DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Received 07/04/2026
Claim(s) 1-3 and 5-15 is/are pending.
Claim(s) 1, 11, and 14-15 has/have been amended.
Claim(s) 4 has/have been cancelled.
The 35 USC § 101 rejection to claim(s) 14 have been withdrawn in view of the amendments received on 07/04/2026.
The 35 U.S.C § 103 rejection to claim(s) 1-3 and 7-15 have been fully considered in view of the amendments received on 07/04/2026 and are fully addressed in the prior art rejection below.
Response to Arguments
Received 07/04/2026
Regarding independent claims 1, 11, and 15:
Applicant’s arguments (Remarks, Page 10: ¶ 4), filed 07/04/2026, with respect to the rejection(s) of claim(s) 1, 11, and 15 under 35 U.S.C § 103 have been fully considered and are persuasive. Wherein, the subject matter of “sample points extracted along an outline of each of the patterns” not full addressed within the applied prior art. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of Meador et al. (US PGPUB No. 20230252747 A1), in view of Cirio et al. (US PGPUB No. 20230334772 A1), in view of Ma (US PGPUB No. 20210227912 A1), in view of Xu et al. (US PGPUB No. 2023036722292 A1), and further in view of Santesteban Garay et al. (US PGPUB No. 20240331251 A1).
Applicant’s arguments (Remarks, Page 11: ¶ 1), filed 07/04/2026, with respect to the rejection(s) of claim(s) 1 under 35 U.S.C § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of the prior art as mentioned above.
Applicant’s arguments (Remarks, Page 12: ¶ 1), filed 07/04/2026, with respect to the rejection(s) of claim(s) 1 under 35 U.S.C § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of the prior art as mentioned above.
Applicant’s arguments (Remarks, Page 12: ¶ 2 to Page 13: ¶ 1), filed 07/04/2026, with respect to the rejection(s) of claim(s) 1 under 35 U.S.C § 103 have been fully considered and are persuasive. However, Applicant fails to view Cirio et al. teaches obtaining pattern information (i.e. input model : sewing order, other assembly information, and/or mapping of fabric pieces) for each of patterns of a garment, the pattern information (i.e. input model) representing a configuration of each of the patterns (i.e. assembly information) and including information (i.e. seam types, stitching types) about sample points extracted along a partial outline of each of the patterns (Cirio; [¶ 0037]; moreover, “… prepare the model for seam processing. Further, seamline-space optimizations may also be performed 303 on these pre-processed inputs, for example to optimize seam normals so as to enforce space continuity prior to seam processing. The seam processing begins with the first seam as identified in the seam data 301a, for example, following the given assembly instructions. For the given seam, all fabric nodes that fall within the seamline area are computed in seamline-space, capturing 304 all fabric nodes that fall within the seamline area. The identified seam is then applied 305 to the captured nodes, folding and deforming the nodes following the seam type” [¶ 0038 and ¶ 0040-0041]).
Additionally, the subject matter of “predicting sewing information about the patterns based on an embedding vector for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information, the sewing information defining a relationship between sewing lines of at least a subset of the patterns that are to be sewn together” corresponding to seams that joins more than two fabric pieces together (Cirio; [¶ 0040-0041 and ¶ 0052-0054]). Moreover, Cirio et al. teaches seam application (Cirio; [¶ 0062-0063]), stitch computing (Cirio; [¶ 0070-0071]), and pattern space optimizations (Cirio; [¶ 0077-0078 and ¶ 0080]).
Yet, the term “outline” is interpreted as being further limiting than to mean one or two sides of a segment/piece as taught by Cirio et al., to mean surrounding all sides of a segment/piece. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of the prior art as mentioned above.
Applicant’s arguments (Remarks, Page 13: ¶ 3 to Page 14: ¶ 1), filed 07/04/2026, with respect to the rejection(s) of claim(s) 1 under 35 U.S.C § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of the prior art as mentioned above.
Applicant’s arguments (Remarks, Page 15: ¶ 3), filed 07/04/2026, with respect to the rejection(s) of claim(s) 11 and 15 under 35 U.S.C § 103 have been fully considered and are persuasive due claim 11's and claim 15's similarity to claim 1. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of the prior art as mentioned above.
Regarding dependent claims 2, 3, 7-10, and 12-14:
Applicant’s arguments (Remarks, Page 15, ¶ 4), filed 07/04/2026, with respect to the rejection(s) of claim(s) 2, 3, 7-10, and 12-14 under 35 U.S.C § 103 have been fully considered and are persuasive, due the dependency upon claims 1, 11, and 15 respectively. Therefore, the rejection has been withdrawn, necessitated by Applicant's amendments. However, upon further consideration, a new ground(s) of rejection is made in view of the prior art as mentioned above.
