DETAILED ACTION
Claims 1-27 are presented for examination.
Claims 28-29 were withdrawn.
This office action is in response to the election submitted on 11-MAY-2026.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/22/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
The information disclosure statement (IDS) submitted on 06/10/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 22-24 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 22 recites the limitation "the fitted face foam geometry". There is insufficient antecedent basis for this limitation in the claim. Examiner has interpreted the insufficient antecedent basis due to an incorrect dependency. Examiner has interpreted claim 22 to be dependent on claim 21 instead of claim 1 when examining the claims. The elements of claim 22 appear to be sequence naturally continuing from claim 21. The antecedent does appear to correct when the dependency of claim 22 is interpreted as dependent on claim 21 instead of claim 1, however, Examiner encourages the Applicant to check the antecedent basis if amending the dependency.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over
YEOMANS et al., U.S. Patent Application Publication 2019/0381361 A1 (hereinafter ‘YEOMANS’) in view of
LI et al., U.S. Patent Application Publication 2021/0259886 A1 (hereinafter ‘LI’).
Regarding Claim 1: A computer-implemented method for customizing a goggle, comprising:
YEOMANS teaches generating a custom 3D model of a goggle frame based, at least in part, on the 3D face scan data, (([0078] YEOMANS “…(a) scanning a body part of at least one person…” [0079] YEOMANS “…(b) creating a digital model of the body part…” [0080] YEOMANS “…( c) creating a digital model of the sports article…” [0075] YEOMANS “…Alternatively, any suitable method for generating a 3D geometry may be used here…” [0076] YEOMANS “…A digital model of a swimming goggle may then be loaded with the average model of the head scans, and the optimal placement of the swimming goggle may then be computed with respect to the average model of the head…”)
YEOMANS teaches wherein the generating the custom 3D model of the goggle frame includes: defining geometry of a face flange portion of the goggle frame based, at least in part, on the 3D face scan data; and ([0125] YEOMANS “…The swimming goggle 10 is matched to fit a model head and comprises a nose bridge 18. The surface of the model head defines a flange angle of 0 degrees for the second seal. A second seal with a flange angle of 0 degrees is indicated by reference numeral 41. The flange angle is defined as the angle between the model head and a rim portion of the second seal, when the goggles are not worn but are aligned to be worn by the model head. A second seal with a flange angle of 30 degrees is indicated by reference numeral 42. A second seal with a flange angle of 60 degrees is indicated by reference numeral 43…”)
YEOMANS teaches defining geometry of one or more vent flange portions of the goggle frame which connect the face flange portion to a geometry of a lens-side portion of the goggle frame to generate the custom 3D model of the goggle frame; and ([0025] YEOMANS “…The second seal may comprise a flange angle of between 30 and 60 degrees. The flange angle is determined in a rim portion of the second seal, for example proximate a nose bridge but the flange angle may generally refer to any position on the rim portion of the second seal. The swimming goggle is matched to fit a model head. The surface of the model head defines a flange angle of 0 degrees for the second seal. The flange angle is defined as the angle between the model head and a rim portion of the second seal, when the goggles are not worn but are aligned to be worn by the model head. At a flange angle of 60 degrees, the rim portion of the second seal may be parallel to the outer lens of the goggle. A lower flange angles represents a tilt of the second seal, wherein the outer rim portion is tilted away from the head of the wearer, i.e. outwards. Through detailed modelling, the inventors have found, that this range of flange angle creates the most even pressure distribution of the second seal on the eye socket and has the lowest peak contact pressure. Therefore, this parameter range provides an optimal level of comfort and sealing efficacy…”)
YEOMANS does not appear to explicitly disclose
receiving three-dimensional (3D) face scan data of at least a portion of a face of a user, wherein the 3D face scan data comprises data for a 3D representation of at least a portion of the face of the user;
outputting a 3D-printer compatible file of the custom 3D model of the goggle frame.
However, LI teaches receiving three-dimensional (3D) face scan data of at least a portion of a face of a user, wherein the 3D face scan data comprises data for a 3D representation of at least a portion of the face of the user; ([0005] LI “…S1: establishing a medical isolation goggles matrix: performing 3D scanning on a basic tester to obtain point cloud data from front and side faces of the basic tester's face, and performing 3D design on the obtained data to obtain the medical isolation goggles matrix…” [0006] “S2: acquiring facial data of a user: photographing the user or performing 3D scanning on the user to obtain point cloud data from front and side faces of the user's face…”)
LI teaches outputting a 3D-printer compatible file of the custom 3D model of the goggle frame. ([0032] LI “…S4: performing additive manufacturing: import the personalized medical isolation goggles model into slice software matched with a 3D printer to perform 3D model slicing, generate a print format file that can be identified by the 3D printer, and input the print format file into the 3D printer to print the personalized medical isolation goggles model, where 3D printing is specifically performed by a thermoplastic polyurethane (TPU) material and a stereolithography appearance (SLA) technology, so as to obtain a pair of personalized medical isolation goggles…”)
YEOMANS and LI are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the defining geometry of one or more vent flange portions of the goggle frame which connect the face flange portion to a geometry of a lens-side portion of the goggle frame to generate the custom 3D model of the goggle frame as disclosed by YEOMANS by outputting a 3D-printer compatible file of the custom 3D model of the goggle frame as disclosed by LI.
