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 .
Claims Status
Claims 1-20 are pending and rejected.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 7/25/2025 and 8/11/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
Claim Objections
The claims are objected to because of the following informalities:
In claim 17, “system of claim 16, interactive," should read – system of claim 16, wherein the interactive method --
Appropriate correction is required.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1:
Claims 1-17 are directed to a system, which is a machine. Claims 18-19 are directed to a method, which is a process. Claim 20 is directed to a non-transitory computer-readable media, which is a product. Therefore, claims 1-20 are directed to one of the four statutory categories of invention.
Step 2A (Prong 1):
Representative claim 1 sets forth the following limitations which recite the abstract idea of presenting product information:
train, using historical shopping environment information and historical shopping session information, a generative artificial intelligence (Al) model, wherein training the generative Al model configures the generative Al model to produce design elements based on user input;
receive user input associated with a shopping session;
input the user input into the generative Al model to generate a design element based on at least a portion of the received user input;
generate, using the generative Al model and based on the design element, an interactive shopping environment that includes a visual representation of the design element configured to enable user interaction with the visual representation within the interactive shopping environment;
receive user feedback associated with the visual representation;
update, using the generative Al model and based on the user feedback, the interactive shopping environment to produce a revised interactive shopping environment, wherein the revised interactive shopping environment includes a revised visual representation of the design element; and
convert the revised visual representation of the design element into a user selectable element configured to, based on selection of the user selectable element, trigger addition of an item corresponding to the user selectable element to a shopping cart associated with the user within the interactive shopping environment.
The recited limitations above set forth steps to present product information. These limitations amount to certain methods of organizing human activity, including commercial or legal interactions (e.g. advertising, marketing or sales activities or behaviors).
Such concepts have been identified by the courts as abstract ideas (see: MPEP 2106).
Step 2A (Prong 2):
Examiner notes that representative claim 1 recites additional elements such as a processor, communication interface, memory, etc.
However, even with additional features such as these, the claims fail to integrate the recited judicial exception into a practical application of the exception. The claims merely include instructions to implement an abstract idea on a computer, or to merely use a computer as a tool to perform an abstract idea, while the additional elements do no more than generally link the use of a judicial exception to a particular field of technological environment or field of use.
Furthermore, this is also because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement a judicial exception with a particular machine, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
In view of the above, under Step 2A (Prong 2), claim 1 does not integrate the recited exception into a practical application (see again: MPEP 2106).
Step 2B:
When taken individually or as a whole, the additional elements of claim 1 do not provide an inventive concept (i.e. whether the additional elements amount to significantly more than the exception itself). As discussed above with respect to integration of the abstract idea into a practical application, even including an additional element of a processor or computer to perform the steps would amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Certain additional elements are also recite well-understood, routine, and conventional activity (See MPEP 2106.05(d)).
Even considered as an ordered combination, any additional elements of claim 1 do not add anything further than when they are considered individually.
In view of the above, claim 1 does not provide an inventive concept under step 2B, and is ineligible for patenting.
Dependent claims 2-17 recite further complexity to the judicial exception (abstract idea) of claim 1, such as by further defining the steps for presenting product information. Thus, each of claims 2-17 are held to recite a judicial exception under Step 2A (Prong 1) for at least similar reasons as discussed above.
Therefore, dependent claims 2-17 do not add “significantly more” to the abstract idea. The dependent claims recite additional functions that describe the abstract idea and only generally link the abstract idea to a particularly technological environment, and applied on a generic computer. Further, the additional limitations fail to provide an improvement to the functioning of the computer, another technology, or a technical field.
Even when viewed as an ordered combination, the dependent claims simply convey the abstract idea itself applied on a generic computer and are held to be ineligible under Steps 2A/2B for at least similar rationale as discussed above regarding claim 1.
The analysis above applied to all statutory categories of invention. Regarding independent claim 18 (method) and claim 20 (medium), the claims recite substantially similar limitations as set forth in claim 1. The additional elements of claims 18 and 20 remain only broadly and generically defined, with the claimed functionality paralleling that of claim 1 (system). As such, claims 18 and 20 and dependent claim 19 are rejected for at least similar rationale as discussed above.
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 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 of this title, 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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Sholl et al. (U.S. Pre-Grant Publication No. 2024/0161423) (“Sholl”), in view of Wiesel et al. (U.S. Pre-Grant Publication No. 2019/0244407) (“Wiesel”).
