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 .
The following is a Final Office Action in response to communications received on 10/23/2025. Claims 1-13, 15-21 are currently pending and have been examined. Claims 1, 2, 3, 7-13, 15-21 have been amended. Claim 14 is cancelled.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Step 1: The claims 1-11 are a system, claims 12-13, 15-20 are a method, and claims 21 is a computer readable medium. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101. However, the claims 1-13 and 15-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A Prong 1: The independent claims (1, 12 and 21, taking claim 1 as a representative claim) recite:
An information processing apparatus for facial feature-based makeup recommendation, the apparatus comprising: one or more processors, coupled with memory, to:
receive, via a client device, face information on a user's face and needs information on the user's needs regarding makeup;
specify a feature quantity of the user's face based on the face information;
determine, using a recommendation model, recommendation makeup information on the makeup recommended for the user based on a correlation between the specified feature quantity, the needs information, and makeup information on the makeup;
present, via the client device, the determined recommendation makeup information to the user; and
receive, via the client device, to update the recommendation model, evaluation information on evaluation of the recommendation makeup information from the user who has applied the makeup after the recommendation makeup information is presented.
These limitations, except for the italicized portions, under their broadest reasonable interpretations, recite certain methods of organizing human activity for managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as well as commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). The claimed invention recites steps for receiving information about a user’s facial features and needs, making a recommendation of makeup to the user, and receiving evaluation information from the user about the recommended makeup. The steps under its broadest reasonable interpretation specifically fall under sales activities. The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
Additionally, these limitations, except for the italicized portions, under their broadest reasonable interpretations, recite a mental process. The claimed invention recites steps for receiving information about a user’s facial features and needs, making a recommendation of makeup to the user, and receiving evaluation information from the user about the recommended makeup which could be done by another user through observation and judgement. A human could observer the facial features of the user, discuss their needs, and based on their knowledge make a recommendation. Next, ask for feedback about the recommendation from the user. The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
Prong 2: This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of
An information processing apparatus for facial feature-based makeup recommendation, the apparatus comprising: one or more processors, coupled with memory, to: (claim 1)
An information processing method causing a computer executing the steps of: (claim 12)
A non-transitory computer readable medium including one or more instructions stored thereon and executable by a processor to: (claim 21)
Via a client device
The additional elements of emphasized above are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do not integrate the abstract idea into a practical application – MPEP 2106.05(f).
Accordingly, these additional elements when considered individually or as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The independent claims are directed to an abstract idea.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong two, the additional elements in the claims amount to no more than mere instructions to apply the judicial exception using a generic computer component.
Dependent claims 2-11, 13, and 15-20 when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. §101 because the additional recited limitations fail to establish that the claims are not directed to the same abstract idea of Independent Claims 1, 12 and 21 without significantly more.
Claims 2 and 13 recite wherein the one or more processors are configured to determine determines the recommendation makeup information based on a history of the evaluation information associated with user identification information that identifies the user. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
Claim 3 and 15 recite further comprising: the memory configured to store the recommendation model, wherein the
Claim 4 and 16 recite wherein the recommendation makeup information includes at least one of information on a makeup product recommended to the user, information on a makeup method recommended to the user, and information on why the makeup product and the makeup method is recommended to the user. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
Claim 5 and 17 recite wherein the needs information includes at least one of information on direction of makeup, information on usage scenes of makeup, information on makeup tools possessed by the user, and information on skin troubles of the user. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
Claim 6 and 18 recite wherein the needs information includes at least one of information on the user's makeup preferences, information on the user's attributes, information on the user's makeup skill level, and information on the user's facial features concerns. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
Claim 7 and 19 recite wherein the evaluation information includes at least one of information on an evaluation of preference, an evaluation of a color tone of the recommended makeup product, an evaluation of impression given by makeup, and an evaluation of makeup technique. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
Claim 8 and 20 recite further comprising the one or more processors to receive, from the user, information that the user wants to obtain the recommended makeup product, wherein the one or more processors configured to receive the evaluation information receives the evaluation information from the user obtaining the recommended makeup product. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
Claim 9 recites the apparatus of claim 1,further comprising the one or more processors configured to receive, from the user, a makeup face image of the user to which the makeup applied based on the recommendation makeup information, wherein the one or more processors configured to receive the evaluation information receives the evaluation information from the user whose makeup face image is received. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
Claim 10 recites the apparatus of claim 3, further comprising:
Claim 11 recites the apparatus of claim 1, further comprising a the one or more processors configured to present a reward to the user inputting the evaluation information. The claim merely further limits the abstract idea and does not integrate the abstract idea into a practical application.
