [0101] "method for custom fitting and manufacturing parametric products comprises generating a parametric model of a custom product based, on at least in part, past learned data pertaining to the custom product and user-specific data of a user"; [0119] "approach described herein...facilitated by executing...examples of the different types of customization"; [0120] "product customization means customizing, or changing, a shape of a custom product for a parametric grading of a product...the parametric grading usually includes determining two or more customized products and interpolating between the sizes of the determined custom product until a desired customized product is obtained"; [0135] "solutions described herein...implemented in the parametric apparel design...2.3.3 fitting using interpolation"; [0139] "in interpolation, one constructs a curve through the data points"; [0142] "2.3.4. fitting using control points"; [0144] "curves generated based on control points may include Bezier curves").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's trained model, as provided by Hadap, to be based on parametric curves as taught by Harvill, especially as Harvill teaches utilizing as such for learned data, in order to provide customization ([0004]), and as it is known in the art that Hadap's t-SNE can be of parametric curves (see extrinsic evidence Kawase et al NPL).
Regarding Claim 35, modified Surville teaches all the claimed limitations as discussed above in Claim 27.
Harville further teaches wherein the parametric curve is a Bezier curve ([0144]).
As best understood in light of the 112(b) rejections-- Claim(s) 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap, as applied to the FIRST REJECTION above, further in view of Amico et al (USPN 7426302), herein Amico.
Regarding Claim 29, modified Surville teaches all the claimed limitations as discussed above in Claim 19.
Modified Surville further teaches wherein the pieces of pattern paper data are vector data expressing a plurality of coordinate points (see Fig. 10; Col. 15 Line 14, 24-30 "taxonomy 11 comprises…information about the orientation of variation in the dimensions of the garment piece…this information is given by a vector comprising an origin point 22, a direction point 23"; Col. 13 Lines 45-48 “The grader selects the garment scale 10 that is to be applied, corresponding to the intended population and/or to the garment in question, together with the taxonomy 11 corresponding to trousers").
Surville does not explicitly teach that the generated pattern paper data are also vector data expressing a plurality of coordinate points.
Amico teaches the generated pattern paper data are vector data expressing a plurality of coordinate points (initial/pieces being vector-- see Fig. 3; Col. 15 Lines 55-56 "step 220, where the data at step 210 is vectorized"; end/generated data being vector-- see Fig. 8; Col. 18 Lines 26-30 "method 220a proceeds to step 225a…to indicate that the vector has been completed"; see Fig. 15; Col. 20 Lines 19-21 "it is assumed that the vectorization process results in the generation of the vector space in FIG. 15, which consists of a vectorized image 38a4 of image 38a3"; see Fig. 4; Col. 20 Lines 37-58 "Method 200a then advances to step 246a, where the largest polygon is labeled as a "pattern boundary". In the present example, since the largest polygon is the polygon formed by vectors forming element 78a4, pattern element 78a4 is labeled 'pattern boundary'. Method 200a then proceeds to step 250a, where the pattern boundary is digitized in a predetermined format. In the present example, pattern element 78a4 is digitized as a pattern boundary, in a format compatible with various CAD and/or CAM systems such as Gerber, Lectra, Investronica, ASTM/AAMA-DXF, Optitex, Polygon and PAD"; Col. 4 Lines 7-10 "present invention provides a garment pattern digitization system that can automatically import a digital image of a garment pattern (raster data), and then export the information to a DXF/AAMA-formatted file (vector data)"; for coordinate points --Col. 15 Lines 56-61 "A vector is a quantity that has magnitude and direction. It can be represented by a straight line, with magnitude being represented by the length of the line and direction being represented by the orientation of the line in space. In a present embodiment, raster data, consisting of a set of pixels is converted into a set of vectors", wherein pixels are coordinate points ,see extrinsic evidence Ishikawa et al USPN 7031527; nevertheless, Col. 35 Lines 36-38 "now to Fig. 44, another specific implementation of method 200, the performance of ...a fully-automatic grade rule number assignment function"; Col. 35 Lines 47-49 "a list of rectangular coordinates (x,y) of turn points and notch points is received and labeled as grade points"; Col. 36 Line 65-Col. 37 Line 3 "referring again to Fig. 45...at step 206p, the vectorized image of the pattern piece is received...obtained from a variety of methods such as method 220 described previously"; Col. 37 Lines 7-9 "algorithm can be used to analyze the shape of the pattern piece to be processed and find a match within library of quadrant layouts").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's data to be vector data of coordinate points as taught by Amico as a known arrangement of data for grading garments (abstract).
As best understood in light of the 112(b) rejections-- Claim(s) 33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818) and Hadap et al (USPN 12070093), herein Hadap, as applied to the FIRST REJECTION above, further in view of Jorgensen (NPL).
Regarding Claim 33, modified Surville teaches all the claimed limitations as discussed above in Claim 19.
Modified Surville does not explicitly teach wherein the trained model is generated with Gaussian Process Latent Variable Model (GPLVM).