Applicant's arguments filed 07/04/2026have been fully considered but they are not persuasive; as expressed below.
Regarding independent claims 1, 11, and 15:
Applicant argues (Remarks, Page 11, ¶ 1), “Per claim 1, sample points are extracted along an outline of each garment pattern, and pattern information representing a configuration of each pattern is obtained from those sample points. The pattern information is applied to a pattern embedding model that comprises a transformer encoder and is trained to estimate a correlation between input pattern information, so as to obtain an embedding vector for each pattern. The sewing information that is predicted defines a relationship between sewing lines of at least a subset of the patterns that are to be sewn together, and a sewing line of a pattern pair is obtained by applying, to a transformer decoder, an embedding vector pair corresponding to the pattern pair. Claim 1 thus recites a specific neural-network pipeline in which a transformer encoder produces per-pattern embedding vectors and a transformer decoder consumes an embedding vector pair for a pattern pair to predict the sewing relationship between the patterns.”
The Examiner disagrees. Applicant’s arguments fail to view the teachings of Cirio et al., wherein the seam stitching involves points along the outline of each garment (Cirio; pattern-space geometries of all fabric pieces [¶ 0037-0038, ¶ 0077, and ¶ 0080]; additionally, “The bounding region of a segment includes the area swiped by the segment when extruded along the endpoint normals by a distance defined by the seam type” [¶ 0056-0058]).
Additionally, the Applicant infers differences between the applied prior art and the subject matter of “predicting”, “transformer encoder”, and “transformer decoder”, and “embedding vector pair”, however Applicant fails to clearly indicate the manner in which the prior art specifically differs. Although, the newly proposed amendments further limits the elements mentioned above, Applicant fails to view the teachings of Cirio et al. regarding the points along the outline of each garment as addressed above.
Therefore, Applicant’s arguments above are not persuasive.
Applicant argues (Remarks, Page 13, ¶ 2), that “Santesteban-Garay does not disclose, teach, or suggest a model that predicts a sewing relationship, or that obtains a sewing line of a pattern pair, by applying an embedding vector pair to a transformer decoder, as recited in amended claim 1.”
The Examiner disagrees. Applicant’s arguments fail to view the teachings of Meador et al., wherein deep learning techniques and methods employed by the landmark extraction to employ any selected prediction or detection technique for detecting and extracting specific landmark features that are present within the garment segment data (Meador; [¶ 0066]). And, the pattern generation unit predicts the landmarks in the garment segments by processing the detected garment segments and associated dimensions inferred from the spatial relationships of landmarks features by employing a suitable deterministic pattern making technique (Meador; [¶ 0067]).
Wherein, the machine learning as taught by Meador et al. is modified by Santesteban Garay et al. to incorporate further detail of an encoder and decoder within a learning structure.
Therefore, Applicant’s arguments above are not persuasive.
Applicant argues (Remarks, Page 14, ¶ 2), that “… even if Meador, Cirio, Santesteban-Garay, and Kim were combined as proposed in the Office Action, the resulting combination would still not yield the features recited in amended claim 1. Meador's garment rendering operates on landmarks that are extracted to produce the patterns, not on sample points extracted along an outline of each pattern, and Meador does not predict sewing information. Cirio processes given seam information through geometric operations rather than predicting a sewing relationship from pattern information. Santesteban-Garay's encoder/decoder arrangement, where present, outputs deformation information rather than a sewing line of a pattern pair. Kim's vectors are geometric position vectors used for exploded-view spacing rather than embedding vectors, and Kim's recited ‘transformer’ is a generic processor or processor module rather than a transformer decoder of a neural network. The combination of these references therefore does not result in a pipeline in which a transformer encoder of a pattern embedding model outputs per-pattern embedding vectors and a transformer decoder consumes an embedding vector pair for a pattern pair to obtain a sewing line for that pattern pair, as recited in amended claim 1.”
The Examiner disagrees. Applicant’s arguments fail to view the rejection as a whole. Although, an explicit term of prediction is silent within Santesteban Garay et al. the calculation/estimation of seam optimization teaches a sewing relationship from pattern information (Santesteban-Garay; pattern space optimizations [¶ 0077-0080]) and Meador et al. teaches a neural network’s ability to perform prediction capabilities (Meador; [¶ 0066-0067]). Even further, the neural network taught by Meador et al. is modified to be configured to incorporate the capabilities of encoding/decoding (otherwise known as VAE) for transforming data (Santesteban-Garay; [¶ 0042, ¶ 0045, and ¶ 0072-0074]).
Therefore, Applicant’s arguments above are not persuasive.
