DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim 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 1-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) limitations of receiving media content and a location, detecting an image, aligning the image, selecting a subset of matches based on location and matching based on the image, and causing a display. These limitations fall under the mental process/ math. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “by a processor,” and “client device” nothing in the claim precludes the determining step from practically being performed in the human mind. The receiving step is routine data gathering, the detecting is a mental step, the aligning is mental/ math, the selecting can be done mentally, the detecting can be done mentally via observation, and the causing a display is displaying results which falls under insignificant post solution activity of verifying barcodes and providing results, thus the method of claim 1 is abstract, and independent claims 13 and 25 are seen as the corresponding computer readable medium and system claims respectively, and the same rejection applies thereto.
The processor and client device is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data (data processing/ gathering). This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept. Thus independent claims 1, 13, and 25 are ineligible under 101.
Dependent claims 2-3 are further describing the abstract idea with generic computer components. Claim 4 is describing the type of data and is not a practical application but limitations on the data, which is further specifying details of the abstract idea. Claim 5 is drawn to math (determining coordinates) and thus is still abstract as its drawn to mental/ math steps. Claims 6-12 are drawn to math, mental steps, and generic components/ limitations related to abstract limitations regarding the data and math, and are generic computer components performing generic computer limitations/ math as a computerization of mental processes and thus the limitations remain abstract. There is not an improvement to the computer as the computer is merely being used as a tool. Thus the dependent claims are rejected also at least based on their dependency. Claims 13-25 have been discussed above re claims 1-12.
Re the newly added limitations to the independent claim of the code being bits encoding/ indexing, the Examiner notes that such limitations are drawn to the details of the data of the abstract idea, and thus are specifying details of the abstract idea. Such a visual code falls under mental processes/ math performed by a generic computer/ components. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). MPEP 2106.04.a.2.III. Even further, regarding details of an encoded visual code and/ or decoding to be able to eligible under 101 would require more than a traditional barcode/ visual code, (MPEP 2106.04a2. a claim to a specific data encryption method for computer communication involving a several-step manipulation of data, Synopsys., 839 F.3d at 1148, 120 USPQ2d at 1481 (distinguishing the claims in TQP Development, LLC v. Intuit Inc., 2014 WL 651935 (E.D. Tex. Feb. 19, 2014)). Even further, the Examiner notes that Recentive Analytics, Inc v. Fox Corp (Fed Cir, 2023-2437, 4/18/2025) teaches that generic machine learning techniques in an environment are still abstract.
Re the newly added limitations of a “neural network” this falls under math concepts being applied to a specific environment (verifying/ matching codes), performed by a generic computer component(s) and is still abstract.
Re the newly added limitations of the details of matching, this is seen as mental steps (locating and identifying) as it pertains to routine data gathering, and the initializing and downsampling are seen as mental steps/math applied to the code environment (verifying/matching).
Re the newly added limtaitosn of claims 12 and 24, such limitations of bounding boxes, and regressing into a probability mapping, these are seen as generic computer applied mental concepts/ math that are applied to the abstract idea, as cropping can be mental and mapping is seen as a math step.
Appropriate correction is requested.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-8, 13-20, and 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mott et al. (US 10147399) in view of Lotter (US 20200334778) and Do et al. (US 20210390677) and Ran et al. (WO 2020083029).
Re claim 1, Mott et al. teaches:
Receiving by a processor from a client device, a media content item and a location of the client device (abstract+ wherein the location and image (media content item) is received);
Re the newly added limitation that the visual code includes a plurality of encoded data bits and indexed a code, Mott et al. teaches at col 3, lines 63+ the use of image processing including pattern recognition, barcode and datamatrix code reading as part of the process to obtain information. Additionally, the Examiner notes that the recited captured visual code is not decoded, it is simply a type of image used to fetch data. Nonetheless, the teachings of Mott et al. teaches a barcode which is interpreted as encoded data bits that indexed a code, as the bits/ parts of the barcode being decoded index a code (data), as traditional barcodes do.
Mott et al. teaches aligning the image of the captured graphical representation to generate a rectified image (col 3, lines 40+ wherein processes are taught to enhance such as filtering, thresholding, etc.) Given such teachings it would have been obvious to one of ordinary skill in the art to generate a rectified image as part of processing an image so as to have a high quality image for comparison.
Mott et al. teaches selecting, based on a location of the device, a subset of codes of a plurality of codes stored in a database having a plurality of location estimates associated therein, determining a match and casing a selectable item to be displayed (claim 1+ wherein the location of the device and the image itself as used to determine a subset of images/ content to be provided to the user). Though silent to reciting that the location is used to select a subset which is then used to detect a match with the rectified image (Mott et al. teaches both the location and image itself and does not specify the order) the Examiner notes that it would have been well within the ordinary skill in the art to process in that particular order (location than image) in order to have the predicted outcome of reducing possible matches based on location and then on the image itself, in order to reduce the processing power/ load on the system. One would have been motivated to try this order as one of a plurality of possible ways to process the data for an expected outcomes.
