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 .
Claim Status
Claims 1-13 and 15-21 are currently pending in the application filed April 9 2024
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55 on April 9 2024.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on April 9 2024 have been considered by the Examiner.
Drawing
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the drawings for claim 1-3, 6-7, 10-12, 15-18 and 21 must be shown or the feature(s) canceled from the claim(s). No new matter should be entered.
Claims 1, 12 and 15 mention “stream of images” however drawing single snapshots not stream of images.
Claims 1, 2, 6, 7, 10, and 16-18 mention “plurality of dimensional parameters” however the drawings do not explicitly show lens width, lens height nor frame bridge width.
Claims 2, 3, and 6 mention “estimated pupillary distance” however the drawings do not show wearer’s eyes or pupillary distance movement.
Claim 10 mentions “reference code” on an arm of said frame however the drawings do not mention reference code on the frame.
Claim 11, and 21 mention “real-time bounding box”, however the drawings do not explicitly show real time bounding box provided by the neural network.
Abstract
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
The abstract of the currently filed disclosure contains language from the claims and is written with semi colons and colons throughout mirroring the claim language. Applicants are encouraged to rewrite the abstract of the disclosure as per the guidance of MPEP 608.01(b) to remove the form an legal phraseology and to be more narrative in nature.
Specification
The disclosure is objected to because of the following informalities:
[Page 5 Line 20] “may embodied” should be “may be embodied”
[Page 22 Line 10] “retrieving the at least lone optical parameter” should be “at least one optical parameter”
Appropriate correction is required.
Claim Objections
Claim 21 objected to because of the following informalities:
Claim 21: “wherein said method further comprises extracting said lens width and said lens height from a bounding box that is the smallest rectangle containing said ophthalmic lens” is repeated twice back to back.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, 6-7, and 15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Le Gallou (US11158082B2)
Regarding claim 1, Le Gallou teaches:
A method (Le Gallou, [Col 3 Line 7]; “A parameter determined by the method, which may be referred to as optical parameter” )
for estimating a position of an optical center (Le Gallou, [Col 13 Line 27]; “the computation of the optical center” ) of an ophthalmic lens mounted on a frame (Le Gallou, [Col 2 Line 59]; “ lens fitted in the frame” ) wherein an image of said frame (Le Gallou, [Col 3 Line 3]; “ spectacle frame”) is obtained by an image capture device. (Le Gallou, [Col 3 Line 5]; “ acquired by an image acquisition system.”)
the method comprising: detecting said ophthalmic lens (Le Gallou, [Col 4 Line 27] “characteristic point”) in a stream of images (Le Gallou, [Col 10 Line 23];“acquired images”) of said frame (Le Gallou, [Col 10 Line 23]; “the selected frame”) obtained by said image capture device(Le Gallou, [Col 3 Line 5]; “ acquired by an image acquisition system.”);
obtaining either a plurality of dimensional parameters of said frame (Le Gallou ,[Col 1 Line 57];“ optical parameters of the frame”) or a plurality of dimensional parameters of said ophthalmic lens (Le Gallou, [Col 1 Line 23];” determine optical parameters such as lens width, lens height”)
determining said estimated position of said optical center (Le Gallou, [Col 13 Line 53]; “the optical centers of the lenses … are given”) based on said detected ophthalmic lens (Le Gallou, [Col 13 Line 55]; “given by…lenses”) and either said plurality of frame dimensional parameters ((Le Gallou, [Col 14 Line 17]; “frame base” points, … situated perpendicularly to each optical center”), or said plurality of ophthalmic lens dimensional parameters (Le Gallou, [Col 13 Line 53]; “the optical centers of the lenses …expressed in the reference frame of the frame) are given by … lenses”).
Regarding claim 2, Le Gallou teaches:
obtaining the plurality of dimensional parameters of said frame(Le Gallou ,[Col 1 Line 57];“ optical parameters of the frame”) and obtaining an estimated pupillary distance(Le Gallou ,[Col 7 Line 53];“ the parameter determined is included in the following list: pupillary distance (PD);”), wherein said determining said estimated position of said optical center (Le Gallou, [Col 13 Line 27]; “the computation of the optical center” ) is based on said detected ophthalmic lens(Le Gallou, [Col 13 Line 55]; “given by…lenses”), said plurality of frame dimensional parameters((Le Gallou, [Col 13 Line 53]; “the optical centers of the lenses …expressed in the reference frame of the frame) are given by … lenses”). and said estimated pupillary distance (Le Gallou,[Col 1 Line 42];” The lens centering point is defined by the interpupillary distance Pd and by the pupillary height h.”)
