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 .
DETAILED ACTION
Status of Claims
This Non-Final Office Action is in response to Applicant’s Request for Continued Examination (RCE) filed 02/20/2026.
In accordance with Applicant’s amendment, claims 1 and 19-20 are amended. Claims 1-20 are currently pending.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submissions filed on 01/23/2026 have been entered.
Response to Amendment
The 35 U.S.C. §101 rejection of claims 1-20 is maintained and the §103 rejection of claims 1-20 has been updated to include a new reference relied on to address the new limitation(s) added to independent claims 1, 19, and 20.
Response to Arguments
Response to §101 arguments: Applicant's arguments (Remarks at pgs. 10-12) with respect to the §101 rejection of claims 1-20 have been considered, but are not persuasive.
In response to applicant’s argument that the claims include “the claims recite continuously capturing customer videos…to obtain a customer trajectories set” and involve videos of customers that “may be hundreds of customers… massive data to be processed” (Remarks at pg. 10), Applicant’s argument’s is unpersuasive because it relies on applying a much narrower interpretation than the claim language requires by seeking to import limitations from the specification, which is impermissible. In particular, the claims do not recite or require “continuously capturing customer videos” nor “customer trajectories” or “hundreds of customers…massive data to be processed” and therefore applicant’s argument relying on these features lack merit. See Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004). See also, CollegeNet, Inc. v. Apply Yourself Inc., 418 F.3d 1225, 1231 (Fed. Cir. 2005) (while the specification can be examined for proper context of a claim term, limitations from the specification will not be imported into the claims).
In response to applicant’s suggestion that the claims provide a solution “in the technical field of target tracking by video processing” (Remarks at pg. 10) and “a specific technological solution for solving the problem of identity resolution in multi-target tracking systems” (Remarks at pg. 11), the Examiner emphasizes that no improvement has been shown to the processor, to video processing, or to any technical field. Notably, the involvement of a one or more cameras and video are limited to “processing videos captured by one or more cameras,” which lacks any meaningful detail (or any detail) as to how any video processing is performed, but instead this activity is recited at a high level of generality and, although the updated §101 rejection addresses the camera(s) and video processing as an additional element, this feature is insufficient to integrate the abstract idea into a practical application or add significantly more to the claims.
In particular, under Step 2A Prong Two of the eligibility inquiry, the step for obtaining…by processing videos by one or more cameras is recited at a high level of generality and is considered insignificant extra-solution data gathering activity, which is not enough to amount to a practical application (MPEP 2106.05(g)). In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Next, under Step 2B, the step for obtaining…by processing videos by one or more cameras is considered insignificant extra-solution data gathering activity, which has been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). Furthermore, obtaining…by processing videos captured by one or more cameras is well-understood, routine, and conventional as evidenced, for example, by Steiner et al. (US 2020/0311788), noting in par. 17 that “camera known in the art capable of capturing video imagery and/or still images, and then communicating those captured images to computer server…identify customers” and by Garel et al. (US 2015/0025936), noting in par. 104 that “intelligence module utilizes algorithms known in the art (such as Intel AIM Suite or SightCorp Crowdsight) to determine a person's gender, approximate age, and sentiment (such as based upon video images captured by cameras or other information monitoring device).” Therefore, the step for obtaining…by processing videos by one or more cameras does not add significantly more to the claims.
Therefore, applicant’s arguments concerning the §101 rejection are not persuasive.
Response to §103 arguments: Applicant's arguments (Remarks at pgs. 13-16) with respect to the §103 rejection of claims 1-20 have been considered, however with the exception of the arguments addressed below, are primarily raised in support of the new limitation added to independent claims 1/19/20 and therefore are believed to be addressed in the new ground of rejection set forth below under §103.
In response to applicant’s argument that the claims include “the following operations,” citing operations S201, S203, S205, and S207 (Remarks at pg. 14), Applicant’s argument’s is unpersuasive because it relies on applying a much narrower interpretation than the claim language requires by seeking to import limitations from the specification, which is impermissible. See Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004). See also, CollegeNet, Inc. v. Apply Yourself Inc., 418 F.3d 1225, 1231 (Fed. Cir. 2005) (while the specification can be examined for proper context of a claim term, limitations from the specification will not be imported into the claims).
In response to applicant’s argument that “Eppley fails to disclose identify candidate customer trajectories corresponding to any shopping receipts” (Remarks at pg. 14), it is first noted that the claims do not recite “customer trajectories corresponding to…shopping receipts,” but instead recite determining, by a processor, a candidate customer track set of a receipt data group corresponding to one of a plurality of shopping receipts from the customer track set, which is taught by Eppley via the disclosed features for determining a shopper journey through a store (i.e., candidate customer track set), including indications of purchased items from the receipt data (i.e., set of receipt data group), and also including the checkout stand used by the shopper, which is also indicative of a candidate customer track set of a receipt data group (See Epley at pars. 42-43, 120, 123, and 130: FIGS. 16A and 16B show a map view of a given shopper's journey through a store [i.e., customer track set]; receipt 702 shown in FIG. 15 wherein the shopper purchased three items (item 1, item 2 and item 3); Each POS checkout stand 182A within a given venue 170A preferably provides transactional receipt data for each purchase made to an appropriate merchant server [i.e., obtaining a customer track set]; receipt data may additionally include identification of the checkout stand used to make the purchase, and identifying information of the shopper [i.e., customer track set and receipt data group]; See also, par. 169 and Fig. 2: running on, or implemented on, a single computer, processor, or controller node or distributed among a plurality of computer, processor). Therefore, Eppley has been shown to teach the disputed limitation.