One of ordinary skill in the art would have been motivated to make this modification in order to improve the fit for a user as discussed in paragraph [0003] of LI “…In view of the foregoing, is an object of the invention to provide a method for preparing personalized medical isolation goggles by 3D printing that solves the foregoing problems associated with the prior art, such that a pair of medical isolation goggles closely fit a user, and pollutants are prevented from entering the medical isolation goggles…”
Regarding Claim 13: YEOMANS and LI teach The method of claim 1
LI teaches wherein the 3D face scan data is obtained using a scanner. ([0029] LI “…S1: establishing a medical isolation goggles matrix: perform 3D scanning on a basic tester to obtain point cloud data from front and side faces of the basic tester's face, and perform 3D design on the obtained data to obtain the medical isolation goggles matrix. Preferably, during 3D scanning, the basic tester sits down naturally with eyes closed, high-precision 3D data of the basic tester's face is quickly acquired by using a hand-held 3D scanner, and the point cloud data of the basic tester's face is converted into triangular mesh surface data in software of the 3D scanner. The 3D scanner can convert, in accordance with stereo information of a real object, the data into digital signals that can be directly processed by a computer, and the point cloud generated is more uniform. Therefore, the accuracy is higher and the stability is higher…”)
Claims 2-4 are rejected under 35 U.S.C. 103 as being unpatentable over
YEOMANS et al., U.S. Patent Application Publication 2019/0381361 A1 (hereinafter ‘YEOMANS’) in view of
LI et al., U.S. Patent Application Publication 2021/0259886 A1 (hereinafter ‘LI’) further in view of
SAIGO, Foreign Patent Publication CN1255989A (hereinafter ‘SAIGO’).
Regarding Claim 2: YEOMANS and LI teach The method of claim 1
YEOMANS and LI do not appear to explicitly disclose
wherein the geometry of the lens-side goggle of the goggle frame comprises predetermined geometry of a lens-side portion of the goggle frame.
However, SAIGO wherein the geometry of the lens-side goggle of the goggle frame comprises predetermined geometry of a lens-side portion of the goggle frame. (Abstract and Figs. 16-18 and 20 SAIGO “…the input of predetermined data, lens material data and lens design data with the selected spectacle frame shape data integration and simulation similar to the actual spectacle wearing state, can more easily and accurately determine the personal like of glasses. provides more data of the information relative to the frame. by comprising a frame picture and frame-related text and voice to make selection easier. In addition, by actively introduced by comparing two same display selected eyeglasses of spectacles try-on paired comparison and selection screen of the screen is selected…”)
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YEOMANS, LI, and SAIGO are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the defining geometry of one or more vent flange portions of the goggle frame which connect the face flange portion to a geometry of a lens-side portion of the goggle frame to generate the custom 3D model of the goggle frame as disclosed by YEOMANS and LI by wherein the geometry of the lens-side goggle of the goggle frame comprises predetermined geometry of a lens-side portion of the goggle frame as disclosed by SAIGO.
One of ordinary skill in the art would have been motivated to make this modification in order to improve selection base on the wearer as discussed on pg. 2 paragraph 2 of the translation by SAIGO “…Besides, it also claims a method for selecting an appropriate lens shape of the eyeglass wearer faceshape according to a predetermined design rule wherein the computer. However, this method does notfully reflect the preference of the eyeglass wearer…”
Regarding Claim 3: YEOMANS and LI teach The method of claim 1
YEOMANS and LI do not appear to explicitly disclose
wherein the geometry of the lens-side portion of the goggle frame comprises a plurality of predetermined geometries for the lens-side portion of the goggle frame.
