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 .
This action is in response to the Amendment filed on 01/07/2026.
Claims 1-4, 6-20 are pending. Claim 1, 7, 8. 20 have been amended. Claim 5 is cancelled.
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) 1-4, 6, 8, 10-14,18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 20200066029 A1, hereinafter Chen) in view of Sareen et al. (US 20110298897A1, hereinafter Sareen), and further in view of O'Brien et al. (US 20200250892 A1, hereinafter O'Brien).
Regarding Claim 1, Chen teaches a method of simulating draping of fabric (Chen, Paragraph [0099], “This module is important for initializing finite-element garment physics simulation”), comprising: displaying user interface elements (Chen, Paragraph [0033], “The method may be one including the data processing arrangement providing a user interface (UI) for the user to use to input data”) [[ configured to indicate physical property parameters of the fabric; receiving adjustment to at least a subset of the physical property parameters determined by manipulation of the user interface elements by a user; wherein the adjustment is constrained by stored correlation between the physical property parameters;]]; generating a mesh of the fabric draped on an object by applying the adjusted physical property parameters to a machine learning model trained using shapes of fabrics draped on the object and physical property parameters of the draped fabrics (Chen, Paragraph [0023], “The method may be one including using a deep neural network model <read on machine learning mode> for generating the 3D garment model” [0034], “simulate automatically a drape and a fit of the digital garment model onto the 3D body avatar” [0039], “generating the complete 3D garment model to comprise one or more of… a 3D mesh model” [0116], “stores selectively one or more of the following in the garment database… material stretch attributes, material strain attributes <read on adjusted physical property parameters>”); and displaying the fabric draped on the object according to the generated mesh (Chen, Paragraph [0012], “generating an image file of the 3D body model of the user wearing the complete 3D garment model, using the simulated complete 3D garment model” [0036], “The method may be one including … display the 3D body avatar in an outfit of one or more selected garments”).
But Chen does not explicitly disclose [[ displaying user interface elements ]] configured to indicate physical property parameters of the fabric; receiving adjustment to at least a subset of the physical property parameters determined by manipulation the user interface elements by a user;
However, Sareen teaches displaying user interface elements configured to indicate physical property parameters of the fabric (Sareen, Paragraph [0028], “FIG. 22 is an example web page <read on user interface> produced by a system according to one embodiment that illustrates how stretch values may be visually displayed using a color tension map <read on physical property parameter>); receiving adjustment to at least a subset of the physical property parameters determined by manipulation of the user interface elements by a user (Sareen, Paragraph [0047], “there may be three fabric presets for stretch-one for warp, one for weft, and one for shear, which may comprise dependent variables that may not be individually solved-for in an isolated test, but rather may require linear regression using all three parameters to find the final presets. [0087], “the user of E-FIT may work to simulate the correct appearance of material textures by adjusting and applying various material texture properties or texture maps that model the color, roughness, light reflection, opacity, and other visual characteristics” [0088] In one embodiment, material textures 188 may be applied to the surface of each 3D mesh corresponding to each pattern piece. These material textures 188 realistically simulate various attributes that make up the appearance of production sample garment 59);
Sareen and Chen are analogous since both of them are dealing with virtual garment try on system that simulate draping of fabric on digital avatars. Chen provided a way of generating a mesh of a garment using deep neural network trained on physical garment data and simulating its drape and fit on a 3D avatar. Sareen provided a way of allowing user to interactively define and/or adjust fabric properties through a graphical user interface and feeding those parameters into a simulation model. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate interactive UI and user editable fabric presets taught by Sareen into modified invention off Chen such that a user could modify physical parameters of the fabric through an interface and immediately visualize the ML based draped result. The motivation is to enable user interactivity and customization of the draping simulation based on material behavior which is discussed by Sareen in Paragraph [0028], [0045]-[0047].