Regarding claims 1, 18 and 20, Sholl teaches a computing system (and related method and medium) for customizing an interactive shopping environment, the computing system comprising:
at least one processor (Fig. 1; para [0093], mobile device);
a communication interface communicatively coupled to the at least one processor (Fig. 1; para [0093], network connection); and
memory storing computer-readable instructions that, when executed by the at least one processor (Fig. 1; para [0093], mobile device executes a user application), cause the computing system to:
train, using historical shopping environment information and historical shopping session information, a generative artificial intelligence (Al) model, wherein training the generative Al model configures the generative Al model to produce design elements based on user input (para [0096], machine learning models 124, which may be trained; para [0101]-[0103], machine learning data pipeline);
receive user input associated with a shopping session (para [0096], Once trained, the machine-learning models 124 are provided with input images received by a computer vision and machine learning pre-processing module 128 from the user application);
input the user input into the generative Al model to generate a design element based on at least a portion of the received user input (para [0097], Based upon the pre-processed input image information generated by the computer vision and machine learning pre-processing module 128, the trained machine learning models 124 generate an image of a user wearing, in a user-selected style, a user-specified digital garment, e.g., a digital representation of a real-world garment, in a pose identified from the input image provided to the user application);
generate, using the generative Al model and based on the design element, an interactive shopping environment that includes a visual representation of the design element configured to enable user interaction with the visual representation within the interactive shopping environment (para [0097], Based upon the pre-processed input image information generated by the computer vision and machine learning pre-processing module 128, the trained machine learning models 124 generate an image of a user wearing, in a user-selected style, a user-specified digital garment, e.g., a digital representation of a real-world garment, in a pose identified from the input image provided to the user application);
update, using the generative Al model and based on the user feedback, the interactive shopping environment to produce a revised interactive shopping environment, wherein the revised interactive shopping environment includes a revised visual representation of the design element (para [0225], system can automatically update a rendering of the user with the additional articles of clothing and in the inferred style.); and
convert the revised visual representation of the design element into a user selectable element configured to, based on selection of the user selectable element, trigger addition of an item corresponding to the user selectable element to a shopping cart associated with the user within the interactive shopping environment (Fig. 55; para [0087], To enhance the shopping experience, the virtual try-on system may seamlessly integrate with e-commerce platforms. Users may be able to directly purchase the clothing items they try on or add them to a Wishlist for future reference. The system provides links to online retailers, allowing users to access additional product information and make informed purchase decisions.; para [0192], [0195]).
Although Sholl teaches updating the interactive shopping environment, Sholl does not explicitly teach steps to receive user feedback associated with the visual representation and update based on the user feedback.
In a similar field of endeavor, Wiesel teaches steps to:
receive user feedback associated with the visual representation (para [0486],system may enable the user to provide feedback, such as, indicating that a first virtual-dressing of a first product on himself appears very realistic, and that a second virtual-dressing of a second product on himself appears non-realistic to him; thereby enabling the system to be self-learning, self-improving, and self-correcting over time.);
update based on the user feedback (para [0486],system may enable the user to provide feedback, such as, indicating that a first virtual-dressing of a first product on himself appears very realistic, and that a second virtual-dressing of a second product on himself appears non-realistic to him; thereby enabling the system to be self-learning, self-improving, and self-correcting over time.);
Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the noted limitations as taught by Wiesel in the system of Sholl, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Namely, an improvement in an online system to generate a realistic image that emulates or simulates how that particular user would appear if he or she wears a particular article of clothing (See Wiesel: para [0004]).
Regarding claim 2, Sholl and Wiesel teach the above system of claim 1. Sholl also teaches wherein the generative Al model is configured to generate the design element at least by:
setting one or more constraints of a gradient-guided genetic algorithm based on at least a portion of the received user input (para [0079], example systems and methods may combine state-of-the-art computer vision algorithms, machine learning algorithms, augmented reality techniques, and a vast clothing style database to create a realistic and interactive virtual try-on experience.; para [0083], users may be able to personalize their virtual outfits by selecting different clothing combinations, adjusting garment parameters (e.g., sleeve length, neckline, top button unbuttoned, multiple unbuttoned buttons, or other styling), and experimenting with color variations);
generating a plurality of populations of design elements using the constrained gradient-guided genetic algorithm (para [0086], user interface may provide controls for selecting clothing items, adjusting garment parameters, and exploring styling options. Users can browse through the clothing database, filter items by category, style, color, or brand, and view detailed product descriptions and user reviews.); and
selecting, as the design element, one of the generated design elements of the plurality of populations of design elements (para [0086], user interface may provide controls for selecting clothing items, adjusting garment parameters, and exploring styling options. Users can browse through the clothing database, filter items by category, style, color, or brand, and view detailed product descriptions and user reviews.).