Applicant argues (Remarks, Page 14, ¶ 3 to Page 15, ¶ 1), “Additionally, the proposed combination of four references, each directed to a different aspect of garment modeling, to assemble the specific transformer encoder and transformer decoder pipeline of amended claim 1 reflects impermissible hindsight reasoning. The Office Action provides no articulated rationale, apart from the asserted individual benefits of each reference, for why a person of ordinary skill in the art would have selected Kim's exploded-view methodology, recharacterized Kim's processor as a transformer decoder of a neural network, and integrated it with Santesteban-Garay's deformation-predicting arrangement and Cirio's geometric seam processing on top of Meador's landmark-based garment rendering, so as to arrive at the recited pipeline. The only roadmap for assembling these disparate references into the recited pipeline is the present application's own disclosure, which is the hallmark of impermissible hindsight (see MPEP § 2142).”
The Examiner disagrees. Wherein, 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).
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).
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.
Claim(s) 1-3 and 7-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Meador et al., US PGPUB No. 20230252747 A1, hereinafter Meador, in view of Cirio et al., US PGPUB No. 20230334772 A1, hereinafter Cirio, in view of Ma, US PGPUB No. 20210227912 A1, hereinafter Ma, in view of Xu et al., US PGPUB No. 2023036722292 A1, hereinafter Xu; and further in view of Santesteban Garay et al., US PGPUB No. 20240331251 A1, hereinafter Santesteban-Garay.
Regarding claim 15, Meador discloses a clothing simulation apparatus (Meador; a clothing simulation apparatus (i.e. garment rendering system) [¶ 0046], as illustrated within Fig. 1; moreover, electronic/computer device [¶ 0088-0089], as illustrated within Fig. 10; additionally; the garment rendering system comprises a simulation engine [¶ 0050]) comprising:
one or more processors (Meador; clothing simulation apparatus (i.e. garment rendering system) [as addressed above] comprises one or more processors [¶ 0061 and ¶ 0079-0080]; moreover, computer processor [¶ 0089-0090 and ¶ 0092]); and
memory storing instructions thereon (Meador; clothing simulation apparatus (i.e. garment rendering system) [as addressed above] comprises memory storing instructions thereon [¶ 0061 and ¶ 0079-0080]; moreover, computer program [¶ 0086]; and moreover, computer memory [¶ 0090, ¶ 0092, and ¶ 0094-0096]), the instructions when executed by the one or more processors cause the one or more processors (Meador; the instructions [as addressed above] when executed by the one or more processors cause the one or more processors to implement [¶ 0079-0081]; moreover, programmable processors executing a computer program to perform functions [¶ 0089-0092]) to:
obtain pattern information for each of patterns of a garment (Meador; processors [as addressed above] (is/are configured) to obtain pattern information for each of patterns of a garment [¶ 0063-0064]; wherein, the landmark extraction unit can employ any selected prediction or detection technique for detecting and extracting specific landmark features that are present within the garment segment data in order to characterize the visible part parameters [¶ 0066-0067]), the pattern information including information about sample points extracted from each of the patterns (Meador; the pattern information including information about sample points extracted from each of the patterns [¶ 0066-0067]; wherein, garment pattern determination and mesher are associated with generating/obtaining pattern information [¶ 0063], as illustrated within Fig. 3);
predict sewing information about the patterns based on an embedding vector for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information (Meador; processors [as addressed above] (is/are configured) to predict implicit sewing information (given landmark features and pattern determination further corresponding to garment pattern) about the patterns [¶ 0063-0064 and ¶ 0066-0067] based on an embedding vector for each of the patterns obtained by applying the pattern information to an implicit pattern embedding model trained (given a neural network and vectors) to estimate a correlation between input pattern information [¶ 0064]; additionally, a simulation engine encodes the virtual garment data in relation with generating a simulation [¶ 0073 and ¶ 0075]; in other words, computer simulations implicitly correspond to perform predictions given a calculated or estimation of an outcome based on prior and/or current information); and
based on the sewing information, generate a simulation result of the garment (Meador; processors [as addressed above] (is/are configured) to generate a simulation result of the garment [¶ 0072-0074] based on the implicit sewing information [as addressed above], as illustrated within Fig. 7A-B; wherein, virtual garment data (corresponding to sewing info) is used to generate a simulation [¶ 0063 and ¶ 0070-0071]), wherein the pattern embedding model comprises a transformer (Meador; the implicit pattern embedding model (given a NN and conversion into one or more word vectors) comprises a transformer (corresponding to virtual garment generation unit) [¶ 0064]; moreover, the simulation engine can include a tailor unit for receiving the virtual garment data and encoding the virtual garment data with the garment image data to form encoded garment data, a solver unit for receiving the encoded garment data and generating based thereon the simulated garment data, and a feedback loop for feeding back the simulated garment data to the tailor unit for further processing thereby [¶ 0022]; additionally, a simulation engine encodes virtual garment data using a NN [¶ 0073-0075]), and wherein, to predict the sewing information, the instructions cause the one or more processors (Meador; predicting the sewing information (corresponding to simulation of sewing) [as addressed above], the instructions cause the one or more processors [¶ 0061 and ¶ 0079-0080]) to:
obtain information indicating a segment extracted from the patterns, to a transformer (Meador; the instructions cause the one or more processors [as addressed above] to obtain information indicating a segment of a pattern pair extracted from the patterns [¶ 0066-0067] to a transformer (corresponding to a simulation engine) [¶ 0050 and ¶ 0073] to predict the implicit sewing information [as addressed above]; wherein, garment pattern represents a 2D shape made of vertices, curves and lines, and the garment pattern can be used as guidance to cut pieces from a sheet of fabric, which can then be sewn to other parts to create the final garment [¶ 0042]).
