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 .
Status of Claims
This action is in reply to the claims filed on 04/06/2026.
Claims 1-3, 8, 13-17 and 20-22 are currently amended.
Claims 1-22 are currently pending and have been examined.
Subject Matter Free of Prior Art
Claims 3, 8-9, and 16 are determined to have overcome the prior art of rejection and are free of prior art, however the claims remain rejected under 35 USC 101, as set forth below.
Claim 3 recites wherein the store location data includes a two dimensional (2D) floor plan of the store, wherein the shelf data indicates a type and dimensions of the shelf.
The closest prior art was found to be as follows:
Stansell et al. (US 2018/0150791 A1) discloses a two dimensional (2D) floor plan of the store in ¶ [0037] “planogram data” and measuring a distance between shelves in ¶ [0060]. However, Stansell does not teach or disclose wherein the shelf data indicates a type and dimensions of the shelf.
Claim 8, and claim 9 which depends from claim 8, recites wherein rendering the scene is further based on the location-based statistical data, and wherein the scene upon rendering further shows a visual representation of the first location-based statistical data within the scene represented using at least one of (i) color coding indicating a value that is greater than a predetermined value or (ii) a numerical value.
Claim 16 recites rendering the scene is further based on location-based statistical data, and wherein the scene upon rendering further visually indicates at least two products with a joint purchase rate above a threshold.
The closest prior art was found to be as follows:
Gruttadauria (US 2008/0147475 A1) discloses location-based statistical data associated with the shelf or product data that is included in the virtual model in ¶ [0032]. However, Gruttadauria does not teach or disclose wherein the scene upon rendering further shows a visual representation of the first location-based statistical data within the scene represented using at least one of (i) color coding indicating a value that is greater than a predetermined value or (ii) a numerical value, or wherein the scene upon rendering further visually indicates at least two products with a joint purchase rate above a threshold.
Moreover, even assuming arguendo that the features of the claims exist individually, the combination of features as claimed would not have been obvious to one of ordinary skill in the art because any combination of the evidence obtained to reach the combination of features as claimed would require substantial reconstruction of Applicant' s claimed invention relying on improper hindsight bias.
Therefore, it is hereby asserted by the Examiner that the claims are free of prior art as the references do not anticipate the claims and do not render obvious any further modification of the references to a person of ordinary skill in art.
Claim Rejections- 35 U.S.C. § 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 1-22 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Under Step 1 of the subject matter eligibility (SME) analysis described in MPEP 2106.03, the instant claims fall within the four statutory categories of invention identified by 35 U.S.C. 101. In the instant case, claims 1-20 are directed to a method, claim 21 is directed to a manufacture, and claim 22 is directed to a system. Claims 1, 21, and 22 are parallel in nature, therefore, the analysis will use claim 1 as the representative claim.
In Step 2A Prong One, it must be considered whether the claims recite a judicial exception. In the instant case, representative claim 1 recites abstract concepts including: determining, ... a physical location … in a store; determining, ... using the physical location ... a … location that corresponds to the physical location, wherein the … location is in a … model that represents a spatial layout of the store; determining ... from the … model, a subset of model data based on the … location, wherein: the model data comprises (i) store location data applicable to the entire store, (ii) shelf data applicable to shelves in the store, and (iii) planogram data applicable to the shelves and products associated with the shelves, wherein the store location data includes a two dimensional (2D) floor plan of the store, wherein the shelf data indicates a type and dimensions of the shelf, or wherein the planogram data indicates dimensions of a product and a location of the product within the shelf, and the subset of the model data comprising (iv) the store location data, (v) a subset of the shelf data applicable to at least a shelf within a predefined distance of the physical location of the device, and (vi) a subset of the planogram data applicable to at least the shelf and a product associated with the shelf; rendering ... a scene based on the subset of the model data, the scene upon rendering showing a visual representation of the product overlaid on an image of the shelf within the scene.