However, SAIGO wherein the geometry of the lens-side portion of the goggle frame comprises a plurality of predetermined geometries for the lens-side portion of the goggle frame. (Abstract and Figs. 16-18 and 20 [shown above in claim 2] SAIGO “…the input of predetermined data, lens material data and lens design data with the selected spectacle frame shape data integration and simulation similar to the actual spectacle wearing state, can more easily and accurately determine the personal like of glasses. provides more data of the information relative to the frame. by comprising a frame picture and frame-related text and voice to make selection easier. In addition, by actively introduced by comparing two same display selected eyeglasses of spectacles try-on paired comparison and selection screen of the screen is selected…”)
YEOMANS, LI, and SAIGO are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the defining geometry of one or more vent flange portions of the goggle frame which connect the face flange portion to a geometry of a lens-side portion of the goggle frame to generate the custom 3D model of the goggle frame as disclosed by YEOMANS and LI by wherein the geometry of the lens-side portion of the goggle frame comprises a plurality of predetermined geometries for the lens-side portion of the goggle frame as disclosed by SAIGO.
One of ordinary skill in the art would have been motivated to make this modification in order to improve selection base on the wearer as discussed on pg. 2 paragraph 2 of the translation by SAIGO “…Besides, it also claims a method for selecting an appropriate lens shape of the eyeglass wearer faceshape according to a predetermined design rule wherein the computer. However, this method does notfully reflect the preference of the eyeglass wearer…”
Regarding Claim 4: YEOMANS and LI teach The method of claim 1 further comprising
YEOMANS and LI do not appear to explicitly disclose
selecting the geometry of the lens-side portion of the goggle frame from a plurality of predetermined geometries of the lens-side portion of the goggle frame.
However, SAIGO selecting the geometry of the lens-side portion of the goggle frame from a plurality of predetermined geometries of the lens-side portion of the goggle frame (Abstract and Figs. 16-18 and 20 [shown above in claim 2] SAIGO “…the input of predetermined data, lens material data and lens design data with the selected spectacle frame shape data integration and simulation similar to the actual spectacle wearing state, can more easily and accurately determine the personal like of glasses. provides more data of the information relative to the frame. by comprising a frame picture and frame-related text and voice to make selection easier. In addition, by actively introduced by comparing two same display selected eyeglasses of spectacles try-on paired comparison and selection screen of the screen is selected…”)
YEOMANS, LI, and SAIGO are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the defining geometry of one or more vent flange portions of the goggle frame which connect the face flange portion to a geometry of a lens-side portion of the goggle frame to generate the custom 3D model of the goggle frame as disclosed by YEOMANS and LI by selecting the geometry of the lens-side portion of the goggle frame from a plurality of predetermined geometries of the lens-side portion of the goggle frame as disclosed by SAIGO.
One of ordinary skill in the art would have been motivated to make this modification in order to improve selection base on the wearer as discussed on pg. 2 paragraph 2 of the translation by SAIGO “…Besides, it also claims a method for selecting an appropriate lens shape of the eyeglass wearer faceshape according to a predetermined design rule wherein the computer. However, this method does notfully reflect the preference of the eyeglass wearer…”
Claims 5-12, 14-16, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over
YEOMANS et al., U.S. Patent Application Publication 2019/0381361 A1 (hereinafter ‘YEOMANS’) in view of
LI et al., U.S. Patent Application Publication 2021/0259886 A1 (hereinafter ‘LI’) further in view of
VARADY et al., U.S. Patent Application Publication 2018/0336737 A1 (hereinafter ‘VARADY’).
Regarding Claim 5: YEOMANS and LI teach The method of claim 1 further comprising
YEOMANS and LI do not appear to explicitly disclose
receiving face landmark data together with the 3D face scan data.
However, VARADY teaches receiving face landmark data together with the 3D face scan data. ([0036] VARADY “…Such an embodiment may include detecting features of an object of unknown size ( e.g., a face). For example, one step may include detecting facial landmarks in one or more 2D images of the capture, and using the landmarks to determine an initial camera pose…”)
YEOMANS, LI, and VARADY are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the wherein the generating the custom 3D model of the goggle frame includes: defining geometry of a face flange portion of the goggle frame based, at least in part, on the 3D face scan data as disclosed by YEOMANS and LI by receiving face landmark data together with the 3D face scan data as disclosed by VARADY.