However, Hadap of modified Surville teaches wherein the trained model can be generated with t-SNE (Col. 6 Lines 22-25 "at block 404, the computing system may learn an embedding function configured to generate a low-dimensional embedding for any high-dimensional body representation that is provided as input to the embedding function"; Col. 9 Lines 22-25 "this low-dimensional embedding may be derived, in some embodiments, from higher-dimensional body parameters in conjunction with dimensionality reduction techniques such as t-SNE").
Jorgensen teaches wherein a trained model can be generated with t-SNE or GPLVM ("5. Discussion...GPLVM...are fundamental parts of decision-making pipelines, whereas t-SNE is a valuable visualization technique").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's grading model, provided by Hadap, to be that of Jorgensen’s GPLVM in order to assist with decision making, especially as both models are in the same art of endeavor as high-to-low dimension models (see extrinsic evidence Li et al NPL for GPLVM being as such).
SECOND REJECTION: As best understood in light of the 112(b) rejections-- Claim(s) 28, 36, 38 is/are rejected under 35 U.S.C. 103 as being unpatentable over Surville (USPN 5757661), in view of Nomura (JPH 11286818), Hadap et al (USPN 12070093), herein Hadap, and Ichinose (USPN 10872184).
Regarding Claim 28, Surville teaches a clothing system (see rejection of Claim 19) comprising:
Modified Surville teaches according to claim 19 (see rejection of claim 19).
Modified Surville does not explicitly teach means for manufacturing clothing based on the generated pattern paper data output.
Ichinose teaches means for manufacturing clothing based on the generated pattern paper data output (see Fig. 4; Col. 4 Line 42 "paper pattern outer shape data 30 for sewing"; Col. 5 Lines 62-67 "in an actual sewing operation, the stitching pitch changes according to the feeding speed of a sewing machine, enabling the stitching pitch to be freely input as in this embodiment allows representation of the same stitching pitch as that for an actual product"; Col. 9 Lines 5-8 "present invention ...applicable to the creation of a sewing analysis model of a general product involving sewing, for example, fabric for clothes").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's clothing pattern paper data, provided by Nomura, to be manufactured with a sewing machine as taught by Ichinose as a known arrangement for manufacturing clothing pattern paper data.
As such, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that modified Surville teaches a clothing manufacturing system (in light of Ichinose).
Regarding Claim 36, modified Surville teaches all the claimed limitations as discussed above in Claim 28.
Ichinose further teaches wherein the means for manufacturing clothing includes a machine for clothing manufacturing, or a cutting machine and a sewing machine (see rejection of Claim 28 for sewing machine).
Regarding Claim 38, Surville teaches a program for outputting pattern data (it is noted that a recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus satisfying the claimed structural limitations; abstract "means for automatically generating grading rules"; Col. 1 Lines 3-4 "computer system for grading garments"; Col. 13 Lines 50-54 "On the basis of this data, the grading software 12 works out grading 9 for the garment file 8. This step is entirely automatic, insofar as the software computes and/or applies the rules to the various characteristic points"; Col. 13 Lines 41-48 "grader selects the garment to be graded. The grading software 13 loads…with the shapes 7 of all of the pieces of the garment to be graded. The grader selects the garment scale 10 that is to be applied, corresponding to the intended population and/or to the garment in question, together with the taxonomy 11 corresponding to trousers", wherein Fig. 7 shows pattern data; wherein at least software indicate program),
the program being executed in a computer (Col. 1 Lines 3-4),
the program including:
receiving size information (Col. 13 Lines 41-48 "grader selects the garment to be graded. The grading software 13 loads…with the shapes 7 of all of the pieces of the garment to be graded. The grader selects the garment scale 10 that is to be applied, corresponding to the intended population"; wherein garment scale indicates size info);
generating, based on the size information, pattern data of clothing having a size suitable for a size indicated by the size information using automation (see Fig. 10; generate-- Col. 16 Lines 15-18 "Increments for a point and for all sizes are computed, thereby enabling the grading rule 30 for the point to be worked out. Thus, the set of grading rules for all of the characteristic points of the garment are worked out"; Col. 13 Lines 50-54 "On the basis of this data, the grading software 12 works out grading 9 for the garment file 8. This step is entirely automatic, insofar as the software computes and/or applies the rules to the various characteristic points"),
using a computer to determine a relationship between pieces of pattern paper data of a plurality of pieces of clothing of a type same as a specific clothing (relationship between claimed pieces-- Col. 16 Lines 15-18 "Increments for a point and for all sizes are computed, thereby enabling the grading rule 30 for the point to be worked out. Thus, the set of grading rules for all of the characteristic points of the garment are worked out"; wherein all sizes is claimed pieces).