When considering the subject matter groupings articulated in MPEP 2106.04, the claims recite an abstract idea of “presenting a scene based on store model or layout information”. These concepts are considered to be certain methods of organizing human activity. Certain methods of organizing human activity are defined by MPEP 2106.04 as including “fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)”. Presenting a scene based on a store layout or planogram, which is used to visualize how products should be arranged/stocked in a store, is a certain method of organizing human activity these are examples of managing personal behavior (i.e. informing a user where a product should be placed). Therefore, claims 1, 21, and 22 recite an abstract idea.
If it is determined that the claims recite a judicial exception, then in Step 2A, Prong 2 of the SME analysis, it is then necessary to evaluate whether the claims recite additional elements that integrate the judicial exception into a practical application of that exception. This is the question of whether a claim is “directed to” a judicial exception. As explained in MPEP 2106.05, the evaluation of Prong Two requires the use of the considerations (e.g. improving technology, effecting a particular treatment or prophylaxis, implementing with a particular machine, etc.) identified by the Supreme Court and the Federal Circuit, to ensure that the claim as a whole “integrates [the] judicial exception into a practical application [that] will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.”
In this instant case, claims 1, 21, and 22 recite the additional elements including: a device; a modeling system; a virtual location; a virtual model that is stored in a database; a non-transitory computer-readable storage medium comprising computer-readable instructions; a processor. The device, model, storage medium, database, and processor are each recited at a high level of generality. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. MPEP 2106.05(h). The recited additional elements do not integrate the abstract idea into a practical application because they amount to no more than a general link of the use of the abstract idea to a particular technological environment or field of use (e.g. a virtual/computer-implemented environment). Employing generic computer functions to execute the abstract idea, does not provide meaningful limits on the claim. Accordingly, the Examiner concludes that the claims fail to integrate the abstract idea of “presenting a scene based on store model or layout information” into a practical application. Claims 1, 21, and 22 are thus directed to an abstract idea.
Under Step 2B of the SME analysis, if it is determined that the claims recite a judicial exception that is not integrated into a practical application of that exception, it is then necessary to evaluate the additional elements individually and in combination to determine whether they 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, the additional element(s) individually and in combination are merely being used to apply the abstract idea to a general computer components. The invention as claimed merely automates “presenting a scene based on store model or layout information” (i.e., the abstract idea) and does not add meaningful limitations to the abstract ideas beyond generally linking the abstract process to implementation via computers/software. Therefore, the additional elements, alone or in ordered combination, do not render the claim as being significantly more than the underlying abstract idea, and the claims 1, 21, and 22 are ineligible.
Dependent claim(s) 2-11 and 18-19 do not aid in the eligibility of the independent claims. These claims merely further define the abstract idea without reciting any further additional elements. Thus dependent claims 2-11 and 18-19 are also ineligible.
Dependent claim 12-13 and 20 recites additional elements including: sending a query to a datastore; and receiving the subset of model data from the datastore based on the query; sending, to the datastore, a request to change product data in the subset of the planogram data … wherein the request causes an update to the planogram data. Similar to the additional elements identified above, the datastore, sending of the query/request, and updating are described in ordinary terms and merely used as tools in performance of the abstract idea. These limitations amount to insignificant extra-solution activity in the form of mere data gathering, which does not amount to an inventive concept (MPEP 2106.05(g). Furthermore, storing/retrieving information in memory has been repeatedly considered a well-understood, routine, and conventional computer activity by the Courts (see MPEP 2106.05(d)II.iv.). Accordingly, claim(s) 12-13 and 20 considered both individually and as a combination, is/are ineligible.
Dependent claim 14-17 recite additional elements including: an AR scene; an augmented reality (AR) device; a set of sensors of the AR device. Similar to the additional elements identified above, AR device and sensors are described in ordinary terms and merely used as tools in performance of the abstract idea. These additional elements do not integrate the abstract idea into a practical application because they merely amount to no more than a general link of the use of the abstract idea to a particular technological environment or field of use. Accordingly, the additional elements do not act to integrate the abstract idea into a practical application, neither do they amount to significantly more than the abstract idea itself. Thus claims 14-17 are also ineligible.
Claim Rejections - 35 U.S.C. § 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.