Meador further fails to disclose sample points extracted along an outline of each of the patterns;
the model comprises a transformer encoder; and
a pattern pair extracted from the patterns by applying, to a transformer decoder, an embedding vector pair corresponding to the pattern pair.
However, Cirio teaches to:
obtain pattern information for each of patterns of a garment (Cirio; obtaining pattern information for each of patterns of a garment [¶ 0037-0038 and ¶ 0040-0041]), the pattern information representing a configuration of each of the patterns and including information about sample points extracted along an outline of each of the patterns (Cirio; the pattern information representing a configuration of each of the patterns and including information [¶ 0037-0038] about sample points extracted along a part or partial outline of each of the patterns [¶ 0040-0041 and ¶ 0052-0054], as illustrated within Fig. 8; moreover, sewing order, other assembly information, and/or mapping of fabric pieces [¶ 0037-0038]; and moreover, seamline-space optimizations involves seam processing identifying seams in the seam data given assembly instructions [¶ 0038]; wherein, all fabric nodes that fall within the seamline area are computed in seamline-space and the identified seam is then applied to the captured nodes, folding and deforming the nodes following the seam type [id.]; even further, the process of assembly of fabric panels to generate a garment involves the stitching together of the fabric panels according to specific seam types and stitch types in a given order [¶ 0040]);
predict sewing information about the patterns based on an optimization for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information (Cirio; implicitly predicting (given a model; moreover a computer model, as taught by Cirio, is implicitly a prediction given a model provides a calculated, estimation, and/or guess of an outcome, based on current and/or prior information) sewing information [¶ 0037-0038] about the patterns based on an optimization for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information [¶ 0040-0041 and ¶ 0052-0054]; moreover, a trained pattern embedding model implicitly corresponds to the modules of optimization and processing [¶ 0037-0038], as illustrated within Fig. 3; wherein, at least of the modules (e.g. seamline space optimizations) implicitly corresponds to a trained pattern embedding model (corresponding to a non-training data model related to sewing patterns), given rotation and/or alignment of seam segments in relation with connecting two chunks (i.e. optimization for multi-chunk seams) [¶ 0053-0054], modeled computation of the stitching [¶ 0070-0071], and/or pattern space optimization (associated with minimizing distortion) [¶ 0077-0080], as illustrated within Fig. 8 and Figs. 9A-B; additionally, seam info applied to a garment model [¶ 0062]), the sewing information defining a relationship between sewing lines of at least a subset of the patterns that are to be sewn together (Cirio; the sewing information defining a relationship between sewing lines of at least a subset (i.e. geometry, stitch type, assembly for sewing) of the patterns that are to be sewn together [¶ 0052-0054, ¶ 0070-0071, and ¶ 0077]; wherein, defining a profile space in relation with properties of a seam that are applied to a model [¶ 0062-0064]; additionally, sewing order or garment assembly information [¶ 0033-0034 and ¶ 0036-0038]);
based on the sewing information, generate a simulation result of the garment (Cirio; generating a simulation (i.e. garment model and/or 3D model) result of the garment based on the sewing information [¶ 0082 and ¶ 0084-0085]; wherein, generating a 3D model of a garment [¶ 0034, and ¶ 0036-0038] corresponding to simulations [¶ 0026 and ¶ 0028]; moreover, the modeling of seams and the connection thereof [¶ 0077 and 0080], as illustrated within Figs. 9A-B); and
wherein, to predict sewing information (Cirio; to implicitly predict (given the modeling of an outcome) sewing information [as addressed above]) wherein the instruction cause the one or more processors (Cirio; the instruction causes the one or more processors [¶ 0095-0096]) to:
obtain information indicating a sewing line of a pattern pair extracted from the patterns (Cirio; the processor(s) [as addressed above] configured to obtain information indicating a sewing line [¶ 0037-0038 and ¶ 0040-0041] of a pattern pair extracted from the patterns ¶ 0052-0054], as illustrated within Fig. 8; moreover, sewing order, other assembly information, and/or mapping of fabric pieces [¶ 0037-0038]).