Surville does not explicitly teach a non-transitory computer-readable storage medium storing the program,
that the pattern data is pattern paper data,
outputting the generated pattern paper data,
Nomura teaches a storage medium storing a program for outputting pattern paper data (abstract "paper pattern shape changed so as to satisfy the constraint condition is outputted from an outputting means M4"; [0001] "invention relates to a pattern making method and apparatus…for automatically grading (enlarging/reducing) data of a...pattern...according to the body size"; [0032] "computer program for the pattern making method of the present invention can also be provided on a medium such as a CD-ROM"),
pattern paper data (abstract "paper pattern shape changed so as to satisfy the constraint condition is outputted from an outputting means M4"; [0001] "invention relates to a pattern making method and apparatus…for automatically grading (enlarging/reducing) data of a...pattern...according to the body size"; [0013] “by modifying the shape data…possible to create patterns for clothing with different designs”; [0032] "computer program for the pattern making method of the present invention can also be provided on a medium such as a CD-ROM"),
outputting the generated pattern paper data (see above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville’s pattern data to be of paper and to have output means and program storage medium as taught by Nomura as a known arrangement to provide pattern shape for clothing after size change/grading, which both Surville and Nomura are directed to.
Surville does not explicitly teach that the automation/computer is using a trained model.
Hadap teaches that the generating pattern data of clothing having a size suitable for a size indicated by the size information using automation uses a trained model (for size information-- Col. 5 Lines 1-4 "body 302 may be generated from newly provided body measurements of a particular customer who is interested in purchasing a custom fitted garment"; for using size information into a trained model to generate -- see Fig. 3; Col. 4 Line 65-Col. 5 Line 1 "resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 5 Lines 9-17 "reference bodies 310, 312, and 314 may have previously had custom designed garment patterns 320, 322, and 324, respectively, designed to fit them...a new custom garment pattern 350 may then be generated by the system by blending or interpolating garment parameters...of the selected sample patterns 320, 322, and 324"; for Fig. 3 being from a trained model-- Col. 5 Lines 19-21 "Fig. 4A is a flow diagram of an illustrative method 400A for selecting reference sample bodies for creation of associated garment patterns"; Col. 5 Lines 25, 49-53 "illustrative method 400A begins at block 402... the set of bodies may be generated using the SMPL model based in part on captured body measurements of real customers (e.g., in order to reflect the general range of body measurements, BMI, weight, height, etc. of a given customer base)"; Col. 5 Lines 63-65 "SMPL model enables training its entire model from aligned 3D meshes of different people in different poses");
the trained model including a model obtained by learning a relationship between pieces of pattern data of a plurality of pieces of clothing of a type same as a specific clothing (see Fig. 3; Col. 4 Line 65-Col. 5 Line 1 "resulting custom garment pattern 350 generated based on garment patterns previously created for the neighboring reference bodies"; Col. 5 Lines 1-4 "body 302 may be generated from newly provided body measurements of a particular customer who is interested in purchasing a custom fitted garment"; Col. 5 Lines 9-17 "reference bodies 310, 312, and 314 may have previously had custom designed garment patterns 320, 322, and 324, respectively, designed to fit them...a new custom garment pattern 350 may then be generated by the system by blending or interpolating garment parameters...of the selected sample patterns 320, 322, and 324"; for plurality-- see 320, 322, 324 that are same type/design as the desired garment; for Fig. 3 being from a trained model—see aforementioned).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Surville's computer to be a trained model as taught by Hadap as known to utilize a trained model to generate pattern data in order for more accurate fits across a larger variety of sizes (Col. 1 Lines 6-23; Col. 2 Lines 7-14).
As such, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that modified Surville teaches a method for outputting pattern paper data.
Surville does not explicitly teach that the storage medium is a non-transitory computer-readable storage medium,
the computer including a processor,
the program causing the processor to perform processing.
Ichinose teaches storage medium is a non-transitory computer-readable storage medium (Col. 9 Lines 15-20 "program of the sewing analysis system according to the above aspects can be installed into a computer by being provided in the form of being stored in a computer-readable recording medium...storage medium is, for example, a non-transitory recording medium and a preferred example is an optical recording medium such as a CD-ROM"; see Fig. 4; Col. 4 Line 42 "paper pattern outer shape data 30 for sewing"),
the computer including a processor (Claim 1 in Col. 12 Lines 6-14 "sewing analysis system...comprising…one or more processors configured to execute the computer-readable instructions"; Col. 12 Lines 1-3 "designing a flat paper pattern shape for ...textiles"),
the program causing the processor to perform processing (Claim 1 in Col. 12 Lines 6-14 "sewing analysis system...comprising…one or more processors configured to execute the computer-readable instructions”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify obvious to modify Surville's CD-ROM program storage, as taught by Nomura, to be stored on a non-transit storage medium as taught by Ichinose, and to modify Surville’s computer program to be of a processor as taught by Ichinose, as a known arrangement for pattern paper data.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and can be used to formulate a rejection if necessary: Terai et al (USPN 11725314) directed to grading by learning the relationship between a plurality of pieces; Goldstone (USPN 11700899) directed to machine learning grading; Oh et al (USPN 11151786), Choche et al (USPN 11112772), Wilcox (US Publication 2022/0087352) directed to components; Gardiner et al (US Publication 2008/0312765) directed to reliability; Yeung et al (USPN 12439986) directed to seam allowance; Doyle (USPN 391392) directed to parametric curve.
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/GRACE HUANG/Primary Examiner, Art Unit 3732