But the combination does not explicitly disclose wherein the adjustment is constrained by stored correlation between the physical property parameters;
However, O’Brien teaches wherein the adjustment is constrained (O’Brien, Paragraph [0116], “the process determines whether the compression and/or stretch is beyond the capability of the fabric and/or body. That is, whether the garment compresses so far that it cannot fit the body model. If so, at block 1180, an error is indicated; [0121], “the clothing is simulated with the barrier constraining the movement of the cloth but not the body. Using the one-foot diameter sphere, for example, the sleeves will look as if the wearer pushed them back to expose the hands. This may also create stylish fabric bunching at the wrists. Other barrier shapes may be used as appropriate. In one embodiment, the barrier shapes may range from spheres, to cubes, cones, or other shapes. In some embodiments, the barrier may be a simple plane, prohibiting movement of the fabric beyond a particular plane”) by stored correlation between the physical property parameters (O’Brien, Fig. 2C, Element 270 Validator, this block check the value passed from Adjustor 268 and ensure they conform to valid combinations , Fig. 3B, block 395, “Enable use of soft constraints, with region of tolerance” which indicate that constraints derived from stored data are applied to limit parameter changes; Fig. 14, Step 1460, “Identify parametric definition of softness (equation or region of tolerance) and activate constraint” Paragraph [0129], “If the constraint identified is a soft constraint, at block 1460, the parametric definition of softness (the reaction of the constraint) is defined, and the constraint is activated…the element may have a region of tolerance, within which the force is kept at zero ( or near zero)”);
O’Brien and Chen are analogous since both of them are dealing with systems for simulating draping of virtual garments onto a 3D object using input fabric characteristics. Chen provided a way of learning a mapping between garment material attributes and the resulting 3D shape when draped onto a body using neural network. O’Brien provided a way of storing fabric characteristic data and use validation logic to enforce compatibility between related parameters. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate validation and correlation aware constraint logic taught by O’Brien into modified invention off Chen such that adjustment to the subset of physical property parameters ins constrained based on stored correlations which can prevent nonphysical combination and improve the realism and reliability of simulation result during the machine learning modelling process.
Regarding Claim 2, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination further teaches wherein the machine learning model is a neural network model (Chen, Paragraph [0023], “The method may be one including using a deep neural network model for generating the 3D garment model”).
Regarding Claim 3, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination further teaches wherein generating the mesh of the fabric comprises: determining a contour of the fabric by applying the adjusted physical property parameters to the machine learning model; and configuring the mesh of fabric to extend to the determined contour of fabric (Chen, Paragraph [0116], “stores selectively one or more of the following in the garment database… material stretch attributes, material strain attributes <read on adjusted physical property parameters>” [0174], [0189], “An output image 1002 may show a control spline prediction after stage 1 of the multi-stage algorithm (or the deep neural network prediction).The coarse-control spline is shown using a dotted line 1004. … The refined control spline may be obtained by adjusting the endpoint of the splines based on the silhouette of the garment layer” “The garment geometry data 130 may include, but is not limited to, 2D silhouette(s) and 3D mesh model(s)”).
Regarding Claim 4, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 3.
The combination further teaches generating the mesh of the fabric further comprises: generating a first portion of the mesh on an upper surface of the object; generating a second portion of the mesh extending from the first portion of the mesh by a predetermined width; and generating a third portion of the mesh extending from the second portion of the mesh to the contour (O’Brien, Fib. 3B, Step 390, 398, “Apply up-sampling and/or down-sampling as needed for detail, bandwidth, speed” “Use barriers to constrain clothing positioning/ movement” Paragraph [0049], [0050], At block 398, up-sampling and/or down-sampling is applied to the final modeled garment, to accommodate additional detail (up-sampling) or lower bandwidth/display quality (down-sampling.) At block 390, barriers are used to constrain the clothing positioning and movement; it is noted by doing step 390, 398 suggests mesh is generated from different regions in incremental regions).
O’Brien and Chen are analogous since both of them are dealing with systems for simulating draping of virtual garments onto a 3D object using input fabric characteristics. Chen provided a way of learning a mapping between garment material attributes and the resulting 3D shape when draped onto a body using neural network. O’Brien provided a way of region based mesh generation that define transitional or boundary regions during garment simulation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate region based constraint enforcement taught by O’Brien into modified invention off Chen such that the mesh generation may occur in multiple parts which will improve simulation realism and topological stability across layered garment regions.
Regarding Claim 6, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination further teaches wherein the stored correlation represents distribution of physical property parameters corresponding to the fabric (O’Brien, Paragraph [0025], “Fabric characteristic data includes … fabric mechanical characteristics (simulation data)”; it is noted these simulation data values are generated and stored for multiple fabrics, forming a distribution of physical properties associated with each fabric type).
O’Brien and Chen are analogous since both of them are dealing with systems for simulating draping of virtual garments onto a 3D object using input fabric characteristics. Chen provided a way of learning a mapping between garment material attributes and the resulting 3D shape when draped onto a body using neural network. O’Brien provided a way of associating store simulation data with fabric types in distributional characteristics for each fabric material. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate data structures taught by O’Brien into modified invention off Chen such that the stored correlation represents the distribution of physical property parameters corresponding to each other which will allow parameter guidance based on empirically tested range per fabric, and enhance simulation plausibility.