Meador and Cirio are considered to be analogous art because both pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce computer-aided design/manufacturing virtualization.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador, to incorporate obtain pattern information for each of patterns of a garment, the pattern information representing a configuration of each of the patterns and including information about sample points extracted along an outline of each of the patterns; predict sewing information about the patterns based on an optimization for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information, the sewing information defining a relationship between sewing lines of at least a subset of the patterns that are to be sewn together; based on the sewing information, generate a simulation result of the garment; and wherein, to predict sewing information wherein the instruction cause the one or more processors to: obtain information indicating a sewing line of a pattern pair extracted from the patterns (as taught by Cirio), in order to provide realistic modeling of garments and fabrics (Cirio; [¶ 0002-0003 and ¶ 0010]).
Meador as modified by Cirio fails to explicitly disclose sample points extracted along an outline of each of the patterns (Wherein, the term outline is interpreted as surrounding of a perimeter/boundary completely on all sides/edges);
a transformer encoder; and
a pattern pair extracted from the patterns by applying, to a transformer decoder, an embedding vector pair corresponding to the pattern pair.
However, Ma teaches to:
obtain pattern information for each of patterns of a garment (Ma; obtaining pattern information for each of patterns of a garment [¶ 0073-0074]; additionally, pattern pieces [¶ 0053-0054], and an automatic sewing apparatus marking pattern pieces with tags by predicting a part from the pattern shape and position [¶ 0055]), the pattern information representing a configuration of each of the patterns and including information about sample points extracted along an outline of each of the patterns (Ma; the pattern information [as addressed above] representing a configuration of each of the patterns and including information about sample points extracted along an outline of each of the patterns [¶ 0069-0072], as illustrated within Fig. 6 and Fig. 7; moreover, nodes located on an outline of the pattern pieces and segments [¶ 0046]); and
the patterns based on an embedding vector for each of the patterns obtained by applying the pattern information to a pattern embedding model to estimate a correlation between input pattern information (Ma; the patterns based on an embedding vector (i.e. vector of data values) for each of the patterns [¶ 0046-0048] obtained by applying the pattern information to a pattern embedding model (i.e. pattern data model) to estimate a correlation between input pattern information [¶ 0053-0055]; wherein, the automatic sewing apparatus output pattern pieces including the sewing line generated or sew pattern pieces along the sewing line [¶ 0049]; and wherein, nodes correspond to a vertex on the outline which represents the shape of the pattern piece [¶ 0058-0059]).
Meador in view of Cirio and Ma are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce computer-aided design/manufacturing virtualization.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, to incorporate to: obtain pattern information for each of patterns of a garment, the pattern information representing a configuration of each of the patterns and including information about sample points extracted along an outline of each of the patterns; and the patterns based on an embedding vector for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information (as taught by Ma), in order to provide reduced consumption of human resources by automatic processing of garments and providing computerized modeling environment to a user (Ma; [¶ 0002-0003]).
Meador as modified by Cirio and Ma fails to disclose a transformer encoder; and
a pattern pair extracted from the patterns by applying, to a transformer decoder, an embedding vector pair corresponding to the pattern pair.
However, Xu teaches the patterns based on an embedding vector for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information (Xu; the patterns based on an embedding vector for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information [¶ 0039 and ¶ 0041-0042]; moreover, garment assembly rendering [¶ 0050-0051], as illustrated within Fig. 4A; wherein; estimating a correlation between input pattern information corresponds to one or more steps [¶ 0055-0057] and placement of segments [¶ 0059-0062]; in other words, the computer is configured to understand and analyze pieces of clothing (e.g. sleeve, pocket, collar, front, back, cuff) and perform placements and/or adjustments based on a relationship between pieces to optimize production [id.]; and wherein trained learning is utilized [¶ 0069-0070]); and
obtain information indicating a sewing line of a pattern pair extracted from the patterns by applying, to an optimization, an embedding vector pair corresponding to the pattern pair (Xu; obtain information indicating a sewing line (i.e. sewing edge or cutting line) of a pattern pair extracted from the patterns [¶ 0045-0048], as illustrated within Fig. 4A, by applying an embedding vector pair (i.e. data value of a segment/patch pair) corresponding to the pattern pair to an optimization process [¶ 0040-0042 and ¶ 0055-0056]; wherein, a feature vector is provided to a learning system [¶ 0069]; additionally, metadata indicating garment type and/or templating [¶ 0038-0039]).
Meador in view of Cirio and Ma, and Xu are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce computer-aided design/manufacturing user interface.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio and Ma, to incorporate the patterns based on an embedding vector for each of the patterns obtained by applying the pattern information to a pattern embedding model trained to estimate a correlation between input pattern information; and obtain information indicating a sewing line of a pattern pair extracted from the patterns by applying, to an optimization, an embedding vector pair corresponding to the pattern pair (as taught by Xu), in order to provide reduced consumption of resources by optimizing the processing garments using a computerized environment (Xu; [¶ 0001-0002 and ¶ 0008]).