Next, in response to applicant’s argument that “Eppley fails to involve the number of sold items matching the trajectory or the number of sold items matching the track point of interest” (Remarks at pg. 14, last paragraph), the Examiner respectfully disagrees and maintains that Eppley teaches features for identifying and counting items purchased by a shopper (i.e., sold items) and matching those items to a journey/route (i.e., track) of a shopper who purchased those items (See Eppley at pars. 121-127 and 130: item location database 375 provides assigned locations for items in the store, e.g., the items purchased on the receipt data 702; show a map view of a given shopper's journey through a store…product analytics server 700 adds a route to the ITEM 1 from the location of the Fisher Price toy purchased by the shown shopper; shopper purchased three items (item 1, item 2 and item 3), a best case route is generated for each of the following travel nodes). Therefore, Eppley teaches the disputed limitation.
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 non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance with the subject matter eligibility guidance set forth in MPEP 2106.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106.03), it is first noted that the claimed method (claims 1-18), device (claim 19), and non-transitory computer-readable storage medium (claim 20) are each directed to a potentially eligible category of subject matter (i.e., process, machine, and article of manufacture). Accordingly, claims 1-20 satisfy Step 1 of the eligibility inquiry.
With respect to Step 2A Prong One of the eligibility inquiry (as explained in MPEP 2106.04), it is next noted that the claims recite an abstract idea that falls under the “Certain methods of organizing human activity” abstract idea grouping by reciting limitations that set forth activities for managing commercial interactions (marketing, or sales activities or behaviors) or managing personal behavior or interactions (e.g., movements of a customer) and steps that, but for the generic computer implementation, may be implemented as “Mental Processes” (e.g., observation, evaluation, judgment, or opinion). The limitations reciting the abstract idea, as set forth in independent claim 1 are identified in bold text below, whereas the additional elements are presented in plain text and are separately evaluated under Step 2A Prong Two and Step 2B:
obtaining a customer track set by processing videos by one or more cameras (The “obtaining” step is considered marketing/sales activity because the obtained customer track set directly pertains to evaluation of customer behavior and purchase activity at a retail location, which is marketing intelligence, and furthermore this step is considered insignificant extra-solution data gathering activity, which is not enough to amount to a practical application (MPEP 2106.05(g)), and such extra-solution data gathering activity has also been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)) and determining, by a processor, a candidate customer track set of a receipt data group corresponding to one of a plurality of shopping receipts from the customer track set (The “determining” step is considered marketing/sales activity because the determined information may directly pertain to evaluation of customer behavior and purchase activity at a retail location, which is marketing intelligence, and furthermore this step is disembodied because the step does not recite “how” or by what means the determining is implemented and therefore this step could be implemented as mental activity such as by observation, evaluation, judgment, or opinion and/or with the aid of pen and paper);
counting, by the processor, for each track in the candidate customer track set, the number of sold items matching the track in a display area of a sold item set indicated by the receipt data group, as a first location matching count of the track (The “counting” step is considered marketing/sales activity because the counted sold items may directly pertain to evaluation of customer behavior and purchase activity at a retail location, which is marketing intelligence, and furthermore this step is disembodied because the step does not recite “how” or by what means the “counting” is implemented and therefore this step could be implemented as mental activity such as by observation, evaluation, judgment, or opinion and/or with the aid of pen and paper);
counting, by the processor, for each track in the candidate customer track set, the number of sold items matching track points of interest in a set of track points of interest of the track in the display area of the sold item set, as a second location matching count of the track (The “counting” step is considered marketing/sales activity because the counted sold items may directly pertain to evaluation of customer behavior and purchase behavior at a retail location, which is marketing intelligence, and furthermore this step is disembodied because the step does not recite “how” or by what means the “counting” is implemented and therefore this step could be implemented as mental activity such as by observation, evaluation, judgment, or opinion and/or with the aid of pen and paper); and
determining, by the processor, a customer track corresponding to the receipt data group in the candidate customer track set based on first location matching counts and second location matching counts of a plurality of tracks in the candidate customer track set (The “determining” step is considered marketing/sales activity because the determined information may directly pertain to evaluation of customer behavior and purchase activity at a retail location, which is marketing intelligence, and furthermore this step is disembodied because the step does not recite “how” or by what means the determining is implemented and therefore this step could be implemented as mental activity such as by observation, evaluation, judgment, or opinion and/or with the aid of pen and paper);
wherein a track point of interest included in the set of track points of interest of each track in the candidate customer track set is a track point indicating a location where a corresponding customer of the track shows interest in an item for sale displayed in an offline sales venue (The “wherein” limitation is considered marketing/sales activity because the track point location information related to a customer and item of interest for sale may directly pertain to evaluation of customer behavior and purchase activity at a retail location, which is marketing intelligence, and furthermore this step is disembodied because this activity could be implemented as mental activity such as by observation, evaluation, judgment, or opinion and/or with the aid of pen and paper).
