DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
2. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 submission filed on 09/10/2026 has been entered.
3. Currently claims 1, 3, 8, 10, 15, 21, 22 and 26 have been amended; claims 4-7, 11-14, 17-20 and 23 are already canceled. Therefore, claims 1-3, 8-10, 15, 16, 21, 22 and 24-26 are pending in this application.
Claim Objections
4. Claims 1-3, 8-10, 21, 22 and 24-26 are objected to for the following informality: the phrase, “encoding sequential arranging multiple 3D models”, as recited in the second line of the last paragraph of each of claims 1 and 8, appears to be a typographical error for --encoding sequentially arranged multiple 3D models--(e.g., see the phrase in the second line of the last paragraph of claim 15). Thus, appropriate correction is required.
Claim Rejections - 35 USC § 101
5. Non-Statutory (Directed to a Judicial Exception without an Inventive Concept/Significantly More)
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 1-3, 8-10,15, 16, 21, 22 and 24-26 are rejected under 35 U.S.C.101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The current claims fall within one of the four statutory categories of invention (MPEP 2106.03).
Step 2A [Wingdings font/0xE0] Prong One:
The claim(s) recite a judicial exception, namely an abstract idea, as shown below:
— Considering each of claims 1, 8 and 15 as representative claims, the following claimed limitations recite an abstract idea (note that the term “video” is construed as a “content item” since a video is itself a content item):
receive a request for a [content item] illustrating an event at a target location and a target time frame;
determine one or more requirements for the [content item];
[collect], based on the one or more requirements, a plurality of crowdsourced [content items] illustrating the event;
extract a set of metadata from the plurality of crowdsourced [content items], the set of metadata including geographical information, capture orientation, and timestamp information;
cluster the plurality of crowdsourced [content items] into location clusters based on a geographical proximity defined by a pre-set threshold distance from the target location;
determine, based on the metadata, a chronological sequence of the clustered [content items] within the location cluster during the target time frame;
determine a first temporal image set of the plurality of crowdsourced [content items];
synchronize the first temporal image set in terms of temporal alignment and spatial alignment based on the metadata;
construct a three-dimensional (3D) model of the event from the synchronized content of the first temporal image set;
create [content item] of the event, [by] sequentially arranging multiple 3D models from a plurality of temporal image sets including the first temporal image set, the [content item] meeting the one or more requirements.
Thus, the limitations identified above recite an abstract idea since the limitations correspond to certain methods of organizing human activity and/or mental processes, which are part of the enumerated groupings of abstract ideas identified according to the current eligibility standard (see MPEP 2106.04(a)).
The claims correspond to certain methods of organizing human activity, wherein a content item—such as a video—is created, in response to a request received from a user, including on one or more requirements; and wherein the content item is created based on analyzing information gathered from content items that other users provided, including: identifying geographical information; capture orientation, timestamp information; grouping the content items based on location—such as, a geometrical proximity defined by a preset threshold distance from the target location; determining, using the metadata, the chronological sequence of the content items in the group above; determining a first image set of the plurality of crowdsourced content using a mathematical formula; synchronizing the first temporal image set in terms of temporal alignment and spatial alignment based on the metadata; constructing a 3D model of the event from the synchronized first temporal image set; and creating the content item of the event, the content item including sequentially arranging multiple 3D models from a plurality of temporal image sets, including the first image set above, etc.
Note that the finding above—certain methods of organizing human activity—is consistent with the specification. For instance, the specification describes that a user provides a set of content, including a request to create media-based case study for an educational topic; and wherein, once a requirement(s) is determined for the educational topic, a search query is constructed, so that one or more relevant media content items are identified—using the search query—from media items that other users provided; and thereby, a customized content item (a customized video) is created by considering one or more factors, including: the location of capture, the direction of capture, the timing of the capture, etc., and eventually the end result is presented to the user (e.g., see [0031] to [0035]).
The current claims also correspond to a mental process; such as, a process that can be performed in the human mind and/or using a pen and paper, given the limitations that recites the process of: determining one or more requirements for a given content item (e.g. a video); extracting metadata that includes multiple pieces of information (e.g., geographical information, capture orientation, timestamp information); and determining, based on temporal information, a chronological sequence of clustered content items (e.g., videos) within the location clusters during the target time frame, etc.
Thus, given such limitations that recite the process of evaluation, observation, and/or judgement, etc., the current claims do recite a mental process.
Similarly, given the limitation that recites a mathematical formula; namely, the claimed “linear interpolation function” (also see [0051] of the specification, which signifies the “linear interpolation formula”), each of the current claims further recites a mathematical concept.