Regarding claim 6, Le Gallou teaches:
wherein said plurality of ophthalmic lens dimensional parameters (Le Gallou, [Col 1 Line 22]; “determine optical parameters such as lens width, lens height, bridge width, … vertex distance”) comprises at least one of a dimension corresponding to a lens width and a dimension corresponding to a lens height (Le Gallou, [Col 1 Line 23]; “lens width, lens height,”) .
Regarding Claim 7, Le Gallou teaches:
wherein said plurality of frame dimensional parameters (Le Gallou, [Col 1 Line 22]; “determine optical parameters such as lens width, lens height, bridge width, … vertex distance”) comprises at least a dimension corresponding to a frame bridge width (Le Gallou, [Col 1 Line 23]; “ bridge width”)
Regarding Claim 15, Le Gallou teaches:
non-transitory information storage medium, characterized in that it stores on which is stored (Le Gallou, [Col 8 Line 43]; “a computer memory storing said computer program product”)one or more sequences of instructions that are accessible to a processor and that, when executed by said processor, cause said processor to implement (Le Gallou, [Col 8 Line 41]; “the invention also relates to a device comprising a screen, a plurality of cameras, a computer processor and a computer memory storing said computer program product”)
a method (Le Gallou, [Col 3 Line 7]; “A parameter determined by the method, which may be referred to as optical parameter” )
for estimating a position of an optical center (Le Gallou, [Col 13 Line 27]; “the computation of the optical center” ) of an ophthalmic lens mounted on a frame (Le Gallou, [Col 2 Line 59]; “ lens fitted in the frame” ) , an image of said frame (Le Gallou, [Col 3 Line 3]; “ spectacle frame”) being obtained by an image capture device (Le Gallou, [Col 3 Line 5]; “ acquired by an image acquisition system.”)
wherein said method comprises: detecting said ophthalmic lens (Le Gallou, [Col 4 Line 27] “characteristic point”) in a stream of images (Le Gallou, [Col 10 Line 23];“acquired images”) of said frame (Le Gallou, [Col 10 Line 23]; “the selected frame”) obtained by said image capture device (Le Gallou, [Col 3 Line 5]; “ acquired by an image acquisition system.”);
obtaining (282) either a plurality of dimensional parameters of said frame (Le Gallou ,[Col 1 Line 57];“ optical parameters of the frame”), either of said frame (140), or a plurality of dimensional parameters of said ophthalmic lens (Le Gallou, [Col 1 Line 23];” determine optical parameters such as lens width, lens height”);
and determining (284) said estimated position of said optical center(Le Gallou, [Col 13 Line 53]; “the optical centers of the lenses … are given”) based on said detected ophthalmic lens (Le Gallou, [Col 13 Line 55]; “given by…lenses”) and either said plurality of frame dimensional parameters (Le Gallou, [Col 14 Line 17]; “frame base” points, … situated perpendicularly to each optical center”), or said plurality of ophthalmic lens dimensional parameters. (Le Gallou, [Col 13 Line 53]; “the optical centers of the lenses …expressed in the reference frame of the frame) are given by … lenses”).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2) further in view of Guillen (FR2966038A1).
Regarding claim 3, Le Gallou fails to teach:
wherein said estimated pupillary distance is either an exact value, measured on a wearer of said ophthalmic lens (30), or an approximate value, obtained from a statistical model.
Guillen teaches:
wherein said estimated pupillary distance (Guillen, [Page 3 Paragraph 1]; “the pupillary distance”), is either an exact value (Guillen, [Page 3 Paragraph 1]; “the actual value of the pupillary distance”), measured on a wearer of said ophthalmic lens (Guillen, [Page 1 Paragraph 1]; “measuring the pupillary distance directly on the person concerned, using a measuring device”)or an approximate value, obtained from a statistical model (Guillen, [Page 3 Paragraph 2];“statistically determined;”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Guillen. The motivation for the combination is obtain either an estimated or actual pupillary distance value (Guillen, [Page 2 Paragraph 3]; “One objective of the invention is to provide a method … accurate measurement of the pupillary distance of the person whose pupillary distance they are trying to determine.”)
Claims 4 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2) further in view of Xia (CN107330878A).
Regarding claim 4, Le Gallou fails to teach:
wherein said detecting (280) said ophthalmic lens comprises using a neural network.