Independent claims 19-20 recite similar limitations as those set forth in claim 1 as discussed above, and have therefore been determined to recite the same abstract idea as claim 1.
With respect to Step 2A Prong Two of the eligibility inquiry (as explained in MPEP 2106.04(d)), the judicial exception is not integrated into a practical application. Independent claim 1 recites the additional element of a processor and obtaining…by processing videos by one or more cameras, independent claim 19 recites the additional elements of a device, memory storing instructions, at least one processor, and obtaining…by processing videos by one or more cameras, and independent claim 20 recites the additional element of a non-transitory computer-readable storage medium storing a program, and obtaining…by processing videos by one or more cameras. The additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (network computing environment). See MPEP 2106.05(f) and 2106.05(h). The step for obtaining…by processing videos by one or more cameras is recited at a high level of generality and is considered insignificant extra-solution data gathering activity, which is not enough to amount to a practical application (MPEP 2106.05(g)). In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry (as explained in MPEP 2106.05), it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Independent claim 1 recites the additional element of a processor and obtaining…by processing videos by one or more cameras, independent claim 19 recites the additional elements of a device, memory storing instructions, at least one processor, and obtaining…by processing videos by one or more cameras, and independent claim 20 recites the additional element of a non-transitory computer-readable storage medium storing a program, and obtaining…by processing videos by one or more cameras. These additional elements have been evaluated, but fail to add significantly more to the claims because they amount to using generic computing elements or instructions/software to perform the abstract idea (See Spec. at pars. 55 and 57), which merely serves to tie the abstract idea to a particular technological environment (network computing environment), similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (generic computing environment) and does not amount to significantly more than the abstract idea itself. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). The step for obtaining…by processing videos captured by one or more cameras has been considered as well, but is considered insignificant extra-solution data gathering activity, which has been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). Furthermore, obtaining…by processing videos captured by one or more cameras is well-understood, routine, and conventional as evidenced, for example, by Steiner et al. (US 2020/0311788), noting in par. 17 that “camera known in the art capable of capturing video imagery and/or still images, and then communicating those captured images to computer server…identify customers” and by Garel et al. (US 2015/0025936), noting in par. 104 that “intelligence module utilizes algorithms known in the art (such as Intel AIM Suite or SightCorp Crowdsight) to determine a person's gender, approximate age, and sentiment (such as based upon video images captured by cameras or other information monitoring device).” Therefore, the additional elements do not add significantly more to the claims.
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
Dependent claims 2-18 recite the same abstract idea(s) as recited in the independent claims, and have been determined to recite further details/steps falling under the “Certain methods of organizing human activity” and/or “Mental Processes” abstract idea groupings discussed above. For example, dependent claims 2-3 provide further details about the receipt group data, which merely narrows the abstract idea and is devoid of any additional elements. Dependent claims 4-18 have been evaluated as well, but similarly recite details falling under the scope of the abstract idea itself. The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself.
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.
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.
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 1-14 and 19-20 are rejected under 35 U.S.C. §103 as unpatentable over Eppley et al. (US 2019/0213616, hereinafter “Eppley”) in view of Sharma et al. (US Patent No. 8,009,863, hereinafter “Sharma”) in view of Nasser (US 2008/0294487).