Mott et al. teaches scanning of barcodes in scenes but is silent to explicitly reciting the restaurant having a barcode thereon, even though FIG. 1C shows plural fiducial areas and barcode reading has been discussed above.
Nonetheless, Lotter teaches that buildings can have QR codes (paragraph [0014]+) to be scanned and affixed or approximate the buildings, on plaques or walls, or a sign, etc.
Prior to the effective filing date, it would have been obvious to one of ordinary skill in the art to combine the teachings to provide markers/ codes for information purposes.
Re the newly added limitations’ of the detecting including the initializing and down sampling, Mott et al./ Lotter are silent to such limitations.
Ran et al. teaches such limitations via binarizing and downsampling in order to locate a code to be decoded “For each of the obtained down-sampled images, in order to facilitate subsequent decoding of the graphics code, the terminal performs image binarization processing to obtain a binarized image containing only black and white and two colors. Among them, the image binarization processing can be mixed Binarization, fast window binarization and adaptive binarization. As shown in FIG. 2, the terminal binarizes the original image 21 and obtains a binarized image 24” and “For the extracted graphic code 32, the terminal samples it based on the principle of small image upsampling and large image downsampling to obtain a sampling map 33, and performs image binarization processing on the sampling map 33 to obtain a binary map 34. For the obtained binarized image 34, the terminal decodes according to the graphic code type and uses a graphic code decoder corresponding to the graphic code type to obtain a graphic code recognition result corresponding to the binarized image 34.” As these processes are intpereted to extract reliable/ readable binarized data, it would have been obvious for such a process would result in a code that is compatibly to be identified with those of the prior art matching teachings.
Prior to the effective filing date, it would have been obvious to one of ordinary skill in the art to combine the teachings in order to process the image data to reduce memory/ processing power and to enable it to be matched/ decoded, consistent with downsampling and binarization as known in the art for code processing.
Re the newly added limitations of a “neural” aligner and code detector, the Examiner notes that the use of neural networks/ machine learning/ AI are routine and conventional in the art of machine intelligence/ accuracy/ predictability. Nonetheless, Do et al. teaches such limitations (paragraph [0091]+ and [102]+) via neural networks and machine learning) and also aligning.
Prior to the effective filing date, it would have been obvious to one of ordinary skill in the art to combine the teachings for machine intelligence and accuracy.
Re claims 2-3, FIG. 1B+ shows a URL based on the images captured.
Re claims 4-6, the abstract+ teaches GPS which is interpreted as 3d, wherein a coordinate is interpreted as average.
Re claim 7, IMU orientations are taught (abstract+).
Re claim 8, though silent to indexing using r-tree data structures, the Examiner notes that r-tree data structures are known in the art for spatial accessing of data, such as indexing of coordinates and multidimensional information and therefore is an obvious expedient for indexing/ spatial accessing of geographical coordinates for expected results of organization and access.
Re claim 12, the Examiner notes that a detector and alignment as part of basic image processing has been discussed above. The recitation of a “neural network” detector/ aligner does not impart any structural limitations aside from that the detector and aligner are configured to work with a neural network. The Examiner notes that detectors and aligners are interpreted to be configured to work with neural networks absent a more specific recitation. Basic straightening/ aligning/ preprocessing of images is an obvious expedient to place them in form for manipulation/ use.
Re claims 13-20 and 24-25, the limtaitosn have been discussed above re claims 1-8, 12, and 1.
Claim(s) 12 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mott et al. in view of Lotter, Do et al., Ran et al., as discussed above, in view of Zucker et al. (US 20200104748).
The teachings of Mott et al./ Lotter/ Do et al./ Ran et al. have been idscused above but are silent to bounding boxes for cropping and mapping/ probabilities.
Zucker et al. generally teaches such limitations with probability and probability mapping (paragraph [0030]+) and bounding boxes for cropping (paragraph [0024]+).
Prior to the effective filing date, it would have been obvious to one of ordinary skill in the art to combine the teachings to target regions for interest and for math/ probability based decisions for accuracy.
Claim(s) 1-6, 8, 13-20, and 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Uchida (US 20140223319) in view of Lotter, Do et al., Ran et al., as discussed above.
Uchida et teaches the claimed limtaiitons as Uchida scans the logo of a building to capture an image. Simply put, a graphic that is detected/ imaged and used as a pointer for data fetching, is functionally equivalent and can be said to be a visual code and matched and used to fetch as set forth in the claims, as there is no decoding of a barcode recited, for example. Thus a visual code functions the same as an image of the prior art, absent a decoding limitation, and thus using an image of the prior art because it’s obvious that any graphic that is imaged can be said to be a code and matched and used to fetch, as the image is just broken up into pieces of data and used to fetch data, similar to how a barcode is processed when decoded, though the claims do not recite decoding. Thus as the prior art teaches an image/ graphic that is imaged and processed and used to fetch data, it can obviously be seen as a code and match and used to fetch data absent a decoding step precluding such an interpretation.