Claim(s) 1, 3-5, 11, 12, and 15-22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Stansell et al. (US 2018/0150791 A1).
Claim 1, Stansell discloses a method implemented by a device (¶ [0033] “AR device”), the method comprising:
determining, using the device, a physical location of the device in a store (¶ [0054] “In the case of (2), locating the modular (404) can include the user providing input to AR device 120 in order to request and receive the relevant data. This input can comprise verbal input (e.g., saying a department, zone, aisle or section, or other identifying information)… or geolocation input (e.g., identifying a current location of AR device 120 by geolocation system 310, and identifying the desired modular from possible modulars at that location or by determining a direction of vision of the user of AR device 120)”);
determining, by the device and using a modeling system (¶ [0033] “augmented reality assisted (AR-assisted) product modular arrangement system”, “the AR-assisted system comprises and AR device, such as a headset, glasses, or mobile device, that uses one or more of computer vision ... to guide a use through locating ... a retail display”) and the physical location (¶ [0066] “a geolocation of AR device 120”), a virtual location that corresponds to the physical location, wherein the virtual location is in a virtual model that is stored in a database and represents a spatial layout of the store (¶ [0054] “AR device 120 can visually scan a modular for markers or other identifiers to identify the desired modular.”; ¶ [0066] “AR device 120 can request or system 100/product database 110 can push only data and information, including images, for products in that department (or associated with a particular modular or zone, etc.)” in view of ¶ [0037] discussion of database 110 comprising AR-optimized modular and product data such as “backend planogram data” and ¶ [0039] “Modular location data”; FIG. 2A-2B);
determining, by the device, from the virtual model, a subset of model data based on the virtual location (¶ [0066]) “AR device 120 can request or system 100/product database 110 can push only data and information, including images, for products in that department (or associated with a particular modular or zone, etc.)”, wherein:
the model data comprises (i) store location data applicable to the entire store, (ii) shelf data applicable to shelves in the store, and (iii) planogram data applicable to the shelves and products associated with the shelves (¶ [0037] “Product databases 110 comprise AR-optimized modular and product data. Conventionally, hardcopy planograms, such as the example planogram 200 depicted in FIG. 2A, are used to manually arrange modulars, modular components (e.g., shelves, hooks, rails, etc.), and products. In embodiments, system 100 uses similar backend planogram data”; ¶ [0039] “Modular location data and fields include information to locate or identify the intended modular on which the product is to be placed and the types of products to be placed thereon. In FIG. 2B, this can include a store zone at 202, a store aisle at 204, and an aisle section at 205; a product department at 206, a product category at 208, and a product category description at 210”), wherein the store location data includes a two dimensional (2D) floor plan of the store, wherein the shelf data indicates a type and dimensions of the shelf, or wherein the planogram data indicates dimensions of a product and a location of the product within the shelf (¶ [0042] “Product arrangement data and fields include information about how the product is to be placed on the modular. In FIG. 2B, this can include ... a product height at 236, a product width at 238, and a product depth at 240, and a coordinate”; ¶ [0044] “The data fields of data set 201 in FIG. 2B are but one example, and in other embodiments more, fewer and/or different fields can be included in data set 201. Data set 201 is associated with a single product to be placed in a specific location on an assigned modular arranged in an assigned area of a retail store”), and
the subset of the model data comprising (iv) the store location data (FIG. 2B “Location ID”), (v) a subset of the shelf data applicable to at least a shelf within a predefined distance of the physical location of the device (¶ [0054] “identifying the desired modular from possible modulars at that location”; ¶ [0066] “For example, if AR device 120 had identified that a user is working in a particular department, such as from product data 201, geolocation of AR device 120 and/or modular 504, or in some other way, AR device 120 can request or system 100/product database 110 can push only data and information, including images, for products in that department (or associated with a particular modular or zone, etc.).”), and (vi) a subset of the planogram data applicable to at least the shelf and a product associated with the shelf (¶ [0044] “Data set 201 is associated with a single product to be placed in a specific location on an assigned modular arranged in an assigned area of a retail store”); and