Claims 1/19/20: As per claim 1, Eppley teaches a method of processing a target track in target tracking (par. 1: systems and methods for extracting shopper traffic flow), characterized by comprising:
obtaining a customer track set by processing … determining, by a processor, a candidate customer track set of a receipt data group corresponding to one of a plurality of shopping receipts from the customer track set (pars. 42-43, 120, 123, and 130: FIGS. 16A and 16B show a map view of a given shopper's journey through a store [i.e., customer track set]; receipt 702 shown in FIG. 15 wherein the shopper purchased three items (item 1, item 2 and item 3); Each POS checkout stand 182A within a given venue 170A preferably provides transactional receipt data for each purchase made to an appropriate merchant server [i.e., obtaining a customer track set]; receipt data may additionally include identification of the checkout stand used to make the purchase, and identifying information of the shopper [i.e., customer track set and receipt data group]; See also, par. 169 and Fig. 2: running on, or implemented on, a single computer, processor, or controller node or distributed among a plurality of computer, processor or controller node);
counting, by the processor, for each track in the candidate customer track set, the number of sold items matching the track … of a sold item set indicated by the receipt data group, as a first location matching count of the track (pars. 43 and 120-123: e.g., product analytics server 700 or the merchant server 115 may search the POS transaction receipt data as desired, e.g., to obtain point of sale (POS) transaction receipt data on a given day/time at a given store. The POS transaction data includes items purchased [i.e., sold item set], and a day/time purchased; receipt data may additionally include identification of the checkout stand used to make the purchase, and identifying information of the shopper; receipt 702 shown in FIG. 15 wherein the shopper purchased three items (item 1, item 2 and item 3 [i.e., sold item set indicated by receipt data group]; See also, par. 169 and Fig. 2: implemented on, a single computer, processor or controller node or distributed among a plurality of computer, processor or controller nodes);
counting, by the processor, for each track in the candidate customer track set, the number of sold items matching track points of interest in a set of track points of interest of the track in location in the sold item set, as a second location matching count of the track (pars. 121-127 and 130: item location database 375 provides assigned locations for items in the store, e.g., the items purchased on the receipt data 702; show a map view of a given shopper's journey through a store…product analytics server 700 adds a route to the ITEM 1 from the location of the Fisher Price toy purchased by the shown shopper; shopper purchased three items (item 1, item 2 and item 3), a best case route is generated for each of the following travel nodes; See also, par. 169 and Fig. 2: running on, or implemented on, a single computer, processor or controller node or distributed among a plurality of computer, processor or controller nodes); and
determining, by the processor, a customer track corresponding to the receipt data group in the candidate customer track set based on first location matching counts and second location matching counts of a plurality of tracks in the candidate customer track set (pars. 121-127: For instance, in the exemplary receipt 702 shown in FIG. 15 wherein the shopper purchased three items (item 1, item 2 and item 3), a best case route is generated for each of the following travel nodes… NODE 1: From a default entrance to the assigned location of item 1…NODE 2: From the assigned location of item 1 to the assigned location of item 2…From the assigned location of item 2 to the assigned location of item 3…NODE 4: From the assigned location of item 3 to the location of the checkout stand used; See also, par. 169 and Fig. 2: running on, or implemented on, a single computer, processor or controller node or distributed among a plurality of computer, processor or controller nodes);
wherein a track point of interest included in the set of track points of interest of each track in the candidate customer track set is a track point indicating a location where a corresponding customer of the track shows interest in an item for sale displayed in an offline sales venue (pars. 73, 137, 167, and Fig. 25A: e.g., particular shoppers visualized may be filtered by a specific item purchased, dwelled upon, or even just recommended in an active location-triggered recommendation transmitted to the shopper in real-time as they journeyed through the store; using a generated map to allow specifically interested merchants to determine where in a given store that people who bought certain products walked; to determine which items or brands were purchased together; and perhaps most importantly to determine the success of dwells and/or impressions made on a customer as they walked between the items that they did ultimately purchase; The present invention also generated customer “impression” data relating to items or display areas that a given customer did not purchase but were exposed to during their path through a store on a given day. Thus, a merchant is enabled to understand in greater detail that a customer who walked past (and thus “dwelled upon”) mops and other kitchen items did not purchase any of those items but did purchase a “Rubbermaid” bucket; FIGS. 25A and 25B show a heat map and exemplary dwell statistics for aggregated shopper activity at a given store within a selected period of time).
Eppley does not explicitly teach processing videos by one or more cameras, nor teach that the counting of the number of sold items is performed in a display area.
Sharma teaches processing videos by one or more cameras (col. 10 lines 3-13 and Figs. 1-2: detects 302 and tracks 303 the customer in the video input images from a plurality of means for capturing images 100 utilizing multi-camera tracking methods as discussed with regard to FIG. 4 and FIG. 5. The present invention joins the trajectories of the customer tracks from a video of a means for capturing images 100 to another video of a means for capturing images).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Eppley with Sharma because the references are analogous since they are each directed to features for gathering and evaluating customer data at a point of sale, which is within Applicant’s field of endeavor of processing a target track of customers based on receipt data, and because modifying Eppley to incorporate Sharma’s camera based processing of videos, as claimed, is already suggested by Eppley (Eppley at par. 55: product analytics server may comprise…camera) and would serve Eppley’s pursuit of providing imagery and visualization of shopper traffic flow (Eppley at par. 81); and further obvious because 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.
Eppley and Sharma do not explicitly teach that the counting of the number of sold items is performed in a display area.
Nasser teaches counting a number of sold items in a display area (par. 116 and Figs. 1A/B: e.g., item quantities sold per category and/or zone; item quantities sold per zone [wherein Fig. 1A depicts zones as display areas within different aisles or departments in the store, e.g., Bakery display area/zone, Product display area/zone]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Eppley/Sharma with Nasser because the references are analogous since they are each directed to features for gathering and evaluating customer data at a point of sale, which is within Applicant’s field of endeavor of processing a target track of customers based on receipt data, and because modifying Eppley to incorporate Nasser’s counting of sold items in a display area, as claimed, would provide the expected benefit of providing business intelligence useful for improving product placement or to improve traffic flow (Nasser at pars. 3 and 167); and further obvious because 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.