One of ordinary skill in the art would have been motivated to make this modification in order to adjust the image data collected as discussed in paragraph [0008] of VARADY “…Scale measurement via a single image can be incorrectly derived due to a number of errors that can be introduced during this setup. A perfect measurement may be achieved if the assumption that the card and face are in the same plane is true. If, however, the card is closer or farther away from the camera than the eyes ( or other facial features being measured), the derived scale will be incorrect because the card will appear a different size than it would if it were at the same distance as the item to be measured. In other words, the card may appear larger relative to the face if closer to the camera, which may result in a scale determination of the face that is too small. Conversely, the card may appear smaller relative to the face if it is farther from the camera, which may result in a scale determination that will be too large. An assumption of the difference in z-plane can be made, but any deviation from said assumption will introduce error. Additionally, if the card is not aligned with respect to the face (or eyes, or other features to be measured), then the scale measurement will also be incorrect…”
Regarding Claim 6: YEOMANS, LI, and VARADY teach The method of claim 5 further comprising
LI teaches importing the 3D face scan data into a computer-aided design (CAD) program together with an existing CAD model containing at least the geometry of the lens-side portion of the goggle frame. ([0031] LI “…S3: establishing a personalized medical isolation goggles model: import the point cloud data of the medical isolation goggles matrix in Sl and the point cloud data of the user in S2 into 3D software for Boolean operations, where the Boolean operations include merging, cutting, and intersecting; and form, by merging and cutting, a personalized medical isolation goggles model conforming to the user's face. Preferably, the 3D software is Solid Works or Autodesk Maya…”)
Regarding Claim 7: YEOMANS, LI, and VARADY teach The method of claim 6
VARADY teaches wherein the data for the 3D representation of at least a portion of the face of the user includes a 3D mesh representation of at least a portion of the face of the user, and the method further comprising aligning the 3D mesh of the 3D face scan data to the existing CAD model using the face landmark data. ([0086] VARADY “…In one embodiment, local facial deformation can occur as a user's expression changes during capture of digital input. This may be due to user smiling or talking during the capture. The exemplary systems and methods disclosed herein may anticipate and account for local facial deformation during capture of digital input and robustly reconstruct a 3D face by tracking these facial deformations and non-rigidly morphing a reconstructed 3D face mesh to align with the image data of the digital input. The non-rigid deformation to align with a subject's face may be performed independent of a learned 3D shape space model (e.g., of a the subject's face), and need not be constrained by it…”)
Regarding Claim 8: YEOMANS, LI, and VARADY teach The method of claim 7
VARADY teaches wherein the aligning of the 3D mesh to the existing CAD model comprises aligning pupil center landmark points to predetermined horizontal and vertical locations of the CAD model. ([0128] VARADY “…In addition to scaling a 3D face model relative to the calibration target, a 3D model may further be scaled relative to the position of detected and aligned face landmarks, e.g., a user's pupils, irises, any other facial features or dimensions, or a combination thereof. Pupil detection in digital input ( e.g., a video/series of images for scaling in the presence of a calibration target) can also be used to measure and scale both distance and near pupillary distance using the methods described herein…”)
Regarding Claim 9: YEOMANS, LI, and VARADY teach The method of claim 7 further comprising
VARADY teaches defining goggle limiting geometry based on one or more components of the existing CAD model and aligning the 3D mesh to the goggle limiting geometry. ([0108] VARADY “…Step 307 may then include using the relative 3D locations shown by the image to position the calibration target and the object of unknown size in a single 3D coordinate system. In other words, step 307 may include using relative positions shown by received digital input to position the calibration target and the object of unknown size in the same 3D coordinate system. Once the calibration target and the object of unknown size are aligned/positioned in the same 3D coordinate system, step 307 may proceed to measuring the calibration target and the object of unknown size with respect to the other in 3D space and then determining a scaling factor between the calibration target and the object of unknown size. In one embodiment, the image described above may include an image with a short exposure duration so as to freeze any motion in time. If there are a series of images in which it is determined that relative motion is not occurring, all of the images in the series of images can be used to position both in the same 3D space (so as to not introduce error from only one frame or one series of measurements)…”)
Regarding Claim 10: YEOMANS, LI, and VARADY teach The method of claim 9 further comprising
VARADY teaches trimming the 3D mesh of the 3D face scan data to obtain a partial 3D face mesh prior to aligning the 3D mesh to the goggle limiting geometry. ([0068] VARADY “…Assessment platform 101 may still use a mask to speed up the processing by isolating the subject and eliminating a large number of pixels (background) that are not material to the problem at hand, but such a mask can be looser fitting so as to not accidentally crop useful area of the subject…”)
Regarding Claim 11: YEOMANS, LI, and VARADY teach The method of claim 10 further comprising
VARADY teaches increasing a coarseness of the partial 3D mesh prior to aligning the 3D mesh to the goggle limiting geometry. ([0123] VARADY “…Implicit geometry constraints may be used to help with initial detection or refine each initial detection. Image patches that are analyzed can be scaled up or down based on image resolution so they can be executed at the same resolution that they were trained ( or inversely, the image can be scaled up or down to match the training resolution). Further refinements to the detected landmarks ( or corner( s)) of the calibration target can be performed via image processing techniques, e.g., circle and line detection (Hough transform, image gradients, etc.). If an image was downsampled in order to match a training dataset's resolution, an original full resolution image can be used for image processing to leverage the advantage of additional pixels without down-sampling artifacts. The length and width of the boundaries or bounding box(s) for image processing can also be scaled based on resolution so the same approximate size in real world measurements ( e.g., millimeters) can be analyzed regardless of pixel resolution. Therefore, a higher resolution image may have a larger bounding box than the same image that was down-sampled to a lower resolution…”)
Regarding Claim 12: YEOMANS, LI, and VARADY teach The method of claim 9
LI teaches wherein the existing CAD model further comprises geometry for at least one of strap outriggers and a nose piece of the goggle frame, and wherein the goggle limiting geometry is further based on the geometry of the strap outriggers and/or the geometry of the nose piece. ([0034] LI “…In this example, the medical isolation goggles lace is an elastic band, and a buckle is arranged at a joint of the elastic band, thereby facilitating the adjustment of tightness. The air holes 2 enable the personalized medical isolation goggles to form airflow circulation when in use. This improves the breathability of the medical isolation goggles and meets the technical requirements of the personal eye protection standard. The curved nose bracket 5 highly fits the user's face, which improves use comfort…”)
Regarding Claim 14: YEOMANS and LI teach The method of claim 13
YEOMANS and LI do not appear to explicitly disclose
wherein the 3D face scan data of at least a portion of the face of the user is obtained using the scanner as the face of the user is rotated through a range of angles relative to the scanner.