rendering, by the device, a scene based on the subset of the model data, the scene upon rendering showing a visual representation of the product overlaid on an image of the shelf within the scene (¶ [0047] “AR device 120 is configured to project images and other information onto a user's field of view via AR device 120, thereby providing an “augmented” view of a real setting, or reality. In operation, AR device 120 uses one or more computer vision, object recognition and/or image processing techniques to recognize real-world objects in a view and augment the view with computer-generated objects in ways that provide meaningful and helpful information to the user.”; ¶ [0063] “overlays an image of a product and related information on the proper location on modular 504 via display 302”)
Claim 4, Stansell discloses the method of claim 1. Stansell further discloses, wherein the virtual model is generated by at least:
receiving product data associated with the product, the product data indicating a location of the product on the shelf and comprising one or more of a shape of the product, a visual representation of product packaging of the product, or an image associated with the shape of the product (¶ [0038] “ Referring to FIG. 2B, an example data set 201 for one product is shown.”); and
associating, in the model data, the shelf data with the product data (¶ [0039] “Modular location data and fields include information to locate or identify the intended modular on which the product is to be placed and the types of products to be placed thereon. In FIG. 2B, this can include a store zone at 202, a store aisle at 204, and an aisle section at 205; a product department at 206, a product category at 208, and a product category description at 210.”; FIG. 2A; FIG. 2B).
Claim 5, Stansell discloses the method of claim 4. Stansell further discloses, wherein the shape of the product includes at least one of a height, width, or length of the product (¶ [0042] “Product arrangement data and fields include information about how the product is to be placed on the modular. In FIG. 2B, this can include a number of horizontal facings (how many of the product should be arranged horizontally in the assigned modular section) at 228… a product height at 236, a product width at 238, and a product depth at 240”).
Claim 11, Stansell discloses the method of claim 1. Stansell further discloses, wherein the planogram data is generated by at least:
assigning, to the shelf, product data associated with the product, wherein the product data includes a product identifier, product dimensions, and a product location within the shelf (FIG. 2A; ¶ [0040] “Product location data and fields include information to properly place the product on the modular. In FIG. 2B, this can include Modular Section at 214 and Location Identification at 216.”; ¶ [0041] “Product identification data and fields include information about the particular product to be placed. In FIG. 2B, this can include the product Universal Product Code (UPC) at 218, an item number (which can be specific to the product, manufacturer and/or retailer) at 220, item description (such as a name of the product) at 224, and an item price at 226.”; ¶ [0042] “Product arrangement data and fields include information about how the product is to be placed on the modular. In FIG. 2B, this can include …, a product height at 236, a product width at 238, and a product depth at 240, and a coordinate”).
Claim 12, Stansell discloses the method of claim 1. Stansell further discloses, wherein determining the subset of the model data comprises:
sending a query to a datastore storing the virtual model, the query indicating the store and the virtual location of the device (¶ [0052] “the received data 201 can be limited based on store”; ¶ [0054] “ In the case of (2), locating the modular (404) can include the user providing input to AR device 120 in order to request and receive the relevant data. This input can comprise … visual input (e.g., standing in front of a desired modular and “scanning” markers or other identifying information on the modular by AR device 120, using artificial intelligence to “read” information on product packaging or identify a type of product being viewed), or geolocation input (e.g., identifying a current location of AR device 120 by geolocation system 310, and identifying the desired modular from possible modulars at that location or by determining a direction of vision of the user of AR device 120).”); and
receiving the subset of the model data from the datastore based on the query (¶ [0052] “In operation, and referring to FIG. 4, AR device 120 communicates with product database 110 via communications system 130 to receive data set 201 for a particular modular or other area to be stocked, at 402”; ¶ [0054] “identifying the desired modular from possible modulars at that location or by determining a direction of vision of the user of AR device 120”).