Claims 19-20 are directed to a device and non-transitory computer-readable storage medium for performing substantially similar limitations as those recited in claim 1 and discussed above. Eppley, in view of Sharma/Nasser, teaches a device and non-transitory computer-readable storage medium for performing the limitations discussed above (Eppley at pars. 53-57 and Figs. 1-2 e.g., server…at least one CPU; computer readable medium), and claims 19-20 are therefore rejected using the same references and for substantially the same reasons as set forth above.
Claim 2: Eppley further teaches wherein the receipt data group comprises electronic-point-of-sale data provided by an electronic point of sale system (pars. 42-43, 54, 70, 120, 122, and Fig. 15 e.g., Mobile devices 105A, 1056, 105C may be used as mobile payment devices by customers at the POS checkout stands 182A, 1826, 182C to complete sale transactions of particular items 181C. Such transactions are included within POS transaction data utilized by a product location analytics server 700 of the present invention. Of course, other traditional payment methods may alternatively be used, e.g., a credit card, debit card, cash, etc. Each POS checkout stand 182A within a given venue 170A preferably provides transactional receipt data for each purchase made to an appropriate merchant server 115 via a network 150. In accordance with the invention, the transactional receipt data is either directly or indirectly forwarded to or accessible by the product location analytics server; point of sale (POS) transaction data collected in a suitable point of sale transaction database 345 provides transaction receipt data to a wayfinder server 710).
Claim 3: Eppley further teaches wherein the receipt data group comprises an item name list that indicates purchased items of a customer and purchase time information (pars. 43, 73, 120, 123, and Fig. 15: POS transaction receipt data…transaction data includes items purchased, and a date/time purchased. The POS transaction data may also include a price paid for the items purchased).
Claim 4: Eppley further teaches determining, using a target tracking model, a customer track set comprising customer tracks in the offline sales venue; and determining the candidate customer track set from the customer track set based on the purchase time information included in the receipt data group (pars. 73, 132, 136, 144, 155, and Figs. 4-14, 16, and 22-25: e.g., particular shoppers visualized may be filtered; journeys of brand-filtered shoppers, gaps in which may be augmented and completed using the location of items determined using POS transaction data (if available), are visualized using a generated map to allow specifically interested merchants to determine where in a given store that people who bought certain products walked; generates shoppers' routes on a floor plan of the store as shown by algorithm 720. In algorithm 730 the product analytics server 700 generates a ‘heat map’ filtered by appropriate parameters chosen by the user. For instance, exemplary parameters to analysis include a heat map of dwells or impressions by shoppers' traversing their routes in purchase of, e.g., a particular brand of goods; or who shopped on a particular day; or who shopped within a window of time on particular days; or who purchased a particular count of items, etc.; combining TIME and DATE filtering parameters, a heat map may be generated for presumed customer paths for items purchased within a selected time slot (e.g., during rush hour 6 pm-9 pm), over the last 7 days, or over the last 30 days, or on every Sunday over the past year; useful analytical information provided by comparing the “impressions” shown in FIG. 18 with the “dwells” shown in FIG. 19, for the filtered parameters (e.g., for customers at the selected store who purchased a “3M” product over the last 30 days); Routes that a particular customer takes on their shopping journey that are not reported using indoor positioning in a given store are then determined using routing between subsequently reported location points).
Claim 5: Eppley further teaches wherein for each track in the candidate customer track set (pars. 88, 123, 123, 132, and 154: plurality of sets of location detail records (LDRs) are obtained, each relating to one of a plurality of shoppers at the given store within a given time frame; product analytics server 700 determines physical movement of each shopper), when a minimum distance from the track to the display area of one of sold items in the sold item set is less than a first distance threshold, the first location matching count of the track is increased by 1 (Examiner’s Note: The preceding step is conditional such that under a broadest scenario, i.e. a scenario in which the minimum distance is not less than a first distance threshold, the method need not invoke the step for increasing the matching count. Notably, the claim does not even positively recite a step for determining, calculating, measuring, etc. a minimum distance to determine whether the condition is met, such that the claimed increasing of a matching count of the track is only increased by 1 if the condition necessarily occurs. Therefore, under a broadest scenario, the preceding limitation is not invoked and the prior art meets the claim by covering a scenario in which the conditional step is not invoked. See Ex parte Katz, 2010-006083, 2011 WL 514314, at *4 (BPAI 2011) (non-precedential) (citing In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004)); see also, Ex parte Masuda, 2016 WL 3036388 (PTAB May 11, 2016). If Applicant wishes to require the increased matching count feature to be positively performed within the scope of the claim, the Examiner suggests amending the claim to positively recite the step by removing the conditional language).