Xia teaches:
wherein said detecting (280) said ophthalmic lens (Xia, [Page 1 Line 47];“the step of performing edge detection on the corrected lens image sample to obtain lens information in the lens image”) comprises using a neural network (Xia, [Page 2 Line 72]; “the neural network model is a convolutional neural network model.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Xia. The motivation for the combination is apply neural networks for lens detection (Xia, [Page 2 Line 68]; “A training unit configured to train the neural network model using the lens information …identifies the lens information in the lens image samples”)
Regarding claim 5, Le Gallou fails to teach:
Wherein said detecting said ophthalmic lens comprises using an image processing algorithm.
Xia teaches:
Wherein said detecting said ophthalmic lens (Xia,[Page 1 Line 77]; “lens information “) comprises using an image processing algorithm (Xia,[Page 1 Line 77]; “Sobel edge detection algorithm “).(Xia, [Page 1 Line 77]; “Sobel edge detection algorithm to obtain lens information in the lens image sample.”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Xia. The motivation for the combination is application of image processing algorithm (Xia, [Page 1 Line 50 ]; “According to Sobel edge detection algorithm, edge detection is performed on the corrected image to obtain lens information in the lens image sample.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2) further in view of Thomet (CN113424098A).
Regarding claim 8, Le Gallou fails to teach:
wherein said method further comprises extracting said lens width and said lens height from a bounding box that is the smallest rectangle containing said ophthalmic lens
Thomet teaches:
wherein said method further comprises extracting said lens width and said lens height (Thomet, [Page 8 Line 466]; “the size (A and B size) of the frame rectangle 8 that defines the lens, and the size of their relative positions”) from a bounding box (Thomet, [Page 2 Line 116]; “Define the region of interest of the elements of the bounding box”) that is the smallest rectangle (Thomet, [Page 12 Line 704];“the region of interest … keep it small enough”) containing said ophthalmic lens (Thomet, [Page 6 Line 352]; “parameters defining the bounding rectangle of the lens”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Thomet. The motivation for the combination is apply the bounding box to extract the lens parameter through the bounding box. (Thomet, [352];“defining the bounding rectangle of the lens”)
Claims 9 and 10 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2) further in view of Komilov (US 8733936 B1).
Regarding claim 9, Le Gallou fails to teach:
wherein said method further comprises obtaining said frame bridge width as a statistical estimate based on a collection of frames.
Komilov teaches:
wherein said method further comprises obtaining said frame bridge width (Komilov, [Col 3 Line 46]; “The bridge length”) as a statistical estimate (Komilov, [Col 5 Line 45]; “Using the statistical approach”) based on a collection of frames (Komilov, [Col 2 Line 33]; “database of glasses frame information”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Komilov. The motivation for the combination is obtain frame bridge width as a statistical estimate. (Komilov, [Col 7 Line 27]; “ the penalty function in FIG. 8 could be used to evaluate the bridge length”)
Regarding claim 10, Le Gallou fails to teach:
wherein said obtaining said plurality of dimensional parameters, either of said frame, or of said ophthalmic lens, comprises using a neural network, or an image processing algorithm, or a database using a reference code on an arm of said frame, or a statistical model.
Komilov teaches:
wherein said obtaining said plurality of dimensional parameters (Komilov, [Col 2 Line 30]; “glasses frame information”), either of said frame, or of said ophthalmic lens, comprises using a neural network, or an image processing algorithm, or a database (Komilov, [Col 2 Line 30]; “database of glasses frame information“) using a reference code (Komilov, [Col 6 Line 4]; “Reference points”)on an arm of said frame, or a statistical model (Komilov, [Col 5 Line 45];“Using the statistical approach, the probability of mutual feature positions under different orientations for each image/video frame is calculated”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Komilov. The motivation for the combination is apply neural network/ image processing algorithm or database using a reference code to obtain dimensional parameters of lenses or frames (Komilov, Figure 2B)
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Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2), Xia (CN107330878A) further in view of Thomet (CN113424098A) and Shan (CN110852269A).
Regarding claim 11, the combination of Le Gallou and Xia fails to teach:
wherein said method further comprises extracting said lens width and said lens height from a bounding box that is the smallest rectangle containing said ophthalmic lens, and wherein said neural network provides said bounding box in real time.
Thomet teaches
wherein said method further comprises extracting said lens width and said lens height (Thomet, [Page 8 Line 466]; “the size (A and B size) of the frame rectangle 8 that defines the lens, and the size of their relative positions”)from a bounding box (Thomet, [Page 2 Line 116]; “Define the region of interest of the elements of the bounding box”) that is the smallest rectangle Thomet, [Page 12 Line 704];“the region of interest … keep it small enough”) containing said ophthalmic lens(Thomet, [Page 6 Line 352]; “parameters defining the bounding rectangle of the lens”)
Thomet fails to teach:
and wherein said neural network provides said bounding box in real time.