Regarding Claim 8, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination further teaches further comprising displaying a visual effect indicating violation of constraints on the physical property parameters as indicated by the stored correlation on the user interface elements responsive to the adjustment violating the constraints (O’Brien, Fig. 2C Element 270 Validator, Fig. 3B, Step 395, “Enable use of soft constraints, with region of tolerance”; it is noted the system is equipped with soft constraints and validators that check parameter inputs. “the region of tolerance” implies a bounded range, within which adjustments are allowed. When violation occur, the system performs validations, implicitly invoking a user-facing feedback mechanism which is constraint violation feedback; Fig. 2C Element 282 End User Tools logically provide UI feedback for validator-triggered events).
O’Brien and Chen are analogous since both of them are dealing with systems for simulating draping of virtual garments onto a 3D object using input fabric characteristics. Chen provided a way of learning a mapping between garment material attributes and the resulting 3D shape when draped onto a body using neural network. O’Brien provided a way of using validator modules and regions of tolerance to monitor user adjusted parameters when violation happened. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate validator feedback taught by O’Brien into modified invention off Chen such that the UI displays a visual effect to indicate the parameter constraints has been violated which can assist users in understanding and correcting invalid input during fabric turning.
Regarding Claim 10, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 8.
The combination further teaches wherein the adjusted physical property parameters are limited according to the constraints (O’Brien, Fig. 3B Step 395, “Enable use of soft constraints, with region of tolerance” Fig. 2C, Element 270 Validator restricts edits through data validation <read on limiting adjusted parameters>).
O’Brien and Chen are analogous since both of them are dealing with systems for simulating draping of virtual garments onto a 3D object using input fabric characteristics. Chen provided a way of learning a mapping between garment material attributes and the resulting 3D shape when draped onto a body using neural network. O’Brien provided a way of limiting parameter edits through a validator. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate constraint limiting logic taught by O’Brien into modified invention off Chen such that adjusted physical property parameters are automatically bounded according to the constraints which can prevent runtime simulation errors and ensure material parameters say within safer, realistic domains.|
Regarding Claim 11, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination further teaches wherein the physical property parameters comprise at least one of a stretch force parameter (Sareen, Paragraph [0048], “One of the presets tested comprises stretch <read on stretch force> and shear resistance”),
a bending force parameter or a density parameter (Sareen, Paragraph [0049], [0056], “Such solutions have constants (such as natural frequency, spring constant, mass, etc.) which can be adjusted such that the mesh behaves like any particular fabric…Additional forces that may be modelled may include damping forces, which simulate the effect of friction and air resistance”; “depending on the type of textile used to build the cloth and the density of threads“ it is noted bending force can be done via using spring, mass/density like simulation parameter).
As explained in rejection of claim 1, the obviousness for combining of using physical parameters of the fabric of Sareen into Chen is provided above.
Regarding Claim 12, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 11.
The combination further teaches wherein the stretch force parameter comprises at least one of a weft stretch force parameter, a warp stretch force parameter or a shear force parameter (Sareen, Paragraph [0047], “there may be three fabric presets for stretch-one for warp, one for weft, and one for shear”).
As explained in rejection of claim 1, the obviousness for combining of using physical parameters of the fabric of Sareen into Chen is provided above.
Regarding Claim 13, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 11.
The combination further teaches wherein the bending force parameter comprises at least one of the parameters a weft bending force parameter, a warp bending force parameter, and a diagonal bending force parameter (Sareen, Paragraph [0052], “Another parameter may comprise bend resistance. This measurement involves the way that fabrics differ from rigid bodies in their ability to bend” [0047]-[0048], “there may be three fabric presets for stretch-one for warp, one for weft, and one for shear” [0049], “The CLOTHFX algorithms are based on modelling the 3D mesh object's vertices as having mass, and the connections between vertices as springs. In other embodiments, alternative algorithms based on known research can be used to model the mesh as interacting particles. In either case, widely known algorithms in classical dynamics may be used to find the time-varying displacement of each point in the mesh. Such solutions have constants (such as natural frequency, spring constant, mass, etc.) which can be adjusted such that the mesh behaves like any particular fabric”; it is noted the spring constants and mass-spring systems which are modeling fabric elasticity and bending which is standard method in cloth simulation for capturing bending stiffness, via the spring network that resists angular deformation across mesh vertices [0053], “the virtual test may be repeated until the surface areas of both tests match, wherein the resultant fabric preset is the final fabric preset for bend resistance”).