Meador as modified by Cirio, Ma, and Xu fails to disclose a transformer encoder; and
a transformer decoder.
However, Santesteban-Garay teaches to:
generate a simulation result of the garment, wherein the pattern embedding model comprises a transformer encoder (Santesteban-Garay; generate a simulation result of the garment [¶ 0034 and ¶ 0038-0039] wherein the pattern embedding model comprises a transformer encoder (i.e. generative module) [¶ 0041-0042 and ¶ 0045]; additionally, pre-processing pipeline [¶ 0040]), and wherein, to predict the information, the instructions cause the one or more processors (Santesteban-Garay; the instructions cause the one or more processors to predict the information [¶ 0060 and ¶ 0069]; moreover, predict encoded garment [¶ 0036 and ¶ 0045]) to:
obtain information indicating a deformation by applying, to a transformer decoder, a pattern pair (Santesteban-Garay; processors [as addressed above] (configured) to obtain information indicating a deformation corresponding to the pattern pair to a transformer decoder [¶ 0042 and ¶ 0045]; wherein, within a VAE output of an encoder is provided to a decoder [¶ 0072-0075]; moreover, garment model [¶ 0054 and ¶ 0072] utilizing a vector space (i.e. vector pair) for calculations [¶ 0076-0078]).
(In other words, Santesteban-Garay teaches a neural network or machine learning model configured to incorporate an encoder/decoder and/or generator/discriminator [as addressed above])
Meador in view of Cirio, Ma, and Xu and Santesteban-Garay are considered to be analogous art because they pertain to generating and/or managing data in relation with providing modeling data to a user, wherein one or more computerized units are utilized in order to produce computer-aided design/manufacturing modeling.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, Ma, and Xu, to incorporate to: generate a simulation result of the garment, wherein the pattern embedding model comprises a transformer encoder, and wherein, to predict the information, the instructions cause the one or more processors to: obtain information indicating a deformation by applying, to a transformer decoder, a pattern pair (as taught by Santesteban-Garay), in order to provide simulations of clothing/garments that require less computationally intensive (Santesteban-Garay; [¶ 0004-0005 and ¶ 0007-0008]).
Regarding claim 1, the rejection of claim 1 is addressed within the rejection of claim 15, due to the similarities claim 1 and claim 15 share, therefore refer to the rejection of claim 15 regarding the rejection of claim 1. Although, claim 1 and claim 15 may not be identical, they are considerably comparable or substantially equivalent given their overlapping subject matter. Thus, it is reasonable to reject claim 1 based on the teachings and rational in relation with the prior art within the rejection of claim 15.
Regarding claim 2, Meador in view of Cirio, Ma, Xu, and Santesteban-Garay further discloses the clothing simulation method of claim 1, further comprising:
extracting a predetermined number of sample points from each of the patterns of the garment (Meador; extracting a predetermined number (corresponding to at least one) of sample points (i.e. landmarks) from each of the patterns of the garment [¶ 0066-0067]; wherein, a predetermined number corresponds to at least one (of a plurality) and more than one based on data of a classified garment segment [¶ 0012 and ¶ 0066]); and
based on a position of a predetermined type of a point included in each of the patterns, adjusting positions of the sample points (Meador; adjusting positions (corresponding to generating landmark data in response to a garment segment data) of the sample points (i.e. landmarks) based on a position of a predetermined type of a point/landmark included in each of the patterns [¶ 0066-0067]).
Regarding claim 3, Meador in view of Cirio, Ma, Xu, and Santesteban-Garay further discloses the clothing simulation method of claim 1, wherein the obtaining of the pattern information for each of the patterns comprises obtaining information about sample points of a target pattern (Meador; the obtaining of the pattern information for each of the patterns [as addressed within the parent claim(s)] comprises obtaining (segment/feature) information about sample points (landmarks) of a target pattern [¶ 0066-0067]), based on a length of an outline from a reference point of the target pattern among the patterns of the garment to each sample point extracted from the target pattern (Meador; based on an implicit length (given a size or dimension associated with a garment segment type) [¶ 0064-0065] of an outline (i.e. garment class) from a reference point of the target pattern among the patterns of the garment to each sample point extracted from the target pattern [¶ 0066-0067]).