Claim 15, Stansell discloses the method of claim 1. Stansell further discloses, wherein the device is an augmented reality (AR) device (¶ [0047] “AR device 120”), and wherein rendering the scene comprises generating a presentation of an AR scene by at least:
determining a field of view of the AR device within the AR scene (¶ [0054] “ In the case of (2), locating the modular (404) can include the user providing input to AR device 120 in order to request and receive the relevant data. This input can comprise … visual input (e.g., standing in front of a desired modular and “scanning” markers or other identifying information on the modular by AR device 120, using artificial intelligence to “read” information on product packaging or identify a type of product being viewed), or geolocation input (e.g., identifying a current location of AR device 120 by geolocation system 310, and identifying the desired modular from possible modulars at that location or by determining a direction of vision of the user of AR device 120)”); and
determining a portion of the subset of model data corresponding to the field of view, wherein the visual representation includes one or more products within the portion of the subset of planogram data overlaid on the image of the shelf within the AR scene (¶ [0063] “ AR device 120 guides the user through product placement similar to label placement, and an example is depicted in FIGS. 8A and 8B. In FIG. 8A, AR device confirms to the user that it is advancing to the next process (“Process 3”), then overlays an image of a product and related information on the proper location on modular 504 via display 302.”).
Claim 18, Stansell discloses the method of claim 1. Stansell further discloses, wherein the physical location of the device is determined by:
generating, by the device, an image showing a marker installed in the store (¶ [0054] ““scanning” markers or other identifying information on the modular by AR device 120”);
determining an identifier of the marker based on processing of the image (see above citation to ¶ [0054]; ¶ [0055] “Markers can be used to provide identifying information that can be machine-read by AR device 120. The identifying information can comprise alpha-numerics, machine-readable codes (e.g., QR code, RFID, bar code), or some other identifiers”);
determining, from the virtual model a physical location of the marker based on the identifier (¶ [0052] “In operation, and referring to FIG. 4, AR device 120 communicates with product database 110 via communications system 130 to receive data set 201 for a particular modular or other area to be stocked, at 402. In one embodiment, this can be carried out in one of at least two ways:…(2) a user identifies a particular modular to be stocked, such as by walking up to it and seeing it needs stocking, and interacts with AR device 120 to obtain the relevant data set 201, in which case activities 402 and 404 in FIG. 4 are reversed”); and
determining the physical location of the device based on the physical location of the marker and the processing of the image (¶ [0052]; ¶ [0054]).
Claim 19, Stansell discloses the method of claim 1. Stansell further discloses, wherein the virtual location of the device is determined from the virtual model based on a lookup that uses the physical location of the device (¶ [0054] “geolocation input (e.g., identifying a current location of AR device 120 by geolocation system 310, and identifying the desired modular from possible modulars at that location or by determining a direction of vision of the user of AR device 120)”).
Claim 20, Stansell discloses the method of claim 1. Stansell further discloses, further comprising:
determining, by the device, a subsequent physical location of the device in the store, wherein the subsequent physical location is different from the physical location (¶ [0054] “geolocation input (e.g., identifying a current location of AR device 120 by geolocation system 310, and identifying the desired modular from possible modulars at that location or by determining a direction of vision of the user of AR device 120)”; Examiner notes the geolocation input identifies a current location of the device. Therefore as the user navigates the store, there subsequent locations are also determined.);
determining a subsequently virtual location of the device that corresponds to the subsequent physical location (¶ [0054] “and identifying the desired modular from possible modulars at that location or by determining a direction of vision of the user of AR device 120”);
sending a query to a data store that stores the virtual model, the query indicating the subsequent virtual location or the subsequent physical location (¶ [0052] “In operation, and referring to FIG. 4, AR device 120 communicates with product database 110 via communications system 130 to receive data set 201 for a particular modular or other area to be stocked, at 402. In one embodiment, this can be carried out in one of at least two ways: … (2) a user identifies a particular modular to be stocked, such as by walking up to it and seeing it needs stocking, and interacts with AR device 120 to obtain the relevant data set 201, in which case activities 402 and 404 in FIG. 4 are reversed.”); and
receiving, from the data store in response to the query a different subset of the model data (¶ [0052] “receive data set 201 for a particular modular”); and
updating the rendering of the scene based on the different subset of the model data (¶ [0063] “AR device 120 guides the user through product placement similar to label placement, and an example is depicted in FIGS. 8A and 8B. In FIG. 8A, AR device confirms to the user that it is advancing to the next process (“Process 3”), then overlays an image of a product and related information on the proper location on modular 504 via display 302”; also see ¶ [0052] “In operation, and referring to FIG. 4, AR device 120 communicates with product database 110 via communications system 130 to receive data set 201 for a particular modular or other area to be stocked, at 402.”).