A subset of visual codes based on the location and image data is provided (paragraph [0078]+. A match is detected and displayed by the client device as codes/ promotion content/ etc. Though silent to aligning an image to generate a rectified image, this is merely interpreted as traditional image processing known in the art as an obvious expedient to provide a clean and high quality image for processing purposes. One would have been motivated to process/ preprocess captured images for accuracy in their use in such instances. Though silent to selecting based on location prior to image matching, the Examiner notes that selecting based on location first is one of a plurality of known solutions available to one of ordinary skill in the art (based on location first or image first). One would have been motivated to select based on location first as way to narrow down/ limit comparisons to ease the processing load.
Re the newly added limitation of a visual code with data bits and indexing, Uchida is silent to such limitations.
Nonetheless, Lotter teaches that buildings can have QR codes (paragraph [0014]+) to be scanned and affixed or approximate the buildings, on plaques or walls, or a sign, etc.
Prior to the effective filing date, it would have been obvious to one of ordinary skill in the art to combine the teachings to provide markers/ codes for information purposes.
Re the newly added limitations of the neural network and downsampling and binarization (bits) the teachings have been discussed above re Do et al. and Ran et al.
Prior to the effective filing date, it would have been obvious to one of ordinary skill in the art to combine the teachings for the results as discussed above (machine intelligence, accuracy, reduce memory/ processing power and to enable it to be matched/ decoded, consistent with downsampling and binarization as known in the art for code processing).
Re claim 2-3, FIG. 5A shows a camera and FIG. 3B shows a URL.
Re claims 4-6, FIG. 5B shows GPS functionalities, interpreted as average 3d coordinates.
Re claim 8, though silent to indexing using r-tree data structures, the Examiner notes that r-tree data structures are known in the art for spatial accessing of data, such as indexing of coordinates and multidimensional information and therefore is an obvious expedient for indexing/ spatial accessing of geographical coordinates for expected results of organization and access.
Re claim 12, the Examiner notes that a detector and alignment as part of basic image processing has been discussed above. The recitation of a “neural network” detector/ aligner does not impart any structural limitations aside from that the detector and aligner are configured to work with a neural network. The Examiner notes that detectors and aligners are interpreted to be configured to work with neural networks absent a more specific recitation. Basic straightening/ aligning/ preprocessing of images is an obvious expedient to place them in form for manipulation/ use.
Re claims 13-18, and 25, the limitations have been discussed above re claims 1-6 and 1.
Claim(s) 12 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Uchida in view of Lotter, Do et al., Ran et al., as discussed above, in view of Zucker et al. (US 20200104748).
The teachings of Uchida/ Lotter/ Do et al./ Ran et al. have been discussed above but are silent to bounding boxes for cropping and mapping/ probabilities.
Zucker et al. generally teaches such limitations with probability and probability mapping (paragraph [0030]+) and bounding boxes for cropping (paragraph [0024]+).
Prior to the effective filing date, it would have been obvious to one of ordinary skill in the art combine the teachings to target regions for interest and for math/ probability based decisions for accuracy.
Response to Arguments
Applicant's arguments filed have been fully considered but they are not persuasive.
The Examiner has provided additional art to teach the newly added limitations.
Re the Applicants argument of the 101 rejection to the independent claims are not abstract, the Examiner notes that the steps of verifying a barcode and providing results are seen as mental/ math. Receiving is data gathering, detecting is a mental step, aligning is math (calculations via weighted probabilities is math per specification paragraph [0096]+), selecting can be done mentally, detecting can be done mentally, and displaying the results is insignificant post solution activity. The newly added limitations about the type of visual code data is merely specifying details of the data of the abstract idea. The mention of a processor is merely generic computer components performing routine/ generic computing steps. There is not an improvement to a computer with such abstract limitations and generic computer components of a processor cannot integrate an abstract/ mental process into a practical application.
Re the Applicants argument about neural networks, such limitations are generic computer components performing mental steps and a neural aligner is a generic computer performing math calculations (probability’s). Even further, the Examiner notes that Recentive Analytics, Inc v. Fox Corp (Fed Cir, 2023-2437, 4/18/2025) teaches that generic machine learning techniques in an environment are still abstract.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 11494577 teaches a neural network code detector as known in the art.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL I WALSH whose telephone number is (571)272-2409. The examiner can normally be reached 7-9pm.
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/DANIEL I WALSH/Primary Examiner, Art Unit 2876