Ma further teaches the obtaining of the pattern information for each of the patterns comprises obtaining information about sample points of a target pattern (Ma; the obtaining of the pattern information for each of the patterns [as addressed within the parent claim(s)] comprises obtaining information about sample points (i.e. nodes) of a target pattern [¶ 0058-0060 and 0069], as illustrate within Fig. 3 and Fig. 6), based on a length of an outline from a reference point of the target pattern among the patterns of the garment to each sample point extracted from the target pattern (Ma; based on a length of an outline from a reference point of the target pattern among the patterns of the garment to each sample point extracted from the target pattern [¶ 0058-0060]; additionally, defining the node and the segment (or the edge) in a single pattern piece and then define the node and the segment (or the edge) in multiple pattern pieces through repeated processes [¶ 0061-0064]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, Ma, Xu, and Santesteban-Garay, to incorporate the obtaining of the pattern information for each of the patterns comprises obtaining information about sample points of a target pattern, based on a length of an outline from a reference point of the target pattern among the patterns of the garment to each sample point extracted from the target pattern (as taught by Ma), in order to provide reduced consumption of human resources by automatic processing of garments and providing computerized modeling environment to a user (Ma; [¶ 0002-0003]).
Regarding claim 7, Meador in view of Cirio, Ma, Xu, and Santesteban-Garay further discloses the clothing simulation method of claim 1, wherein the sewing information comprises a pair of lines sewn together within the patterns (Cirio; the sewing information [as addressed within the parent claim(s)] comprises a pair of lines sewn together within the patterns [¶ 0031 and ¶ 0040-0041]; moreover, sewing order, other assembly information, and/or mapping of fabric pieces [¶ 0037-0038]; wherein, the process of assembly of fabric panels to generate a garment involves the stitching together of the fabric panels according to specific seam types and stitch types in a given order [¶ 0040-0041 and ¶ 0052-0054]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, Ma, Xu, and Santesteban-Garay, to incorporate the sewing information comprises a pair of lines sewn together within the patterns (as taught by Cirio), in order to provide realistic modeling of garments and fabrics (Cirio; [¶ 0002-0003 and ¶ 0010]).
Regarding claim 8, Meador in view of Cirio, Ma, Xu, and Santesteban-Garay further discloses the clothing simulation method of claim 7, wherein the sewing information further includes information indicating a sewing direction of the lines (Cirio; the sewing information [as addressed within the parent claim(s)] further includes information indicating a sewing direction of the lines [¶ 0031 and ¶ 0062-0063], as illustrated within Fig. 6; additionally, connecting line segments [¶ 0052-0053], as illustrated within Fig. 8).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, Ma, Xu and Santesteban-Garay, to incorporate the sewing information further includes information indicating a sewing direction of the lines (as taught by Cirio), in order to provide realistic modeling of garments and fabrics (Cirio; [¶ 0002-0003 and ¶ 0010]).
Regarding claim 9, Meador in view of Cirio, Ma, Xu, and Santesteban-Garay further discloses the clothing simulation method of claim 1, wherein the information indicating the sewing line of the pattern pair (Meador; the information indicating the sewing line of the pattern pair [as addressed within the parent claim(s)]) comprises:
information about sample points that are extracted from a first pattern of the pattern pair (Meador; information about sample points (i.e. landmarks) that are extracted from a 1st pattern (corresponding to a garment segment) of the pattern pair [¶ 0066-0067]); and
information about sample points that are extracted from a second pattern of the pattern pair (Meador; information about sample points (i.e. landmarks) that are extracted from a 2nd pattern (corresponding to another garment segment) of the pattern pair [¶ 0066-0067]).
Cirio further teaches information about points that are extracted from a first pattern of the pattern pair and correspond to a starting point and an end point of the sewing line included in the first pattern (Cirio; information about points that are extracted from a 1st pattern of the pattern pair and correspond to a starting point and an end point of the sewing line included in the 1st pattern [¶ 0042-0044], as illustrated within Fig. 4); and
information about points that are extracted from a second pattern of the pattern pair and correspond to a starting point and an end point of the sewing line included in the second pattern (Cirio; information about points that are extracted from a 2nd pattern of the pattern pair and correspond to a starting point and an end point of the sewing line included in the 2nd pattern [¶ 0042-0044], as illustrated within Fig. 4).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, Ma, Xu, and Santesteban-Garay, to incorporate information about points that are extracted from a first pattern of the pattern pair and correspond to a starting point and an end point of the sewing line included in the first pattern; and information about points that are extracted from a second pattern of the pattern pair and correspond to a starting point and an end point of the sewing line included in the second pattern (as taught by Cirio), in order to provide realistic modeling of garments and fabrics (Cirio; [¶ 0002-0003 and ¶ 0010]).
Regarding claim 10, Meador in view of Cirio, Ma, Xu, and Santesteban-Garay further discloses the clothing simulation method of claim 1, wherein the pattern embedding model is trained based sewing information (Meador; the pattern embedding model is trained [¶ 0058 and ¶ 0065-0066] based on sewing information [as addressed within the parent claim(s)]; moreover, a NN can be trained corresponding to a one-shot network or tailor-solver units [¶ 0074-0075]).