However, VARADY teaches wherein the 3D face scan data of at least a portion of the face of the user is obtained using the scanner as the face of the user is rotated through a range of angles relative to the scanner. ([0131] VARADY “…In general, building a 3D model of a scene from multiple 2D images of differing vantage points ( e.g., camera positions) may involve … the movement of the object(s) relative to a stationary camera(s)…”)
YEOMANS, LI, and VARADY are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the wherein the 3D face scan data is obtained using a scanner as disclosed by YEOMANS and LI by wherein the 3D face scan data of at least a portion of the face of the user is obtained using the scanner as the face of the user is rotated through a range of angles relative to the scanner as disclosed by VARADY.
One of ordinary skill in the art would have been motivated to make this modification in order to adjust the image data collected as discussed in paragraph [0008] of VARADY “…Scale measurement via a single image can be incorrectly derived due to a number of errors that can be introduced during this setup. A perfect measurement may be achieved if the assumption that the card and face are in the same plane is true. If, however, the card is closer or farther away from the camera than the eyes ( or other facial features being measured), the derived scale will be incorrect because the card will appear a different size than it would if it were at the same distance as the item to be measured. In other words, the card may appear larger relative to the face if closer to the camera, which may result in a scale determination of the face that is too small. Conversely, the card may appear smaller relative to the face if it is farther from the camera, which may result in a scale determination that will be too large. An assumption of the difference in z-plane can be made, but any deviation from said assumption will introduce error. Additionally, if the card is not aligned with respect to the face (or eyes, or other features to be measured), then the scale measurement will also be incorrect…”
Regarding Claim 15: YEOMANS and LI teach The method of claim 13
YEOMANS and LI do not appear to explicitly disclose
wherein the 3D face scan data of at least a portion of the face of the user is obtained using the scanner as the scanner is rotated through a range of angles relative to the face of the user.
However, VARADY teaches wherein the 3D face scan data of at least a portion of the face of the user is obtained using the scanner as the scanner is rotated through a range of angles relative to the face of the user. ([0131] VARADY “…In general, building a 3D model of a scene from multiple 2D images of differing vantage points ( e.g., camera positions) may involve movement of the camera(s) relative to a stationary scene…”)
YEOMANS, LI, and VARADY are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the wherein the 3D face scan data is obtained using a scanner as disclosed by YEOMANS and LI by wherein the 3D face scan data of at least a portion of the face of the user is obtained using the scanner as the scanner is rotated through a range of angles relative to the face of the user as disclosed by VARADY.
One of ordinary skill in the art would have been motivated to make this modification in order to adjust the image data collected as discussed in paragraph [0008] of VARADY “…Scale measurement via a single image can be incorrectly derived due to a number of errors that can be introduced during this setup. A perfect measurement may be achieved if the assumption that the card and face are in the same plane is true. If, however, the card is closer or farther away from the camera than the eyes ( or other facial features being measured), the derived scale will be incorrect because the card will appear a different size than it would if it were at the same distance as the item to be measured. In other words, the card may appear larger relative to the face if closer to the camera, which may result in a scale determination of the face that is too small. Conversely, the card may appear smaller relative to the face if it is farther from the camera, which may result in a scale determination that will be too large. An assumption of the difference in z-plane can be made, but any deviation from said assumption will introduce error. Additionally, if the card is not aligned with respect to the face (or eyes, or other features to be measured), then the scale measurement will also be incorrect…”
Regarding Claim 16: YEOMANS and LI teach The method of claim 1
YEOMANS and LI do not appear to explicitly disclose
wherein the 3D face scan data is generated from a sequence of images of the face of the user obtained using a camera.