For these reasons claims 1-13 and 15-21 are rejected under 35 USC 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim 1-7, 9-10, 12-13, and 15-21 are rejected under 35 U.S.C. 103 as being unpatentable over Yang (US 20220211163) in view of Satori (US 20180075523).
Regarding claims 1, 12, and 21, Yang discloses:
An information processing apparatus for facial feature-based makeup recommendation, the apparatus comprising: one or more processors, (processor [0025]) coupled with memory, to: (claim 1) (Figure 6- makeup assistance apparatus)
An information processing method for facial feature-based makeup recommendation, the method comprising (claim 12) (Figure 6- makeup assistance apparatus)
A non-transitory computer readable medium including one or more instructions stored thereon and executable by a processor to: (claim 21) (Figure 6- makeup assistance apparatus)
Receive, via a client device [0042] The smart mirror and such terminal devices each may be equipped with a display for displaying images and an imaging device for capturing images of users, such as a camera., face information on a user's face (facial features) and needs information on the user's needs regarding makeup (skin quality);
specify a feature quantity (a positional relationship of the facial features) of the user's face based on the face information; ([0063] The facial feature point extraction may comprise the extraction of information about the facial features. The make-up information extraction may comprise determining a positional relationship of the facial features by performing matching. The facial skin quality assessment may comprise generation of a make-up plan based on skin quality.)
present, via the client device [0042], the determined recommendation makeup information to the user; and ([0139] The presentation unit 47 is configured to present at least one make-up plan determined by the makeup matching server by performing matching according to the face make-up region.)
While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, the reference does not explicitly disclose:
determine, using a recommendation model, recommendation makeup information on the makeup recommended for the user based on a correlation between the specified feature quantity, the needs information, and makeup information on the makeup;
receive, via the client device, to update the recommendation model, evaluation information on evaluation of the recommendation makeup information from the user who has applied the makeup after the recommendation makeup information is presented.
However Satori teaches:
determine, using a recommendation model, recommendation makeup information on the makeup recommended for the user based on a correlation between the specified feature quantity, the needs information, and makeup information on the makeup; [0095] In some embodiments, the looks displayed via menu 916i may include user-specific recommendations for combinations of makeup products. For example, a user may load an image of their face (e.g., via option 902). The loaded image may be analyzed by platform 120 (e.g., by using the previously described feature detection processes and/or any other computer vision processes) to determine certain characteristics of the face depicted in the loaded image. For example, analysis performed on the image may detect a general shape of the face, shapes and arrangement of certain key features (e.g., eyes, nose, mouth, etc.), hair color and texture, and skin tone. Based on the detected characteristics, platform 120 may generate one or more recommended looks that are specifically tailored to the characteristics of the face in the loaded image. In some embodiments, product recommendations may be based on a user-specific product browsing or selection history. For example, the system may recommend a look that includes a makeup product previously selected by the user. [0096] Product recommendations may be based on objective and or subjective “rules” such as general color combination rules (e.g., primary vs. secondary color combinations), specific application rules (e.g., product combinations for daytime vs. nighttime usage), makeup effects and predetermined goals (e.g., applying bronzer to define or sculpt certain facial features), etc.. In some embodiments, these rules may be generated by one or more expert makeup artists, manufacturers/designers, retailers, etc.. For example, in an embodiment, retailer (such as a department store) may individually define certain makeup recommendation rules to generate looks that are selectable via menu 916i. Alternatively or in addition, individual makeup artists or designers may define their own recommendation rules to automatically generate user selectable looks via menu 916i. In some embodiments, look recommendations may be automatically generated using machine-learning based models, for example based on historical aesthetic feedback data. For example, although not shown in screen 900i, in some embodiments, users may be presented with options to rate makeup products and looks, both in general and as applied to their specific facial features.
receive, via the client device, to update the recommendation model, In some embodiments, look recommendations may be automatically generated using machine-learning based models, for example based on historical aesthetic feedback data. evaluation information on evaluation of the recommendation makeup information from the user who has applied the makeup after the recommendation makeup information is presented. [0096] For example, although not shown in screen 900i, in some embodiments, users may be presented with options to rate makeup products and looks, both in general and as applied to their specific facial features.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang to include the limitations above, as taught in Satori, in order to produce a composite image that simulate the application of a corresponding real-world makeup product (paragraph 0025).
Regarding claims 2 and 13, Yang in view of Satori teaches the limitations set for the above. While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, the reference does not explicitly disclose:
one or more processors are configured to determine the recommendation makeup information based on a history of the evaluation information associated with user identification information that identifies the user.