Regarding claim 3, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein receiving the user input comprises receiving contextual information associated with the interactive shopping environment, and wherein the contextual information comprises one or more of occasion information, weather information, fashion trends, venue information, location information, room-type information, extent information, usage information, methodology information, budget information, theme information, meal information, occupation information, formality information, date information, time information, style information, color information, brand information, size information, pattern information, fabric information, material information, jewelry material information, jewelry stones, neckline information, detailed feature information, finish information, dress code information, attendee information, music information, services information, destination information, mode of travel information, lodging information, or transportation information (para [0485], user-specific manner, taking into account user preferences, user settings, user profile, user questionnaire, user body type or ratio or dimensions, current trends or shopping trends or fashion trends (e.g., ranking higher the products that match a current shopping trend), current weather or season (e g, ranking higher Summer Dresses, if the user searches for “dress” in the United States in July), geographic location, or the like.; para [0128] other product information (e.g., price, vendor, maker, model name, model number, or the like). Textual analysis and/or contextual analysis may be used, to extract available product sizes, product dimensions, available destinations for shipping, or the like. Pairs of Key/Value items may be extracted and analyzed (e.g., “Size”/“Medium”)).
Regarding claim 4, Sholl and Wiesel teach the above system of claim 3. Wiesel also teaches wherein receiving the user input comprises receiving image data associated with an environmental aspect (para [0461], optionally detects or extracts or maintains the background of the user's image in order to maintain the unique background for AR purposes...thus the nearby motorcycle and the street environment is extracted and is maintained for AR rendering of virtually-dressed items).
Regarding claim 5, Sholl and Wiesel teach the above system of claim 4. Wiesel also teaches wherein the received image data is reproducible as one or more of a visually displayable image or a video, wherein the visually displayable image or video depicts one or more of a portion of a room, a portion of a building, a portion of a house, the user, a portion of the user, a portion of a wedding venue, a portion of a landscape, or a portion of a vehicle (para [0461], optionally detects or extracts or maintains the background of the user's image in order to maintain the unique background for AR purposes...thus the nearby motorcycle and the street environment is extracted and is maintained for AR rendering of virtually-dressed items).
Regarding claim 6, Sholl and Wiesel teach the above system of claim 4. Wiesel also teaches wherein receiving the user input comprises receiving personal information associated with the user comprising one or more of user preference information, user profile information, user history information, user location, or user hobbies (para [0086], user may take several pictures or videos. In some embodiments, additional parameters and preferences, from the user and or external resources; para [0461], user uploads her photograph, which is analyzed by an analysis engine that detects body parts (e.g., head, arms, hands, legs, knees, neck), and/or detects other body features (e.g., hair color, hair style, tattoo, birthmark, skin color) or accessories that the user already wears; para [0465], user-specific purchase history or browsing history, user-specific data obtained from social media account or from user-defined settings or preferences).
Regarding claim 7, Sholl and Wiesel teach the above system of claim 6. Wiesel also teaches wherein generating the design element comprises: structuring a prompt for the generative Al model based on one or more of at least a portion of the contextual information, at least a portion of the image data, or at least a portion of the personal information; and providing the prompt to the generative Al model (Fig. 20; para [0467], photograph that Carla uploaded includes Carla standing next to her motorcycle; and accordingly, the system identifies that in addition to Carla, the uploaded image contains particular background features that should be maintained, thereby generating the five search results of the five summer dresses to be virtually dressed on the image of Carla standing next to her same motorcycle, or with the same image background of the original uploaded photo; thereby producing a realistic, real-life image of the product, virtually dressed by the actual user, and virtually located in the particular environment or spatial location that appeared in the originally-uploaded image of the actual user).