Shan teaches:
and wherein said neural network (Shan, [Page 7 Line 409]; “Multi-task convolutional neural network”) provides said bounding box in real time (Shan, [Page 2 Line 111]; “real-time correlation between the human target and the face target)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou and Xia with Thomet and Shan. The motivation for the combination is apply real time bounding box via neural network for extracting lens width and lens height. (Shan, [Page 2 Line 109]; “To obtain the bounding box of the face target can improve the timeliness of detecting and tracking the human target and the face target”)
Claims 12-13, and 16-18 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2) further in view of Zhang (US 10591752 B1).
Regarding claim 12, Le Gallou teaches:
A system (Le Gallou, [Col 17 Line 42]; “eyes+spectacles” system”)
implementing a method (Le Gallou, [Col 3 Line 7]; “A parameter determined by the method, which may be referred to as optical parameter” )
for estimating a position of an optical center (Le Gallou, [Col 13 Line 27]; “the computation of the optical center” ) of an ophthalmic lens mounted on a frame (Le Gallou, [Col 2 Line 59]; “ lens fitted in the frame” ) said
system comprising: at least one processor configured for: detecting said lens (Le Gallou, [Col 4 Line 27] “characteristic point”) in a stream of images (Le Gallou, [Col 10 Line 23];“acquired images”) of said frame (Le Gallou, [Col 10 Line 23]; “the selected frame”)
Obtaining either a plurality of dimensional parameters of said frame(Le Gallou ,[Col 1 Line 57];“ optical parameters of the frame”) or a plurality of dimensional parameters of said ophthalmic lens (Le Gallou, [Col 1 Line 23];” determine optical parameters such as lens width, lens height”)
and
determining said estimated position of said optical center (Le Gallou, [Col 13 Line 53]; “the optical centers of the lenses … are given”) based on said detected ophthalmic lens (Le Gallou, [Col 13 Line 55]; “given by…lenses”) and either said plurality of frame dimensional parameters, (Le Gallou, [Col 14 Line 17]; “frame base” points, … situated perpendicularly to each optical center”), or said plurality of ophthalmic lens dimensional parameters(Le Gallou, [Col 13 Line 53]; “the optical centers of the lenses …expressed in the reference frame of the frame) are given by … lenses”)
Le Gallou fails to teach:
and a mobile device equipped with an image capture device adapted to obtain said stream of images of said frame
Zhang teaches:
and a mobile device equipped with an image capture device (Zhang, [Col 3 Line 59]; “The front image can be captured using any type of camera known in the field such as a digital camera, smartphone camera, electronic tablet, or the like.”) adapted to obtain said stream of images of said frame (Zhang, [Col 7 Line 65]; “ takes one or more photographic images”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Zhang. The motivation for the combination is apply mobile device as an image capturing device (Zhang, [Col 3 Line 59]; “smartphone camera”)
Regarding claim 13, Le Gallou fails to teach:
wherein said mobile device is a smartphone and said image capture device is a smartphone camera
Zhang teaches:
wherein said mobile device is a smartphone (Zhang, [Col 3 Line 59]; “smartphone camera”)and said image capture device (Zhang, [Col 3 Line 59]; “The front image can be captured using any type of camera known in the field such as a digital camera, smartphone camera, electronic tablet, or the like.”) is a smartphone camera (Zhang, [Col 3 Line 59]; “smartphone camera”)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou with Zhang. The motivation for the combination is apply smartphone camera as an image capturing device (Zhang, [Col 3 Line 59]; “smartphone camera”)
Regarding claim 16,the combination of Le Gallou and Zhang teaches:
wherein the at least one processor (Le Gallou, [Col 8 Line 41]; “the invention also relates to a device comprising a screen, a plurality of cameras, a computer processor and a computer memory storing said computer program product”) is further configured for: obtaining the plurality of dimensional parameters of said frame (Le Gallou ,[Col 1 Line 57];“ optical parameters of the frame”) ; and obtaining an estimated pupillary distance(Le Gallou ,[Col 7 Line 53];“ the parameter determined is included in the following list: pupillary distance (PD);”), wherein said determining said estimated position of said optical center(Le Gallou, [Col 13 Line 27]; “the computation of the optical center” ) is based on said detected ophthalmic lens (Le Gallou, [Col 13 Line 55]; “given by…lenses”), said plurality of frame dimensional parameters and said estimated pupillary distance(Le Gallou,[Col 1 Line 42];” The lens centering point is defined by the interpupillary distance Pd and by the pupillary height h.”)