However Satori teaches:
one or more processors are configured to determine the recommendation makeup information based on a history of the evaluation information associated with user identification information that identifies the user. [0095-0096] In some embodiments, product recommendations may be based on a user-specific product browsing or selection history. For example, the system may recommend a look that includes a makeup product previously selected by the user. In some embodiments, look recommendations may be automatically generated using machine-learning based models, for example based on historical aesthetic feedback data. For example, although not shown in screen 900i, in some embodiments, users may be presented with options to rate makeup products and looks, both in general and as applied to their specific facial features.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang to include the limitations above, as taught in Satori, in order to produce a composite image that simulate the application of a corresponding real-world makeup product (paragraph 0025).
Regarding claims 3 and 15, Yang in view of Satori teaches the limitations set for the above. While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, the reference does not explicitly disclose:
further comprising: the memory configured to store the recommendation model, wherein the one or more processors are configured to determine that the recommendation makeup information refers to the recommendation model and determine that the recommendation makeup information corresponds to a combination of the specified feature quantity and the received needs information as the recommendation makeup information; and the one or more processors are configured to modify the recommendation model based on the received evaluation information.
However Satori teaches:
further comprising: the memory configured to store the recommendation model, wherein the one or more processors are configured to determine that the recommendation makeup information refers to the recommendation model and determine that the recommendation makeup information corresponds to a combination of the specified feature quantity and the received needs information as the recommendation makeup information; and the one or more processors are configured to modify the recommendation model based on the received evaluation information. [0095] In some embodiments, the looks displayed via menu 916i may include user-specific recommendations for combinations of makeup products. For example, a user may load an image of their face (e.g., via option 902). The loaded image may be analyzed by platform 120 (e.g., by using the previously described feature detection processes and/or any other computer vision processes) to determine certain characteristics of the face depicted in the loaded image. For example, analysis performed on the image may detect a general shape of the face, shapes and arrangement of certain key features (e.g., eyes, nose, mouth, etc.), hair color and texture, and skin tone. Based on the detected characteristics, platform 120 may generate one or more recommended looks that are specifically tailored to the characteristics of the face in the loaded image. In some embodiments, product recommendations may be based on a user-specific product browsing or selection history. For example, the system may recommend a look that includes a makeup product previously selected by the user. [0096] Product recommendations may be based on objective and or subjective “rules” such as general color combination rules (e.g., primary vs. secondary color combinations), specific application rules (e.g., product combinations for daytime vs. nighttime usage), makeup effects and predetermined goals (e.g., applying bronzer to define or sculpt certain facial features), etc.. In some embodiments, these rules may be generated by one or more expert makeup artists, manufacturers/designers, retailers, etc.. For example, in an embodiment, retailer (such as a department store) may individually define certain makeup recommendation rules to generate looks that are selectable via menu 916i. Alternatively or in addition, individual makeup artists or designers may define their own recommendation rules to automatically generate user selectable looks via menu 916i. In some embodiments, look recommendations may be automatically generated using machine-learning based models, for example based on historical aesthetic feedback data. For example, although not shown in screen 900i, in some embodiments, users may be presented with options to rate makeup products and looks, both in general and as applied to their specific facial features.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang to include the limitations above, as taught in Satori, in order to produce a composite image that simulate the application of a corresponding real-world makeup product (paragraph 0025).
Regarding claims 4 and 16, Yang in view of Satori teaches the limitations set for the above. Yang further discloses:
wherein the recommendation makeup information includes at least one of information on a makeup product recommended to the user, information on a makeup method recommended to the user ([0108 …determine at least one makeup plan conforming to the user requirement for the user to select. For example, the makeup plan may include cosmetics and see [0049]), and information on why the makeup product and the makeup method is recommended to the user.
Regarding claims 5 and 17, Yang in view of Satori teaches the limitations set for the above. Yang further discloses:
wherein the needs information includes at least one of information on direction of makeup ([0049] the make-up plan may comprise a description of the make-up steps and a corresponding makeup effect image.), information on usage scenes of makeup, information on makeup tools possessed by the user, and information on skin troubles of the user.
Regarding claims 6 and 18, Yang in view of Satori teaches the limitations set for the above. Yang further discloses:
wherein the needs information includes at least one of information on the user's makeup preferences, ([0151] providing the user with a make-up plan according to the user's personalized needs, so that the user may further modify the make-up effect image according to his/her preference,) information on the user's attributes, information on the user's makeup skill level, and information on the user's facial features concerns.
Regarding claims 7 and 19, Yang in view of Satori teaches the limitations set for the above.