However, VARADY teaches wherein the 3D face scan data is generated from a sequence of images of the face of the user obtained using a camera. ([0032] VARADY “…FIGS. 1, 6, and 7 will pertain to an exemplary method of obtaining digital input. In one embodiment, the digital input may be comprised of any data configured for providing the information for a 3D analysis. The digital input may include, for example, a series of images from a singular image sensor taken from different camera positions, a video taken from different camera positions, a series of images or a video taken from different perspectives with depth information included, a 3D point cloud captured from a depth or 3D sensor, a series of images from multiple 2D sensors, a video captured from multiple 2D sensors, etc…”)
YEOMANS, LI, and VARADY are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the wherein the generating the custom 3D model of the goggle frame includes: defining geometry of a face flange portion of the goggle frame based, at least in part, on the 3D face scan data as disclosed by YEOMANS and LI by wherein the 3D face scan data is generated from a sequence of images of the face of the user obtained using a camera as disclosed by VARADY.
One of ordinary skill in the art would have been motivated to make this modification in order to adjust the image data collected as discussed in paragraph [0008] of VARADY “…Scale measurement via a single image can be incorrectly derived due to a number of errors that can be introduced during this setup. A perfect measurement may be achieved if the assumption that the card and face are in the same plane is true. If, however, the card is closer or farther away from the camera than the eyes ( or other facial features being measured), the derived scale will be incorrect because the card will appear a different size than it would if it were at the same distance as the item to be measured. In other words, the card may appear larger relative to the face if closer to the camera, which may result in a scale determination of the face that is too small. Conversely, the card may appear smaller relative to the face if it is farther from the camera, which may result in a scale determination that will be too large. An assumption of the difference in z-plane can be made, but any deviation from said assumption will introduce error. Additionally, if the card is not aligned with respect to the face (or eyes, or other features to be measured), then the scale measurement will also be incorrect…”
Regarding Claim 27: YEOMANS and LI teach The method of claim 1
YEOMANS and LI do not appear to explicitly disclose
wherein defining the geometry of the face flange portion of the goggle frame comprises adjusting the face flange portion based on at least nostrils, temple, or combinations thereof of the face of the user.
However, VARADY teaches wherein defining the geometry of the face flange portion of the goggle frame comprises adjusting the face flange portion based on at least nostrils, temple, or combinations thereof of the face of the user. ([0097] VARADY “…FIG. 2B includes various examples of configurations and shapes that may be achieved by changing one or more of parameters of the parametric model 220. The parametric model 220 may include a representation of the eyewear product that may be modified to alter properties, including shape, size, color, finish, etc. The parametric model 220 may be adapted to a variety of shapes, sizes, and configurations to fit a diversity of face shapes and sizes. For example, nose pads of an initial parametric model of the eyewear product may not match the contour of the user's nose (e.g., from a user anatomic model). The initial parametric model may instead intersect with the surface of the nose if the initial parametric model is aligned with or overlaid over the user anatomic model. The assessment platform 101 may configure or modify the initial parametric model such that the nose pads match the contour and angle of the user's nose from the user anatomic model, e.g., the nose pads are modified to sit flush against the surface of the modeled user's nose. In some embodiments, parametric model 220 may be generated directly from user anatomic data, without obtaining an initial (e.g., generic) parametric model and modifying the initial model based on the user anatomic data. For example, parametric model 220 may be generated with a provided 3D model of the user's face/anatomic measurements of the user's face, with a 3D mesh or point cloud (e.g., from a depth sensor), and/or another method where a parametric model may be generated without modifying a pre-existing one…”)
YEOMANS, LI, and VARADY are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the wherein the generating the custom 3D model of the goggle frame includes: defining geometry of a face flange portion of the goggle frame based, at least in part, on the 3D face scan data as disclosed by YEOMANS and LI by wherein defining the geometry of the face flange portion of the goggle frame comprises adjusting the face flange portion based on at least nostrils, temple, or combinations thereof of the face of the user as disclosed by VARADY.