Regarding claim 17, the combination of Le Gallou and Zhang teaches:
wherein said plurality of ophthalmic lens dimensional parameters (Le Gallou, [Col 1 Line 22]; “determine optical parameters such as lens width, lens height, bridge width, … vertex distance”) comprises at least one of a dimension corresponding to a lens width and a dimension corresponding to a lens height(Le Gallou, [Col 1 Line 23]; “lens width, lens height,”)
Regarding claim 18, the combination of Le Gallou and Zhang teaches:
wherein said plurality of frame dimensional parameters (Le Gallou, [Col 1 Line 22]; “determine optical parameters such as lens width, lens height, bridge width, … vertex distance”) comprises at least a dimension corresponding to a frame bridge width (Le Gallou, [Col 1 Line 23]; “ bridge width”)
Claims 19 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2), Zhang (US 10591752 B1) further in view of Komilov (US 8733936 B1).
Regarding claim 19, the combination of Le Gallou and Zhang fail to teach:
wherein said method further comprises obtaining said frame bridge width as a statistical estimate based on a collection of frames.
Komilov teaches:
wherein said method further comprises obtaining said frame bridge width (Komilov, [Col 3 Line 46]; “The bridge length”) as a statistical estimate (Komilov, [Col 5 Line 45]; “Using the statistical approach”) based on a collection of frames (Komilov, [Col 2 Line 33]; “database of glasses frame information”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou and Zhang with Komilov. The motivation for the combination is obtain frame bridge width as a statistical estimate. (Komilov, [Col 7 Line 27]; “ the penalty function in FIG. 8 could be used to evaluate the bridge length”)
Claims 20 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2) and Zhang (US 10591752 B1) further in view of Thomet (CN113424098A).
Regarding claim 20, the combination of Le Gallou and Zhang fail to teach:
wherein said method further comprises extracting said lens width and said lens height from a bounding box that is the smallest rectangle containing said ophthalmic lens.
Thomet teaches
wherein said method further comprises extracting said lens width and said lens height (Thomet, [Page 8 Line 466]; “the size (A and B size) of the frame rectangle 8 that defines the lens, and the size of their relative positions”) from a bounding box (Thomet, [Page 2 Line 116]; “Define the region of interest of the elements of the bounding box”) that is the smallest rectangle (Thomet, [Page 12 Line 704];“the region of interest … keep it small enough”) containing said ophthalmic lens (Thomet, [Page 6 Line 352]; “parameters defining the bounding rectangle of the lens”).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou and Zhang with Thomet. The motivation for the combination is apply the bounding box to extract the lens parameter through the bounding box. (Thomet, [352];“defining the bounding rectangle of the lens”)
Claims 21 is rejected under 35 U.S.C. 103 as being unpatentable over Le Gallou (US11158082B2) and Zhang (US 10591752 B1) further in view of Thomet (CN113424098A) and Shan (CN110852269A).
Regarding claim 21, the combination of Le Gallou and Zhang fail to teach:
wherein said method further comprises extracting said lens width and said lens height from a bounding box that is the smallest rectangle containing said ophthalmic lens, and wherein said method further comprises extracting said lens width and said lens height from a bounding box that is the smallest rectangle containing said ophthalmic lens, and wherein said neural network provides said bounding box in real time.
Thomet teaches:
wherein said method further comprises extracting said lens width and said lens height (Thomet, [Page 8 Line 466]; “the size (A and B size) of the frame rectangle 8 that defines the lens, and the size of their relative positions”)from a bounding box (Thomet, [Page 2 Line 116]; “Define the region of interest of the elements of the bounding box”) that is the smallest rectangle Thomet, [Page 12 Line 704];“the region of interest … keep it small enough”) containing said ophthalmic lens(Thomet, [Page 6 Line 352]; “parameters defining the bounding rectangle of the lens”)
Thomet fails to teach:
and wherein said neural network provides said bounding box in real time.
Shan teaches:
and wherein said neural network (Shan, [Page 7 Line 409]; “Multi-task convolutional neural network”) provides said bounding box in real time (Shan, [Page 2 Line 111]; “real-time correlation between the human target and the face target)
Before the time of filing, it would have been obvious to one of ordinary skill in the art to combine Le Gallou and Xia with Thomet and Shan. The motivation for the combination is apply real time bounding box via neural network for extracting lens width and lens height. (Shan, [Page 2 Line 109]; “To obtain the bounding box of the face target can improve the timeliness of detecting and tracking the human target and the face target”)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHIVANGI SARKAR whose telephone number is (571)272-7262. The examiner can normally be reached M-F: 7:30-5:00.
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/SHIVANGI SARKAR/Examiner, Art Unit 2666
/EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666
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