Claim 6: Eppley further teaches wherein for each track in the candidate customer track set (pars. 88, 123, 123, 132, and 154: plurality of sets of location detail records (LDRs) are obtained, each relating to one of a plurality of shoppers at the given store within a given time frame; product analytics server 700 determines physical movement of each shopper), when a minimum distance among distances from track points of interest in the set of track points of interest of the track to a display area of one of sold items in the sold item set is less than a second distance threshold, the second location matching count of the track is increased by 1 (Examiner’s Note: The preceding step is conditional such that under a broadest scenario, i.e. a scenario in which the minimum distance is not less than a second distance threshold, the method need not invoke the step for increasing the second matching count. Notably, the claim does not even positively recite a step for determining, calculating, measuring, etc. a minimum distance to determine whether the condition is met, such that the claimed increasing of a matching count of the track is only increased by 1 if the condition necessarily occurs. Therefore, under a broadest scenario, the preceding limitation is not invoked and the prior art meets the claim by covering a scenario in which the conditional step is not invoked. See Ex parte Katz, 2010-006083, 2011 WL 514314, at *4 (BPAI 2011) (non-precedential) (citing In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004)); see also, Ex parte Masuda, 2016 WL 3036388 (PTAB May 11, 2016). If Applicant wishes to require the increased matching count feature to be positively performed within the scope of the claim, the Examiner suggests amending the claim to positively recite the step by removing the conditional language).
Claim 7: Eppley further teaches wherein when at least one of the following conditions is satisfied, a track point on a track in the candidate customer track set is regarded as a track point of interest on the track: Condition 1: a residence time length associated with the track point is greater than a first predetermined time length threshold; and Condition 2: a corresponding tracking image of the track point indicates that a customer associated with the track point has a motion of reaching out to the item for sale displayed in the offline sales venue (Examiner’s Note: The preceding step is conditional such that under a broadest scenario, i.e. a scenario in which neither condition is satisfied, the method need not regard the track point on a track in the candidate customer track set as a track point of interest in the track. Therefore, under a broadest scenario, the preceding limitation is not invoked and the prior art meets the claim by covering a scenario in which the conditions are not invoked. See Ex parte Katz, 2010-006083, 2011 WL 514314, at *4 (BPAI 2011) (non-precedential) (citing In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004)); see also, Ex parte Masuda, 2016 WL 3036388 (PTAB May 11, 2016). If Applicant wishes to require the increased matching count feature to be positively performed within the scope of the claim, the Examiner suggests amending the claim to positively recite the step by removing the conditional language).
Claim 8: Eppley further teaches wherein the minimum distance is a two-dimensional Euclidean distance (Examiner’s Note: The preceding limitation is conditional because parent claim 5 does not require the minimum distance as discussed above, such that under a broadest scenario, the method need not invoke the action related to the minimum distance, nor does claim 8 or parent claim 5 positively recite a step for actually determining, calculating, measuring, etc. a minimum distance to determine whether the condition is met. Therefore, under a broadest scenario, the preceding limitation is not invoked and the prior art meets the claim by covering a scenario in which the condition is not invoked. See Ex parte Katz, 2010-006083, 2011 WL 514314, at *4 (BPAI 2011) (non-precedential) (citing In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004)); see also, Ex parte Masuda, 2016 WL 3036388 (PTAB May 11, 2016)).
Claim 9: Eppley further teaches wherein the minimum distance is a two-dimensional Euclidean distance (The preceding limitation is conditional because parent claim 5 does not require the minimum distance as discussed above, such that under a broadest scenario, the method need not invoke the action related to the minimum distance, nor does claim 9 or parent claim 6 positively recite a step for actually determining, calculating, measuring, etc. a minimum distance to determine whether the condition is met. Therefore, under a broadest scenario, the preceding limitation is not invoked and the prior art meets the claim by covering a scenario in which the condition is not invoked. See Ex parte Katz, 2010-006083, 2011 WL 514314, at *4 (BPAI 2011) (non-precedential) (citing In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004)); see also, Ex parte Masuda, 2016 WL 3036388 (PTAB May 11, 2016)).
Claim 10: Eppley further teaches wherein the display area of one of the sold items indicated by the receipt data group is represented by two-dimensional coordinates of a representative point (Fig. 14A and pars. 43, 46, and 116-117: e.g., Activity – 1 Min Ago Purchase…Aisle 15 Bay 22; floor plan(s) in some embodiments may divide the venues 170A, 170B in the y-coordinate by aisles, rows and the like, and may be associated with a size of the aisle, row, or the like (such as, for example, 7′-7″). The CAD floor plan(s) of the venues 170A, 1706 in these embodiments are divided in the x-coordinate by bay, section, shelving units, and the like. Some sections may occupy an entire row (a y-coordinate unit), or a portion of a row (an x-coordinate within a y-coordinate unit); product analytics server 700 or the merchant server 115 may search the POS transaction receipt data as desired, e.g., to obtain point of sale (POS) transaction receipt data on a given day/time at a given store).