One of ordinary skill in the art would have been motivated to make this modification in order to adjust the image data collected as discussed in paragraph [0008] of VARADY “…Scale measurement via a single image can be incorrectly derived due to a number of errors that can be introduced during this setup. A perfect measurement may be achieved if the assumption that the card and face are in the same plane is true. If, however, the card is closer or farther away from the camera than the eyes ( or other facial features being measured), the derived scale will be incorrect because the card will appear a different size than it would if it were at the same distance as the item to be measured. In other words, the card may appear larger relative to the face if closer to the camera, which may result in a scale determination of the face that is too small. Conversely, the card may appear smaller relative to the face if it is farther from the camera, which may result in a scale determination that will be too large. An assumption of the difference in z-plane can be made, but any deviation from said assumption will introduce error. Additionally, if the card is not aligned with respect to the face (or eyes, or other features to be measured), then the scale measurement will also be incorrect…”
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over
YEOMANS et al., U.S. Patent Application Publication 2019/0381361 A1 (hereinafter ‘YEOMANS’) in view of
LI et al., U.S. Patent Application Publication 2021/0259886 A1 (hereinafter ‘LI’) further in view of
Schwartz, U.S. Patent Application Publication 2013/0174333 A1 (hereinafter ‘Schwartz’).
Regarding Claim 17: YEOMANS and LI teach The method of claim 1 further comprising
YEOMANS and LI do not appear to explicitly disclose
creating fitted face foam geometry, and wherein defining geometry of the face flange portion of the goggle frame is based, at least in part, on the fitted face foam geometry.
However, Schwartz teaches creating fitted face foam geometry, and wherein defining geometry of the face flange portion of the goggle frame is based, at least in part, on the fitted face foam geometry. ([0104] Schwartz “…FIG. 13 is a method and a device for varying the shape of the seal (16) to conform to the users orbit. This variation creates variable thickness of the seal (16). In the preferred embodiment the seal (16) would be made of gel and would be thinner closer to the nose and thicker away from the nose at the lateral margin of the orbit. This invention allows the variable and flexible seal (16) to serve as a conforming element of the goggle (10) to the human orbit, which is curved and varies with the variations that are present in humans of varying facial (20) shapes. Variations in the seal (16) and variations in the nosepiece (14) and the eyepiece (12) can all be adjusted to create a more unique fit for the user to include but not restricted to an adjustment to facial contours (20) and eye and orbital socket (18) and inter-papillary distance (19). Other materials can be used of variable thickness to conform to the orbit to include but not restricted to foam and silicon and other non-gelatinous elastomers…”)
YEOMANS, LI, and Schwartz are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the wherein the generating the custom 3D model of the goggle frame includes: defining geometry of a face flange portion of the goggle frame based, at least in part, on the 3D face scan data as disclosed by YEOMANS and LI by creating fitted face foam geometry, and wherein defining geometry of the face flange portion of the goggle frame is based, at least in part, on the fitted face foam geometry as disclosed by Schwartz.
One of ordinary skill in the art would have been motivated to make this modification in order to improve the seal on the design as discussed in [0006] of Schwartz “…For swimmers, finding goggles that properly fit and provide a watertight seal against the face is important. Unfortunately, it is estimated that approximately 50% of commonly worn goggles provide a watertight seal. While some goggles are designed to address the watertight problem by using seals made of gel material to create a watertight seal, these goggles do not address the problem of eye spacing variations and the anatomical facial differences of the users that cause poor fitting goggles…”
Claim 25 is rejected under 35 U.S.C. 103 as being unpatentable over
YEOMANS et al., U.S. Patent Application Publication 2019/0381361 A1 (hereinafter ‘YEOMANS’) in view of
LI et al., U.S. Patent Application Publication 2021/0259886 A1 (hereinafter ‘LI’) further in view of
Norman, U.S. Patent Application Publication 2011/0313878 A1 (hereinafter ‘Norman’).
Regarding Claim 25: YEOMANS and LI teach The method of claim 1
YEOMANS and LI do not appear to explicitly disclose
wherein the goggle customization process further comprises applying a unique marking to the custom 3D model of the goggle whereby the unique marking is reproduced on a goggle printed from the 3D-printer compatible file.
However, Norman teaches wherein the goggle customization process further comprises applying a unique marking to the custom 3D model of the goggle whereby the unique marking is reproduced on a goggle printed from the 3D-printer compatible file. ([0105] Norman “…FIG. 7 depicts a nested tray of assorted unique custom products, complete with identification markings affixed to the sprue of the product by the system in an automated fashion…”)
YEOMANS, LI, and Norman are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the outputting a 3D-printer compatible file of the custom 3D model of the goggle frame as disclosed by YEOMANS and LI by wherein the goggle customization process further comprises applying a unique marking to the custom 3D model of the goggle whereby the unique marking is reproduced on a goggle printed from the 3D-printer compatible fileas disclosed by Norman.