Claim 21, which is directed to a non-transitory computer-readable medium, recites limitations that are parallel in nature as those addressed above for method claim 1. Claim 21 is therefore rejected for the same reasons as set forth above for claim 1.
Claim 22 which is directed to a system, recites limitations that are parallel in nature as those addressed above for method claim 1. Claim 22 is therefore rejected for the same reasons as set forth above for claim 1.
Claim Rejections - 35 U.S.C. § 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.
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 factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 2 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Stansell in view of Cheshire et al. (US 2023/0385916 A1).
Claim 2, Stansell discloses the method of claim 1. Stansell further discloses, wherein the virtual model is generated by at least:
receiving the store location data that includes the 2D floor plan of the store, the 2D floor plan indicating at least the shelf, a location of the shelf in the store, and horizontal dimensions of the shelf (¶ [0037] “Conventionally, hardcopy planograms, such as the example planogram 200 depicted in FIG. 2A, are used to manually arrange modulars, modular components (e.g., shelves, hooks, rails, etc.), and products. In embodiments, system 100 uses similar backend planogram data, updated with additional fields and data”);
receiving, for the shelf identified in the 2D floor plan, at least a vertical dimension associated with the shelf ( FIG. 2A; ¶ [0073] “Instead of merely optimizing a theoretical design, system 100 is tied to real-world physical locations, dimensions and objects, requiring sophisticated location determination and awareness in real-time”).
Stansell does not explicitly disclose limitations associated with a three dimensional (3D) model for the shelf. However, Cheshire et al. – which like Stansell is directed to generating virtual store environments – teaches:
generating a three dimensional (3D) model for the shelf based on the horizontal dimensions and at least the vertical dimension (Cheshire ¶ [0076] “The 3D shelving units 402, 404, and 406, their respective dimensions, structural elements, and other features, such as how many shelves per shelving unit, may be loaded from memory 106 and/or database 105”); and
generating the model data, the model data comprising the 3D model of the shelf and associating the 3D model with the location of the shelf in the store (¶ [0076] “ Virtual 3D area 400A is depicted as a shelving area, which may be generated as described herein by the algorithm of method 200. As shown for FIG. 4A, virtual 3D area 400A comprises 3D shelving units 402, 404, and 406 that are shown positioned next to each within virtual 3D area 400A. The 3D shelving units 402, 404, and 406, their respective dimensions, structural elements, and other features, such as how many shelves per shelving unit, may be loaded from memory 106 and/or database 105”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the 3D model as taught by Cheshire in the method of Stansell because three-dimensional (3D) models of physical products or packages corresponding to real-world products or packages are useful in virtual reality shopping environments, e-commerce environments and gaming environments (Cheshire ¶ [0002]).
Claim 6, Stansell discloses the method of claim 4. Stansell further discloses, wherein the planogram data comprises at least a subset of a model of the product (see “Size”, “Product” and “Type” in FIG. 2A) and … the shelf (FIG. 2A).
Stansell in view of Mani does not explicitly disclose limitations associated with a 3D model of the shelf. However, Cheshire further teaches a subset of a 3D model of the shelf (Cheshire ¶ [0063] “ At block 202, method 200 comprises loading, from the memory, a matrix file (e.g., a planogram matrix file (e.g., for example, a PSA file) comprising metadata of a virtual product area. In various aspects, the virtual product area may comprise a 3D shelf or aisle of a retail area”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the 3D model as taught by Cheshire in the method of Stansell and Mani because three-dimensional (3D) models of physical products or packages corresponding to real-world products or packages are useful in virtual reality shopping environments, e-commerce environments and gaming environments (Cheshire ¶ [0002]).
Claims 7 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Stansell in view of Gruttadauria (US 2008/0147475 A1).