Santesteban-Garay further teaches model is trained based on a loss about a difference between the predicted sewing information and ground truth (Santesteban-Garay; the model is trained based on a loss about a difference between the predicted information and ground truth [¶ 0072-00076]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, Ma, Xu, and Santesteban-Garay, to incorporate model is trained based on a loss about a difference between the predicted sewing information and ground truth (as taught by Santesteban-Garay), in order to provide simulations of clothing/garments that is less computationally intensive (Santesteban-Garay; [¶ 0004-0005 and ¶ 0007-0008]).
Regarding claim 11, the rejection of claim 11 is addressed within the rejection of claim 15, due to the similarities claim 11 and claim 15 share, therefore refer to the rejection of claim 15 regarding the rejection of claim 11. Although, claim 11 and claim 15 may not be identical, they are considerably comparable or substantially equivalent given their overlapping subject matter. However, the subject matter/limitations not addressed by claim 15 is/are addressed below.
Meador discloses wherein:
the predicting of the sewing information about the patterns comprises predicting arrangement information about the patterns and the sewing information, based on an embedding vector for each of the patterns (Meador; the implicit predicting (given a calculated or estimated outcome) of the sewing information about the patterns comprises predicting arrangement (i.e. segment) information about the patterns and the sewing information based on an embedding vector for each of the patterns [¶ 0063-0064 and ¶ 0066-0067]; additionally, a simulation engine encodes the virtual garment data in relation with generating a simulation [¶ 0073 and ¶ 0075]); and
the generating of the simulation result of the garment comprises generating the simulation result of the garment, based on the sewing information and the arrangement information (Meador; the generating of the simulation result of the garment comprises generating the simulation result of the garment [¶ 0072-0074] based on the implicit sewing information and the arrangement information [as addressed above], as illustrated within Fig. 7A-B; wherein, virtual garment data (corresponding to sewing info) is used to generate a simulation [¶ 0063 and ¶ 0070-0071]).
(further refer to the rejection of claim 15)
Regarding claim 12, the rejection of claim 12 is addressed within the rejection of claim 10, due to the similarities claim 12 and claim 10 share, therefore refer to the rejection of claim 10 regarding the rejection of claim 12.
Regarding claim 13, Meador in view of Cirio, Ma, Xu, and Santesteban-Garay further discloses the clothing simulation method of claim 1, wherein the information about the sample points comprises at least one of:
information indicating positions of the sample points within a pattern of the garment;
information indicating positions of the sample points within the garment;
information indicating a positional relationship between adjacent ones of the sample points; and
information indicating a type of the sample points (Meador; the information about the sample points comprises (at least one of: ) information (i.e. class) indicating a type of the sample points (i.e. landmarks) [¶ 0066-0067]).
Ma further teaches information indicating positions of the sample points within the garment (Ma; information indicating positions of the sample points within the garment [¶ 0045-0048]; moreover, types of nodes and segment is a vector with a state node and an end node [¶ 0058-0059]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention was made to modify Meador as modified by Cirio, Ma, Xu, and Santesteban-Garay, to incorporate information indicating positions of the sample points within the garment (as taught by Ma), in order to provide reduced consumption of human resources by automatic processing of garments and providing computerized modeling environment to a user (Ma; [¶ 0002-0003]).
Regarding claim 14, Meador discloses a computer program that, when executed by a processor, cause the processor to perform (Meador; a computer program [¶ 0086 and ¶ 0089] that, when executed by a processor, cause the processor to perform [¶ 0060 and ¶ 0079-0081]; moreover, processor receive instructions from memory [¶ 0092 and ¶ 0094-0096]) the method of claim 1 (as further addressed within the rejection of claim 1).
Allowable Subject Matter
Claims 5 and 6 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Igarashi et al. (US PGPUB No. 20090040224 A1) regarding connectors of a pattern;
Lee et al. (US PGPUB No. 20210217250 A1) regarding guide for combining pattern pieces of clothing;
Wilcox (US PGPUB No. 20210383031 A1 & US PGPUB No. 20230200477 A1) regarding modeling and identification of segments of clothing;
Liang et al. (US PGPUB No. 20230306699 A1) regarding modeling and sewing points; and
Oldach et al. (US PGPUB No. 20170186217 A1) regarding connecting seams and alignment.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Refer to PTO-892, Notice of Reference Cited for a listing of analogous art.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Charles Lloyd Beard whose telephone number is (571)272-5735. The examiner can normally be reached Monday - Friday, 8:00 AM - 5: 00 PM, alternate Fridays EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tammy Goddard can be reached at (571) 272-7773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
CHARLES LLOYD. BEARD
Primary Examiner
Art Unit 2611
/CHARLES L BEARD/Primary Examiner, Art Unit 2611
Prosecution Insights