One of ordinary skill in the art would have been motivated to make this modification in order to improve the fficiency of the manufacturing process for customized products as discussed in paragraph [0002] of Norman “…The present invention relates to the design, sale and manufacture of made-to-order or mass-customized products. More specifically to a computer-based method and system for customer-driven design, sale and manufacturing of unique or custom-made product(s) exclusively through a highly efficient sales & manufacturing system which advantageously combines key elements of computer aided design methodologies, the interne and Additive Fabrication methodologies to personalize or customize said products…”
Claim 26 is rejected under 35 U.S.C. 103 as being unpatentable over
YEOMANS et al., U.S. Patent Application Publication 2019/0381361 A1 (hereinafter ‘YEOMANS’) in view of
LI et al., U.S. Patent Application Publication 2021/0259886 A1 (hereinafter ‘LI’) further in view of
Norman, U.S. Patent Application Publication 2011/0313878 A1 (hereinafter ‘Norman’) further in view of
Piontek, U.S. Patent Application Publication 2006/0053556 A1 (hereinafter ‘Piontek’).
Regarding Claim 26: YEOMANS, LI, and Norman teach The method of claim 25 wherein the unique marking comprises at least one of:
Norman teaches a unique identifier associating the custom 3D model to a specific customer; and ([0098] Norman “…FIG. 5 illustrates an embodiment of a method for the addition of identification markings on a product represented by 3D geometry which are added as a 3D appendage, placard, tab, or directly to a surface of a part or product to convey information, which can be carried digitally, about said part or product into human or machine readable form including information about the part, the date of manufacture, customer information or other pertinent information. The method can be carried out by one or more approaches to 3D geometry manipulation metholodigies, the location and content being defined by either a user or customer or automatically by the system, and the geometry being manifested, along with the geometry representing a user/customer product via one or more additive fabrication methodologies at the time of production of the user/customer product at one or more locations…”)
YEOMANS, LI, and Norman do not appear to explicitly disclose
information identifying the selected one of the plurality of face foams of pre-determined sizes.
However, Piontek teaches information identifying the selected one of the plurality of face foams of pre-determined sizes ([0076] Piontek “…For easy identification of size the facial cushions 31 would be marked with appropriate indicia 30 in writing showing a size designation or in the best current mode with indica in the form of color coding for easy identification. The color coding or written indica 30 to identify size could be imparted by extruding it in the color of the foam making up the facial cushion 31 or silkscreened or otherwise applied on the surface of the cushions 26, 28, and 31. Once the optimum dimensions of the facial cushion 31 are determined, yielding a comfortable fit and maximal pressure distribution about the face and sides of the patient's head, the facial cushion 31 is removably mounted to the interior of the helmet casing 12 using the aforementioned means for registered engagement of the facial cushion 31 with the helmet casing 12…”)
YEOMANS, LI, Norman, and Piontek are analogous art because they are from the same field of endeavor, user customization and selection.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the a unique identifier associating the custom 3D model to a specific customer as disclosed by YEOMANS, LI, and Norman by information identifying the selected one of the plurality of face foams of pre-determined sizes as disclosed by Piontek.
One of ordinary skill in the art would have been motivated to make this modification in order to accommodate different users based on the cushion required as discussed in paragraph [0021] by Piontek “…he device is best made of modular construction allowing for the substantially transparent helmet casing to fit a variety of different sized patients. Interchangeable and replaceable cushions of variable dimensions on one surface to accommodate different patient facial structures are positionable in a plurality of interchangeable light weight helmet casings. The cushions on their exterior surface are dimensioned for a registered fit with the helmet casing surface and apertures in the cushion register with apertures in the helmet casing. The cushions can also be color coded to designate different sizes to accommodate different sized patients…”
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter:
Claim 18 is 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. Claims 19-21, which depend from claim 18, are allowable per incorporation of the allowable subject matter form which the claims depend.
Claims 22-24 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims. It is noted, claims 22-24 are allowable per the interpreted dependency as discussed above in the rejection under 35 U.S.C. 112(b).
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chumbley et al., US 2018/0017815 A1 is cited in the corresponding EPO application. The reference does contain relevant information regarding eyewear, however, for reasons as discussed in the response from the Applicant to the EPO, the reference has not been applied in the current rejection. It is notable, paragraph [0077] contains node analysis which is relevant to claim 20.
Rasmussen et al., US 2013/0088490 A1 provides a scan of a user’s face for fitting eyewear. It also provides a unique ID for the user in the data (Fig. 7) and provides data based on selection of the style of classes and type of lens (Fig. 7).
Conclusion
Claims 1-17 and 22-27 are rejected.
Claims 18-21 are objected to.
Claims 28-29 were withdrawn.
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/JOHN E JOHANSEN/Examiner, Art Unit 2187
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