Claim 7, Stansell teaches the method of claim 1. Stansell does not disclose limitations associated with location-based statistical data. However, Gruttadaria – which like Stansell is directed to providing visualizations of shelf space – teaches, further comprising:
associating location-based statistical data with the shelf data or product data that is included in the virtual model, wherein the location-based statistical data comprises first location-based statistical data that is based on values measured for the shelf or the product over a past period of time (Gruttadaria: ¶ [0032] “Product sales data 233 may indicate how frequently units of a particular product are sold. That is product sales data 233 provides a sales rate for products included in a state-of-the shelf simulation. In one embodiment, the product sales data may be tied to the actual sales made by a particular retail location over a specified period of time (e.g., some period of minutes, hours, days, weeks, etc.) for a given product, group of products, or product category”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the location-based statistical data as taught by Gruttadauria in the method of Stansell because there is a need for techniques to provide a state-of-the-shelf analysis that conveys the state of the shelf as it changes over time (Gruttadauria ¶ [0009]).
Claim 10, the combination of Stansell in view of Gruttadauria teaches the method of claim 7. Stansell does not disclose limitations associated with location-based statistical data, however Gruttadauria further teaches: wherein the first location-based statistical data comprises foot traffic data associated with the location of the shelf, view data associated with the location of the product on the shelf, or acquisition data of units of the product from the shelf (Gruttadauria ¶ [0032] “In one embodiment, the product sales data may be tied to the actual sales made by a particular retail location over a specified period of time (e.g., some period of minutes, hours, days, weeks, etc.) for a given product, group of products, or product category”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the location-based statistical data as taught by Gruttadauria in the method of Stansell because there is a need for techniques to provide a state-of-the-shelf analysis that conveys the state of the shelf as it changes over time (Gruttadauria ¶ [0009]).
Claims 13 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Stansell in view of Soon-Shiong (US 2014/0129393 A1).
Claim 13, Stansell discloses the method of claim 12. Stansell does not disclose limitations associated with updating the planogram data, however Soon-Shiong – which like Stansell is directed to virtual planogram management – teaches, further comprising:
sending, to the datastore, a request for a change to product data in the subset of the planogram data, wherein the change is associated with at least one of a product spatial location, a product type, or a product dimension, wherein the request causes an update to the planogram data, wherein the update comprises the change to the product data (Soon-Shiong ¶ [0074] “Thus, a virtual marketplace can be configured to display the items that are present in a physical marketplace, and update according to the changes made in the physical marketplace. … A dynamic planogram can be used to generate a corresponding virtual freezer on display 600 available inside a grocery store, or remote to, the grocery store. ... If a frozen pizza is removed from the physical freezer (e.g., for purchase by a shopper, relocation, etc.), the frozen pizza can be removed from the virtual freezer in real-time or substantially real-time”; ¶ [0075] “Planogram manager 710 interacts with planogram sever 720 to create, update, instantiate, or otherwise manage virtual planogram 770. Planogram server 720 generates a planogram 770 in accordance with information provided by planogram manager 710, possibly based on input provided by vendors 730, 740, 750, 760, or others.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the updating of the planogram as taught by Soon-Shiong in the method of Stansell because there is still a need for improved apparatuses, systems, and methods for providing interactive virtual marketplaces (Soon-Shiong ¶ [0009]).
Claim 14, the combination of Stansell in view of Soon-Shiong teaches the method of claim 13. Stansell does not disclose limitations associated with updating the planogram data, however Soon-Shiong further teaches, further comprising updating the visual representation in the scene to show the change overlaid on the image of shelf within the AR scene, wherein the scene is an augmented reality (AR) scene (Soon-Shiong: ¶ [0074] “If a frozen pizza is removed from the physical freezer (e.g., for purchase by a shopper, relocation, etc.), the frozen pizza can be removed from the virtual freezer in real-time or substantially real-time. If the planogram used to display items in the freezer is configured to instruct the replacement of the frozen pizza with a strawberry fruit bar, the dynamic planogram used to generate the virtual freezer can configure the display to present a representation of a strawberry fruit bar in place of the frozen pizza, also in real time or substantially real-time.”; also see ¶ [0083] “For example, the planogram can include rules that govern placement of virtual items (i.e., images of real-world objects) on a shelf in an augmented reality view on the display relative to items actually present on the shelf”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the updating of the planogram as taught by Soon-Shiong in the method of Stansell because there is still a need for improved apparatuses, systems, and methods for providing interactive virtual marketplaces (Soon-Shiong ¶ [0009]).