While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, the reference does not explicitly disclose:
wherein the evaluation information includes at least one of information on an evaluation of preference, an evaluation of a color tone of the recommended makeup product, an evaluation of impression given by makeup, and an evaluation of makeup technique.
However Satori teaches:
wherein the evaluation information includes at least one of information on an evaluation of preference, an evaluation of a color tone of the recommended makeup product, an evaluation of impression given by makeup, and an evaluation of makeup technique. [0096] Alternatively or in addition, individual makeup artists or designers may define their own recommendation rules to automatically generate user selectable looks via menu 916i. In some embodiments, look recommendations may be automatically generated using machine-learning based models, for example based on historical aesthetic feedback data. For example, although not shown in screen 900i, in some embodiments, users may be presented with options to rate makeup products and looks, both in general and as applied to their specific facial features.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang to include the limitations above, as taught in Satori, in order to produce a composite image that simulate the application of a corresponding real-world makeup product (paragraph 0025).
Regarding claim 9, Yang in view of Satori teaches the limitations set for the above.
While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, the reference does not explicitly disclose:
further comprising the one or more processors configured to receive, from the user, a makeup face image of the user to which the makeup applied based on the recommendation makeup information,
wherein the one or more processors configured to receive the evaluation information receives the evaluation information from the user whose makeup face image is received.
However Satori teaches:
further comprising the one or more processors configured to receive, from the user, a makeup face image of the user to which the makeup applied based on the recommendation makeup information, [0095] In some embodiments, the looks displayed via menu 916i may include user-specific recommendations for combinations of makeup products. For example, a user may load an image of their face (e.g., via option 902). The loaded image may be analyzed by platform 120 (e.g., by using the previously described feature detection processes and/or any other computer vision processes) to determine certain characteristics of the face depicted in the loaded image.
wherein the one or more processors configured to receive the evaluation information receives the evaluation information from the user whose makeup face image is received. [0096] In some embodiments, look recommendations may be automatically generated using machine-learning based models, for example based on historical aesthetic feedback data. For example, although not shown in screen 900i, in some embodiments, users may be presented with options to rate makeup products and looks, both in general and as applied to their specific facial features.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang to include the limitations above, as taught in Satori, in order to produce a composite image that simulate the application of a corresponding real-world makeup product (paragraph 0025).
Regarding claim 10, Yang in view of Satori teaches the limitations set for the above.
While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, the reference does not explicitly disclose:
the one or more processors configured to refer to the modified recommendation model and redetermine recommendation makeup information corresponding to the combination of the specified feature quantity and the received needs information as the recommendation makeup information;
the one or more processors configured to present the re-determined redetermined recommendation makeup information to the user.
However Satori teaches:
the one or more processors configured to refer to the modified recommendation model and redetermine recommendation makeup information corresponding to the combination of the specified feature quantity and the received needs information as the recommendation makeup information; [0095] In some embodiments, the looks displayed via menu 916i may include user-specific recommendations for combinations of makeup products. For example, a user may load an image of their face (e.g., via option 902). The loaded image may be analyzed by platform 120 (e.g., by using the previously described feature detection processes and/or any other computer vision processes) to determine certain characteristics of the face depicted in the loaded image. For example, analysis performed on the image may detect a general shape of the face, shapes and arrangement of certain key features (e.g., eyes, nose, mouth, etc.), hair color and texture, and skin tone. Based on the detected characteristics, platform 120 may generate one or more recommended looks that are specifically tailored to the characteristics of the face in the loaded image. In some embodiments, product recommendations may be based on a user-specific product browsing or selection history. For example, the system may recommend a look that includes a makeup product previously selected by the user. [0096] Product recommendations may be based on objective and or subjective “rules” such as general color combination rules (e.g., primary vs. secondary color combinations), specific application rules (e.g., product combinations for daytime vs. nighttime usage), makeup effects and predetermined goals (e.g., applying bronzer to define or sculpt certain facial features), etc.. In some embodiments, these rules may be generated by one or more expert makeup artists, manufacturers/designers, retailers, etc.. For example, in an embodiment, retailer (such as a department store) may individually define certain makeup recommendation rules to generate looks that are selectable via menu 916i. Alternatively or in addition, individual makeup artists or designers may define their own recommendation rules to automatically generate user selectable looks via menu 916i.
the one or more processors configured to present the re-determined redetermined recommendation makeup information to the user. In some embodiments, look recommendations may be automatically generated using machine-learning based models, for example based on historical aesthetic feedback data. For example, although not shown in screen 900i, in some embodiments, users may be presented with options to rate makeup products and looks, both in general and as applied to their specific facial features.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang to include the limitations above, as taught in Satori, in order to produce a composite image that simulate the application of a corresponding real-world makeup product (paragraph 0025).