Sareen and Chen are analogous since both of them are dealing with digital garment simulation systems that incorporate fabric-specific parameter to generate 3D mesh drapes over virtual avatars. Chen provided a way of using machine learning to generate draped 3D mesh of the garment. Sareen provided a way of applying different parameters such as warp/weft/shear stretch, bending to drive cloth simulation using the digital body model. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate fabric parameter derivation and component force modeling taught by Sareen into modified invention off Chen such that parameters used in the machine learning process are derived from real world measurements which will increase the accuracy and realism of the simulated drape mesh generated by the machine learning model.
Regarding Claim 14, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination does not explicitly disclose but O’Brien teaches further comprising: receiving fabric information from the user via the user interface elements; and determining the physical property parameters corresponding to the received fabric information by applying the fabric information to a generative model for generating the physical property parameters (O’Brien, Paragraph [0025], “Fabric characteristic … may test the fabric and generate fabric characteristic data locally”, Fig. 2C Element 268, Fabric Characteristic Adjustor, Adjustor 268 processes input of fabric information (which is user facing) and derives simulation parameters <read on physical property parameters> from it).
O’Brien and Chen are analogous since both of them are dealing with systems for simulating draping of virtual garments onto a 3D object using input fabric characteristics. Chen provided a way of learning a mapping between garment material attributes and the resulting 3D shape when draped onto a body using neural network. O’Brien provided a way of using user selected fabric and convert into fabric characteristic data. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate generation pipeline taught by O’Brien into modified invention off Chen such that fabric information received from the user can be transformed into parameters using in generation model which will allow non-expert users to select simple fabric options and still benefit from physically accurate draping results.
Regarding Claim 18, the combination of Chen, Sareen, O’Brien teaches the invention in Claim 14.
The combination further teaches wherein the fabric information comprises at least one of a type of selected fabric, composition information of the selected fabric (Sareen, Paragraph [0056], “A swatch of cloth of the same dimensions can have very different weights, depending on the type of textile <read on type of selected fabric> used to build the cloth”; it is noted since different type of textile are used it is composition of textile used), and unit weight information of the selected fabric (Sareen, Paragraph [0056], “The weight is divided by the surface area of the swatch to arrive at the surface density”).
As explained in rejection of claim 1, the obviousness for combining of using different type of the fabric of Sareen into Chen is provided above.
Regarding Claim 19, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination further teaches further comprising: sending the adjusted physical property parameters to a server through a network (Sareen, Paragraph [0047], “fabric presets for stretch-one for warp, one for weft, and one for shear…require linear regression using all three parameters to find the final presets <read on adjusted physical property parameter> [0035], “In one embodiment, application service provider (ASP) 100 may receive data from consumer system 20 and stereophotogrammetry system 150. In one embodiment the ASP 100 and consumer system 20 may be connected through a wide area network 1500”);
and receiving the generated mesh from the server (Sareen, Paragraph [0174], “Once received, simulation requests are sent to a queue system 903 that is capable of maintaining lists of multiple simulation requests from multiple users.” [0170], “The user may see the resultant output of the 3D virtual try-on process on 3D viewer application 132”).
As explained in rejection of claim 1, the obviousness for combining of using adjusted physical property parameters of Sareen into Chen is provided above.
Regarding Claim 20, it recites limitations similar in scope to the limitations of claim 1 and the combination of Chen, Sareen and O’Brien teaches all the limitations as of Claim 1. And Chen discloses these features can be implemented on a computer readable storage medium (Chen, Paragraph [0001], the present disclosure relates to computer program products comprising a non-transitory computer readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a computerized device comprising data processing hardware to execute aforesaid methods.).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 20200066029 A1, hereinafter Chen) in view of Sareen et al. (US 20110298897A1, hereinafter Sareen), further in view of O'Brien et al. (US 20200250892 A1, hereinafter O'Brien) as applied to Claim 5 above and further in view of Siddique et al. (US 20160210602 A1, hereinafter Siddique).
Regarding Claim 7, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 1.
The combination further teaches wherein the stored correlation represents [[ reduction in a number of dimensions of ]] the physical property parameters associated with the fabric fabrics (Chen, Paragraph “stores selectively one or more of the following in the garment database… material stretch attributes, material strain attributes <read on physical property parameters>”);
But, the combination does not explicitly disclose reduction in a number of dimensions.