Response to Arguments
Applicant's arguments filed 04/06/2026 with respect to the 35 U.S.C. 101 rejections of claims 1-21 have been fully considered but they are not persuasive.
On pages 10 of the Remarks, Applicant argues “the claims are subject matter eligible for at least reciting a practical application under prong two of step 2A”, particularly, “the specification explicitly identifies technical problems with conventional virtual modeling systems and describes how the claimed invention, as captured in claim 1, provides technical solutions to those problems”.
The Examiner respectfully disagrees. In computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool. Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016). Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology. Similarly, "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015)
Applicant argues claim 1 improves the accuracy, speed, and efficiency (“usage of computing resources”) of rendering because the scene does not need to be rendered based on the entire model data but only locally-relevant model data. The technical improvements of increased speed/efficiency when processing less data are inherent with applying the abstract idea of filtering content on a generic computer. The claimed method does not include more than mere instruction to apply the abstract idea on a general purpose computer operating in its ordinary way to render a scene based on data stored in memory. In response to the improved accuracy argument, Examiner notes that if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. See MPEP 2106.05(a). The Specification does not contain the detail necessary to show an improvement in rendering accuracy compared to when an entire model is used for the rendering. Accordingly, these arguments are not persuasive.
The method of determining location-specific data and rendering a scene from that specific data, is not analogous to Enfish where the claims recited a specific data structure in combination with details in the Specification discussing how the invention improved the way a computer stores and retrieves data in memory. Processing a subset of data with a general purpose computer is distinct from reciting a specific data structure (a self-referential database) that is contrary to the structure of a standard relational database. In Enfish the computer’s capabilities to store and retrieve data are improved rather than invoking computers merely as a tool to store/retrieve/render as in the instant claims.
For at least these reasons, the Examiner is maintaining the § 101 rejections of claims 1-22.
Applicant's arguments filed 06/03/2026 with respect to the 35 U.S.C. 103 rejections of claims 1, 3-5, 11-12, and 15-20 have been fully considered but are not persuasive.
On page 16 of the Remarks, Applicant argues “Independent claim 1 has been amended to recite elements like those in allowable claim 3 ... claim 1 is now believed to be allowable over the cited art”.
The Examiner respectfully disagrees. The amendments to claim 1 include the features of claim 3 written in the alternative instead of requiring each feature. Stansell teaches wherein the planogram data indicates dimensions of a product and a location of the product within the shelf, as explained in the rejection, and therefore still anticipates claim 1 as amended.
For at least these reasons claims 1, 3-5, 11-12, and 15-22 remain rejected. The 102 rejections of independent claims 21 and 22 has been withdrawn, and these claims are considered allowable over the cited prior art. Claim 21 was amended to include the allowable subject matter of claims 7 and 8. Claim 22 was amended to include the allowable subject of claim 16 (without the subject matter of intervening claim 15), however the combination of Stansell and the next most relevant art such as Gruttadaria (US 2008/0147475 A1) was still deficient in teaching “wherein the scene upon rendering further visually indicates at least two products with a joint purchase rate above a threshold” as recited in claim 16.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
K. Walczak, J. Sokolowski and J. Dziekoński, (NPL Reference U) discusses the problem of building configurable virtual reality environments, with a particular focus on user interaction allowing convenient creation and exploration of such spaces.
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 KENNEDY A GIBSON-WYNN whose telephone number is (571)272-8305. The examiner can normally be reached M-F 8:30-5:30 PM.
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/K.G.W./ Examiner, Art Unit 3688
/VICTORIA E. FRUNZI/ Primary Examiner, Art Unit 3689 8/6/2026