Claim 11: Eppley further teaches wherein the display area of one of the sold items indicated by the receipt data group is represented by two-dimensional coordinates of a representative point (Fig. 14A and pars. 43, 46, and 116-117: e.g., Activity – 1 Min Ago Purchase…Aisle 15 Bay 22; floor plan(s) in some embodiments may divide the venues 170A, 170B in the y-coordinate by aisles, rows and the like, and may be associated with a size of the aisle, row, or the like (such as, for example, 7′-7″). The CAD floor plan(s) of the venues 170A, 1706 in these embodiments are divided in the x-coordinate by bay, section, shelving units, and the like. Some sections may occupy an entire row (a y-coordinate unit), or a portion of a row (an x-coordinate within a y-coordinate unit); product analytics server 700 or the merchant server 115 may search the POS transaction receipt data as desired, e.g., to obtain point of sale (POS) transaction receipt data on a given day/time at a given store).
Claim 12: Eppley further teaches wherein the purchase time information comprises a corresponding real-time checkout time when the customer purchases each item in real time by self-service (pars. 41-42, 49, 83, 105, 122, and Fig. 7A: use of a mobile device such as a mobile phone or smart phone for checkout, or use of a mobile handheld scanner device provided by the retailer for use within the store; after selecting the first item at the store, e.g., the Fisher Price Think & Learn “Code-A-Pillar”, the given shopper may then receive a recommendation for an associated item…the recommendation for the associated item may be sent to the given shopper outside the application program, e.g., via text. Ideally the recommendation for the associated item is sent to the user in real time so as to affect the given shopper's experience while on their pathway through the store; the present invention relates equally to the use of a mobile POS terminal checkout stands so long as the POS transactional data includes a location of the mobile POS terminal checkout stand at the time of purchase; location detail record (LDR) minimally contains time and position).
Claim 13: Eppley further teaches wherein in counting the first location matching count, for a track point on the track which matches a sold item in the sold item set in the …area, the track point satisfies: a real-time checkout time of the sold item matches a residence time period of the track point (pars. 2, 41-42, 49, 83, 105, 120-127, 136, and Figs. 7A and 15: Point of sale (POS) transactional data as used herein is presumed to include an identity of an item or items purchased, an identity of the particular checkout stand used for that purchase, and various other POS transactional data such as time purchased, date purchased; For instance, in the exemplary receipt 702 shown in FIG. 15 wherein the shopper purchased three items (item 1, item 2 and item 3); location detail record (LDR) minimally contains time and position); and wherein in counting the second location matching count, for a track point of interest in the set of track points of interest of the track which matches a sold item in the sold item set in … area location, the track point of interest satisfies: a real-time checkout time of the sold item matches a residence time period of the track point of interest (pars. 73, 120-127, 136, and Figs. 7A and 15: particular shoppers visualized may be filtered by a specific item purchased, dwelled upon, or even just recommended in an active location-triggered recommendation transmitted to the shopper in real-time; receipt data typically includes a list of items purchased, a priced at which they were purchased, and a date and time of the purchase; item location database 375 provides assigned locations for items in the store, e.g., the items purchased on the receipt data 702; wayfinder server 710 obtains the point of sale (POS) receipt data 702 from the point of sale transaction database 345, and the location of each item purchased from the item location database; combining TIME and DATE filtering parameters, a heat map may be generated; exemplary receipt 702 shown in FIG. 15 wherein the shopper purchased three items (item 1, item 2 and item 3), a best case route is generated for each of the following travel nodes: NODE 1: From a default entrance to the assigned location of item 1; NODE 2: From the assigned location of item 1 to the assigned location of item 2; NODE 3: From the assigned location of item 2 to the assigned location of item 3; NODE 4: From the assigned location of item 3 to the location of the checkout stand used), but does not explicitly teach item display area.
Nasser teaches item display area (par. 116 and Figs. 1A/B: e.g., item quantities sold per zone [wherein Fig. 1A depicts zones as display areas within different aisles or departments in the store, e.g., Bakery display area/zone, Product display area/zone]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further include, in the combination of Eppley/Sharma/Nasser, Nasser’s item display area, as claimed, in order to provide the benefit of business intelligence useful for improving product placement or to improve traffic flow (Nasser at pars. 3 and 167); and further obvious because 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.
Claim 14: Eppley further teaches wherein the residence time period of the track point is represented by a representative time of the track point; and the residence time period of the track point of interest is represented by a representative time of the track point of interest (pars. 8, 73, 132, 136-137, 139, 142-143, and Figs. 17-20: plurality of dwell locations associated with each of the filtered LDR; particular shoppers visualized may be filtered by a specific item purchased, dwelled upon, or even just recommended in an active location-triggered recommendation transmitted to the shopper in real-time; exemplary parameters to analysis include a heat map of dwells or impressions by shoppers' traversing their routes in purchase of, e.g., a particular brand of goods; or who shopped on a particular day; or who shopped within a window of time on particular days; or who purchased a particular count of items, etc.; generate a heat map showing normalized, or relative impressions and dwells, rather than an actual count of the impressions or dwells over the requested period of time; TIME is shown as being selectable between the “Last Day”, or “Last 7 Days”, or “Last 30 Days”. Of course, any particular time parameter may be implemented, e.g., within the past hour, within the past 6 months, within the past year. Also, a DATE parameter may be implemented, either separate from TIME or together with TIME).