Claim 8, 11, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Yang (US 20220211163) in view of Satori (US 20180075523) in further view Peyrelevade (US 20030065578).
Regarding claims 8 and 20, Yang in view of Satori teaches the limitations set for the above.
While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, and Satori teaches the application of recommended product to a user image and receiving feedback, the references do not explicitly disclose:
further comprising the one or more processors configured to receive, from the user, information that the user wants to obtain the recommended makeup product,
wherein the one or more processors configured to receive the evaluation information receives the evaluation information from the user obtaining the makeup product.
However Peyrelevade teaches:
further comprising the one or more processors configured to receive, from the user, information that the user wants to obtain the recommended makeup product, ("Buy" icon in Figure 10)
wherein the one or more processors configured to receive the evaluation information receives the evaluation information from the user obtaining the makeup product. (Step 150 "enable the subject to indicated whether the first product is acceptable" and Step 160 "Select at least one second beauty product complementary with the first beauty product" and see Figure 20 "Buy")
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang in view of Satori to include further comprising the one or more processors configured to receive, from the user, information that the user wants to obtain the recommended makeup product, wherein the one or more processors configured to receive the evaluation information receives the evaluation information from the user obtaining the makeup product, as taught in Peyrelevade, in order to increase sales through cross selling based on improved recommendations (paragraph 008).
Regarding claim 11, Yang in view of Satori teaches the limitations set for the above.
While Yang discloses a makeup apparatus for making recommendations about products using extracted information about the facial features of the user, skin information of the user, and other user data inputs, and Satori teaches the application of recommended product to a user image and receiving feedback, the references do not explicitly disclose:
further comprising a module configured to present a reward to the user inputting the evaluation information.
However Peyrelevade teaches:
further comprising a module configured to present a reward to the user inputting the evaluation information. ([0094] Recommended products 720 may be an individual product and/or a package of products. In one embodiment, the package option may include a special discount. The discount may be applied if the user purchases an individual recommended product and/or package of recommended products with the selected product. The discount may be offered at time of payment. The discount may be used by the AI engine 540 as a sales tool to encourage sales that may not otherwise occur.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the makeup recommendation process of Yang in view of Satori to include further comprising a module configured to present a reward to the user inputting the evaluation information, as taught in Peyrelevade, in order to increase sales through cross selling based on improved recommendations (paragraph 008).
Relevant Art Not Cited
Tamura (US 20150366328) discloses an application for applying makeup based on the similarity of a received user image and a target face image.
Response to Argument
Applicant’s arguments, filed 10/23/2025, with respect to the title object and claim interpretation under 35 USC 112f have been fully considered and are persuasive. The objection and interpretation have been withdrawn.
Applicant's arguments filed 10/23/2025 have been fully considered but they are not persuasive.
With respect to the remarks directed to “the claims are not directed to a mental process” the examiner maintains, as reflected in the updated rejection, that the claims could be performed by the human mind. Make-up artist perform this operation as they evaluate a human face, make judgement about what make up products to apply and the manner in which they should be applied. The now added additional elements are merely tangential to the abstract idea. In the same manner, the recitation of these tangential additional elements do not remove the claims from being “directed to a method of organizing human activity”. The claims as amended still recite making recommendations to a user about a product and the application of that product and the feedback loop of evaluation data could also be performed by hand or the human mind or be mere data collection in a business process. It also involves the evaluation of the product. Implementation using computer elements does not overcome the recitation of an abstract idea.
With respect to the remarks directed to “the claims are directed to a technical solution to a technical problem”, the examiner maintains the claims do not integrate the judicial exception into a practical application. The automated approach recited here is just that, the automation of a business practice. The claims recite an accurate and effective way of allegedly improving the recommendation and personalization of makeup, but this is an improvement that lies in the abstract idea. The technology itself is not improved. For at least these reasons the claims remain rejected under 35 USC 101.
With respect to the rejection under 35 USC 103, the rejection has been updated and now relies on the teachings of Yang in view of Satori to teach the claims as amended. Previously cited Peyrelevade is still relied on for dependent claims 8, 11, and 20, but no longer for the independent claims as discussed in the interview on 10/14/2025.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VICTORIA E. FRUNZI whose telephone number is (571)270-1031. The examiner can normally be reached Monday- Friday 7-4 (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marissa Thein can be reached at (571) 272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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VICTORIA E. FRUNZI
Primary Examiner
Art Unit TC 3689
/VICTORIA E. FRUNZI/Primary Examiner, Art Unit 3689 1/13/2026