Regarding claim 8, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein the user feedback comprises a request to perform one or more of changing a color of the visual representation, changing a texture of the visual representation, changing a size of the visual representation, changing a pattern of the visual representation, changing a material of the visual representation, changing a brand associated with the visual representation, changing a location of the visual representation within the interactive shopping environment, or changing a style of the visual representation (para [0476], system may further modify, replace, or otherwise augment or change the background of each such image, in order to further personalize the catalog to each user, based on user-specific data (e.g., browsing history, shopping history) and/or based on contextual analysis).
Regarding claim 9, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein the interactive shopping environment is associated with one of a personal stylist, a wedding planner, an interior decorator, a travel agent, or a personal shopper (para [0455], system may be used with a variety of other contexts and items…furniture…art).
Regarding claim 10, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein generating the visual representation of the design element comprises generating one of a two-dimensional (2D) visual representation of the design element or a three- dimensional (3D) visual representation of the design element (para [0049], module only needs a single user image that may be invariant, but is not limited to quality and camera angles in order to create a 3D estimation of the user).
Regarding claim 11, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein generating the interactive shopping environment comprises generating one of a virtual reality environment or an augmented reality environment (para [0049], dressing process using image processing, computer vision and machine learning; para [0057], process uses artificial intelligence techniques in order to distinguish between the user's body and clothes from the background; para [0506], a Virtual Reality (VR) device or helmet or glasses or headgear, an Augmented Reality (AR) device or helmet or glasses or headgear).
Regarding claim 12, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein:
receiving the user feedback comprises receiving one or more of a user rating, a user comment, or user interaction with the visual representation (para [0484], system may utilize a tagging module able to generate tags based on contextual analysis, morphologic analysis, NLP analysis of textual description and/or user reviews and/or user comments and/or product description); and
updating the interactive shopping environment comprises modifying one or more of a color of the design element, a texture of the design element, a size of the design element, a shape of the design element, or a material of the design element (para [0486], system may enable the user to provide feedback, such as, indicating that a first virtual-dressing of a first product on himself appears very realistic, and that a second virtual-dressing of a second product on himself appears non-realistic to him; thereby enabling the system to be self-learning, self-improving, and self-correcting over time).
Regarding claim 13, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein converting the revised visual representation of the design element into the user selectable element comprises generating one of a hyperlink or a button associated with the item (para [0468], each one of the search results, is also a click-able link that redirects the user to a particular product page or particular vendor web-site).
Regarding claim 14, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein generating the design element comprises generating a first design element and a second design element, and wherein the interactive shopping environment includes a first visual representation of the first design element and a second visual representation of the second design element (para [0045], enable a user, to obtain an emulated or simulated image which shows the user to appear to be wearing, concurrently, two different products that optionally originate from (or are sold by) two different vendors or sources).
Regarding claim 15, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein updating the interactive shopping environment further comprises segmenting the first design element from the second design element (para [0045], Each one of the products may be separately resized and enhanced, and the two (or more) items may then be overlayed or superimposed or pasted or otherwise inserted onto or into the image of the user).
Regarding claim 16, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches wherein updating the interactive shopping environment further includes performing a first reverse image search of the first design element and performing a second reverse image search of the second design element in a database (para [0458], system may automatically perform calibration, normalization and/or resizing of image-based search results, in order to enable the user to better grasp how various items that are all search results of a single search query, would appear in a particular AR context).
Regarding claim 17, Sholl and Wiesel teach the above system of claim 1. Wiesel also teaches interactive shopping environment includes an avatar associated with the user, and wherein the avatar appears dressed in the visual representation of the design element or in the revised visual representation of the design element (Fig. 29; para [0481], generate virtual dressing images, as well as a three-dimensional mannequin or avatar, that resembles the user's body structure).
Regarding claim 19, Sholl and Wiesel teach the above method of claim 18. Wiesel also teaches wherein converting the revised visual representation of the design element into the user selectable element is based on receipt of a user approval input, indicating approval of the revised interactive shopping environment (Fig. 55; para [0087], To enhance the shopping experience, the virtual try-on system may seamlessly integrate with e-commerce platforms. Users may be able to directly purchase the clothing items they try on or add them to a Wishlist for future reference. The system provides links to online retailers, allowing users to access additional product information and make informed purchase decisions.; para [0192], [0195]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANAND LOHARIKAR whose telephone number is 571-272-8756. The examiner can normally be reached Monday through Friday, 9am – 5pm.
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/ANAND LOHARIKAR/Primary Examiner, Art Unit 3689
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