Claim 16 is rejected under 35 U.S.C. §103 as unpatentable over Eppley et al. (US 2019/0213616, hereinafter “Eppley”) in view of Sharma et al. (US Patent No. 8,009,863, hereinafter “Sharma”) in view of Nasser (US 2008/0294487), as applied to claim 1 above, and further in view of Edge et al. (US 2015/0169597, hereinafter “Edge”).
Claim 16: Eppley teaches wherein determining a customer track corresponding to the receipt data group in the candidate customer track set based on first location matching counts and second location matching counts of a plurality of tracks in the candidate customer track set (as discussed above in the rejection of claim 1, which is incorporated herein) and as a portion of the customer track corresponding to the receipt data group (pars. 120 and 123: receipt data may additionally include identification of the checkout stand used to make the purchase, and identifying information of the shopper; generates the best case route presumably taken by each customer based on a sequence of travel nodes based on their relevant trans), but does not teach comprises: determining a weighted sum of a first location matching count and a second location matching count for each track in the candidate customer track set; determining a maximum weighted sum of all weighted sums; and determining a corresponding track corresponding to the maximum weighted sum.
Edge teaches comprises: determining a weighted sum of a first location matching count and a second location matching count for each track in the candidate customer track set (pars. 53 and 80: possible locations of a common type of item 70 crowd sourced for many users together with the corresponding probabilities that each location is the correct location for the type of item 70 may be combined (e.g. by a server 50) to yield a single location for the item 70 using weighted averaging or by finding a small area containing the greatest weighted sum of possible locations); determining a maximum weighted sum of all weighted sums; and determining a corresponding track corresponding to the maximum weighted sum (pars. 53 and 80: finding a small area containing the greatest weighted sum of possible locations).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Eppley/Sharma/Nasser with Edge because the references are analogous since they are each directed to features for gathering and evaluating customer data at a point of sale, which is within Applicant’s field of endeavor of processing a target track of customers based on receipt data, and because modifying Eppley/Sharma/Nasser to incorporate Edge’s weighted sum techniques, as claimed, would provide the expected benefit of more reliable and accurate indications of locations of items and users (Edge at pars. 38 and 48); and further obvious because 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.
Allowable over the prior art
Claims 15 and 17-18 are allowable over the prior art. In particular, claims 15 and 17 are allowable over the prior art, whereas claim 18 is allowable over the prior art based on its dependency from claim 17. Claims 15 and 17-18 are not allowed, however, because they are subject to a §101 rejection as discussed above. In addition, even if these rejections are overcome, claims 15 and 17-18 would be objected to as dependent upon rejected base claims and would be allowable only if rewritten in independent form including all of the limitations of their base claims and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Chen et al. (US 2021/0133787): discloses features for product popularity analysis and management, including analyzing traffic flows of customers.
Berry et al. (US 2021/0295081): discloses a tracking and analytics system for extracting visitor tracks in a space of interest based on three-dimensional computer models of the space created from captured images.
Bonner et al. (US 2009/0240571): discloses features for acquiring actual real-time shopper behavior during a shopper’s product selection.
Sorensen (US 2006/0010030): discloses features for modeling shopping behavior.
Glaser et al. (US 2017/0323376): discloses computer vision driven applications within an environment for tracking objects and their locations.
D. A. Mora Hernandez et al., "How Computer Vision Provides Physical Retail with a Better View on Customers," 2019 IEEE 21st Conference on Business Informatics (CBI), Moscow, Russia, 2019, pp. 462-471: discloses tracking locations of customers within retail stores in real-time using a video data acquisition system to aid in providing real-time dashboards, displaying personalized recommendations, efficiently deploying staff, shoplifting prevention and general store optimization.
J. Kröckel et al., "Customer Tracking and Tracing Data as a Basis for Service Innovations at the Point of Sale," 2012 Annual SRII Global Conference, San Jose, CA, USA, 2012, pp. 691-696: discloses customer tracking via aerial mounted surveillance cameras and computer vision algorithms, tracking and tracing of customers to facilitate visual analysis such as number of visits and movement patterns.
P. L. Venetianer et al., "Video verification of point of sale transactions," 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, London, UK, 2007, pp. 411-416: discloses intelligent video and POS analysis to aid with loss prevention in a retail environment.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Timothy A. Padot whose telephone number is 571.270.1252. The Examiner can normally be reached on Monday-Friday, 8:30 - 5:30. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Brian Epstein can be reached at 571.270.5389. The fax phone number for the organization where this application or proceeding is assigned is 571- 273-8300.
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/TIMOTHY PADOT/
Primary Examiner, Art Unit 3625
03/20/2026