However, Siddique teaches wherein the stored correlation represents reduction in a number of dimensions of the physical property parameters associated with the fabric (Siddique, Paragraph [0113], [0159], “The module enables photorealistic modeling of apparel permitting life-like simulation (in terms of texture, movement, color, shape, fit etc.) of the apparel” “applying a dimensionality reduction technique such as principal component analysis (PCA), probabilistic principal component analysis (PPCA), 2D PCA, Gaussian Process Latent Variable Models GPLVM, or independent component analysis (ICA)”).
Siddique and Chen are analogous since both of them are dealing with simulation or prediction of draped fabric properties based on measurable inputs. Chen provided a way of use fabric properties as parameters for simulating garment draping. Siddique provided a way of reducing the feature space dimensionality using statistical correlation and PCA. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate PCA based reduction of physical property dimensions taught by Siddique into modified invention off Chen such that the stored correlation represents dimensionality reduction which will allow more efficient simulation and feature constraint storage.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 20200066029 A1, hereinafter Chen) in view of Sareen et al. (US 20110298897A1, hereinafter Sareen), further in view of O'Brien et al. (US 20200250892 A1, hereinafter O'Brien) as applied to Claim 8 above and further in view of Ubillos et al. (US 20130239057 A1, hereinafter Ubillos).
Regarding Claim 9, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 8.
The combination does not explicitly disclose but Ubillos teaches wherein the visual effect is shown on a pointer of a slide bar corresponding to the physical property parameters (Ubillos, Paragraph [0037], “These sliders may provide a visual indication to the user while the user moves the sliders along the track 155” [0148], “A response curve 1119 … Black and white input markers are illustrated … to provide a visual indication”).
Ubillos and Chen are analogous since both of them are dealing with UI-based adjustment of parameter values using slider bars. Chen provided a way of process physical fabric parameters via UI elements. Ubillos provided a way of presenting real time visual feedback on the slider pointer itself when a user interacts with the slider. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate slider pointer feedback mechanism taught by Ubillos into modified invention off Chen such that a visual effect is shown on the slider pointer when constraints are violated or values are adjusted which will give immediate user feedback at the point of interaction and improve the UI clarity.
Claim(s) 15-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 20200066029 A1, hereinafter Chen) in view of Sareen et al. (US 20110298897A1, hereinafter Sareen), further in view of O'Brien et al. (US 20200250892 A1, hereinafter O'Brien) as applied to Claim 1 above and further in view of Kuijpers et al. (“The measurement of fabric properties for virtual simulation—a critical review”, hereinafter Kuijpers) and Zhou et al. (“Evaluation of Luster, Hand Feel and Comfort Properties of Modified Polyester Woven Fabrics”, hereinafter Zhou).
Regarding Claim 15, the combination of Chen, Sareen and O’Brien teaches the invention in Claim 14.
The combination does not explicitly disclose but Kuijpers teaches representing fabric types on a graph with axes corresponding to a plurality of features (Kuijpers, Page 7, “The main focus is on bending, shear, tensile, and friction properties because these are widely considered to be among the most important fabric properties determining fabric behavior” Page 9, “Table 1: fabric properties measured by the KES-F system” Page 30, “Graphs with full curves representing the raw measured data”);
Kuijpers and Chen are analogous since both of them are dealing with representation of physical fabric properties for digital garment simulation. Chen provided a way of using material parameters to drive a neural network based draping model. Kuijpers and Chen are analogous since both of them are dealing with representation of physical fabric properties for digital garment simulation. provided a way of using standardized physical property axes and visualizations used in fabric simulation environments. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate multi-feature axes taught by Kuijpers and Chen are analogous since both of them are dealing with representation of physical fabric properties for digital garment simulation into modified invention off Chen such that fabric types are represented on a graph with axes corresponding to a plurality of features to facilitate more interpretable selection and tuning of fabric inputs bases on visualized simulation-relevant data.
The combination does not explicitly disclose but Zhou teaches determining the fabric information according to the graph responsive to receiving a fabric type from the user (Zhou, Page 75, “FIGURE 4. Radar plot for comparisons of fabrics comfort properties.” “A comparison of the performance among the three fabrics using a radar plot is illustrated in Figure 4. The most relevant comfort properties were included in this plot with scales from 0 to 10. The ratings were calculated by dividing the corresponding values by the best obtained value for that specific property”).
Zhou and Chen are analogous since both of them are dealing with comparing or simulating fabric characteristics using measurable features. Chen provided a way of applying fabric feature value to simulate drape. Zhou provided a way of selecting a plotted fabric in a radar plot yields numerical values per features axis based on user selection. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate radar plot based retrieval of per feature values taught by Zhou into modified invention off Chen such that when a user selects a fabric type from the plot, the corresponding physical property values are retrieved as the simulation input which will improving usability and enabling visual profile-based selection.
Regarding Claim 16, the combination of Chen, Sareen, O’Brien. Kuijpers and Zhou teaches the invention in Claim 15.
The combination further teaches wherein each of the fabric types is represented as a zone defined by ranges of the features indicated by the axes (Zhou, Page 75, “FIGURE 4. Radar plot for comparisons of fabrics comfort properties”; it is noted in a radar plot, each fabric type appears as a polygonal shape across the axes, which forms a zone defined by per-axis values, i.e. range of features <read on zone defined by range of the features>).
As explained in rejection of claim 16, the obviousness for combining of radar plot based retrieval of per feature values of Zhou into Chen is provided above.
Regarding Claim 17, the combination of Chen, Sareen, O’Brien. Kuijpers and Zhou teaches the invention in Claim 16.
The combination further teaches further comprising generating a detailed level of the fabric information on the fabric type responsive to receiving a user input indicating selection within the zone (O’Brien, Paragraph Fig. 2C, Element 268, Fabric Characteristic Adjustor, Fig. 1, Element 120 Fabric Characteristic Generation, system adjusts characteristics after receiving user input, generating fabric parameters and adjust them via validator 270).
O’Brien and Chen are analogous since both of them are dealing with systems for simulating draping of virtual garments onto a 3D object using input fabric characteristics. Chen provided a way of learning a mapping between garment material attributes and the resulting 3D shape when draped onto a body using neural network. O’Brien provided a way of refining fabric parameters interactively using user facing modules Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate user guided refinement taught by O’Brien into modified invention off Chen such that a more detailed level of fabric information is generated based on user input which can improve simulation quality by refining material assumptions after initial user input.
Response to Arguments
Applicant’s arguments with respect to claim 1, 20 filed on 01/07/2026, with respect to rejection under 35 USC § 103 in regard to prior art does not teaches the limitation(s) “receiving adjustment to at least a subset of the physical property parameters determined by manipulation the user interface elements by a user, wherein the adjustment is constrained by stored correlation between the physical property parameters” “adjustment to one or more physical property is performed by a user using user interface elements. The adjustment, however, is constrained by correlation between the physical property parameters that is stored”
In response to the argument, prior art Sareen teaches in Paragraph [0047], [0087], [0088], [0190], [0191] that describe the opaqueness or transparency of the garment may also be adjusted by the user. This adjustment allows the user to see the avatar through the garment to assess fit. And to provide a 3D Viewer and the consumer interface where the user views the consumer drape. The system is designed for a software application on any computing device , where interactive tools (like buttons or sliders for transparency or selecting different "presets" ) constitute the manipulation of UI elements to adjust the parameters of the virtual garment and also provide "fabric presets", and it would be a matter of routine engineering for a person having ordinary skill in the art to provide a UI (as shown in Sareen's 3D viewer) where a user can select or tweak these presets, those paragraph clearly teaches the limitation “receiving adjustment to at least a subset of the physical property parameters determined by manipulation the user interface elements by a user”. Prior art O’Brien teaches in Paragraph [0116], [0119], [0121], [0129] that the system determines if fabric characteristics conform to valid combinations of these characteristics. A combination of multiple physical parameters that must be valid is the technical equivalent of an inter-parameter correlation. For example, if a fabric has a certain thickness, its weight and stiffness must fall within a correlated range to be physically valid. And Validator 270 determines if values are beyond the capability of fabric or beyond the specification. This acts as a functional constraint on any adjustments, ensuring that the resulting fabric model remains physically realistic. Also provided a way for refining parameters based on these validations. To determine if a combination is beyond capability, the system must compare the parameters against a stored database or manifold of physical properties. This stored data represents the stored correlation that constrains the user's manual adjustments to prevent non-physical results, clearly those paragraph teaches the limitation “wherein the adjustment is constrained by stored correlation between the physical property parameters”. Hence the combination of prior arts Chen, Sareen and O’Brien fully anticipates all the limitations in Claim 1. Therefore, applicant remark cannot be considered persuasive.
In regard to Claims 2-4, 6-19, they directly/indirectly depends on independent Claim 1. Applicant does not argue anything other than the independent Claim 1. The limitations in those claims in conjunction with combination previously established as explained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/YuJang Tswei/ Primary Examiner, Art Unit 2614