Step 2A [Wingdings font/0xE0] Prong Two:
The claim(s) recite additional element(s), wherein a computer-based system is utilized as a tool to facilitate the recited steps/functions regarding: receiving input or a request (e.g., “receiving, by a content creation program, a request for a volumetric video illustrating an event at a target location and target time frame”); determining one or more requirement(s) (e.g., “determining, by the content creation program, one or more requirements for the volumetric video”); collecting content items from sources over a network (e.g., “retrieving, based on the one or more requirements, a plurality of crowdsourced videos illustrating the event from a social media network”); analyzing the collected content items (e.g., “extracting, by the content creation program, metadata from the plurality of crowdsourced videos . . . clustering the plurality of crowdsourced videos into location clusters based on a geographical proximity defined by a pre-set threshold distance from the target location”); determining one or more results (e.g., “determining, based on the metadata, a chronological sequence of clustered videos within the location clusters during the target time frame; determining a first temporal image set of the plurality of crowdsourced videos by applying geometric operations comprising: joining multiple points corresponding to the plurality of crowdsourced videos . . . using a linear interpolation function from a first point to subsequent points and connecting a last point back to the first point to define a closed loop contour”); synchronizing images (e.g., “synchronizing the first temporal image set in terms of temporal alignment and spatial alignment based on the metadata into synchronized media content”); generating a customized content (e.g., “constructing a three-dimensional (3D) model of the event from the synchronized first temporal image set, wherein constructing the 3D model comprises: analyzing one or more frames of the synchronized media content . . . verifying consistency across the synchronized media content”; “creating the volumetric video of the event . . . comprising encoding sequential arranging multiple 3D models from a plurality of temporal image sets including the first temporal image set, in a volumetric video format that stores 3D geometry and texture information for each frame of the volumetric video meeting the one or more requirements”), etc.
However, the claimed additional element(s) fail to integrate the abstract idea into a practical application since the additional element(s) are utilized merely as a tool to facilitate the abstract idea. Thus, when each claim is considered as a whole, the additional element(s) fail to integrate the abstract idea into a practical application since they fail to impose meaningful limits on practicing the abstract idea. For instance, when each of the claims is considered as a whole, none of the claims provides a technological improvement over the relevant existing technology.
The observations above confirm that the claims are directed to an abstract idea.
Step 2B
Accordingly, when the claim(s) is considered as a whole (i.e., considering all claim elements both individually and in combination), the claimed additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to “significantly more” than the abstract idea itself (also see MPEP 2106). The claimed additional elements are directed to conventional computer elements, which are serving merely to perform conventional computer functions.
Accordingly, when each of the current claims is considered as a whole (e.g., see the discussion under Prong Two above regarding such consideration of the claim as a whole), none of the claims recites an element—or a combination of elements—directed to an inventive concept.
It is also worth to note that use of the conventional computer/network technology to facilitate the process of generating pertinent content to a user (e.g., one or more customized videos, etc.), based on a request and/or parameters received from the user, etc., is already directed to a well-understood, routine or conventional activity in the art (see US 2016/0105708; US 2015/0143239; US 2013/0117780, etc.).
Of course, the same is true regarding the process of identifying, using metadata, related scenes from one or more videos; and/or generating one or more customized videos based on compiling multiple captured scenes, etc. (e.g. see US 2016/0080835; US 2013/0325869; US 2009/0132924; US 2018/0310025; US 2018/0160251, etc.).
The above observation confirms that each of the current claims fails to amount to “significantly more” than an abstract idea.
It is worth noting that the above analysis already encompasses each of the current dependent claims (i.e., claims 2, 3, 9, 10, 13, 16, 21, 22 and 24-26). Particularly, each of the dependent claims also fails to amount to “significantly more” than the abstract idea since each dependent claim is directed to a further abstract idea, and/or a further conventional computer element utilized to facilitate the abstract idea.
Thus, the findings above demonstrate that none of the claims is implementing an element—or a combination of elements—directed to an inventive concept (e.g., none of the current claims is reciting an element—or a combination of elements—that provides a technological improvement over the existing/conventional technology).
► Applicant’s arguments directed to section §101 have been fully considered (the RCE filed on 09/10/2026, which includes the response filed on 08/27/2026). However, the arguments art not persuasive at least for the following reasons:
Firstly, regarding the Office’s analysis presented under Prong One of Step 2A, Applicant is asserting that “[t]he Office Action alleges that independent claim 1 recites the judicial exception of ‘mathematical steps and fundamental aspect of mathematics or directed to mental processes performed in the human mind’ . . . the features of amended claim 1 do not recite mathematical relationships, mathematical formulas or equations, and mathematical calculations, and therefore, do not recite a mathematical concept. For example, Applicant respectfully submits that ‘receiving, by a content creation program, a request for a volumetric video illustrating an event at a target location and target time frame,’ . . . and ‘creating the volumetric video of the event, creating the volumetric video comprising encoding sequential 3D models in a volumetric video format that stores 3D geometry and texture information for each frame of the volumetric video,’ as recited in amended claim 1, do not recite mathematical relationships, mathematical formulas or equations, and mathematical calculations . . . even if the above-identified features of amended claim 1 are based on or involve a mathematical concept, they do not recite a mathematical concept” (emphasis added).
However, besides misconstruing the eligibility inquiry under Prong One, Applicant appears to omit part of the Office’s findings outlined under Prong One. For instance, unlike Applicant’s theory, the inquiry under Prong One does not necessarily require all of the limitations to recite a mathematical concept; rather, the inquiry requires one to determine whether there is a limitation(s) that recites a mathematical concept. In this regard, each of claim 1, 8 and 15 recites, the step of interpolating multiple data points using a linear interpolation function (e.g., see the 9th paragraph of claim 1). Thus, it is quite evident—at least to one having ordinary skill in the art—that the above is indeed a mathematical concept. Accordingly, given the fact that each of the current independent claims recites the above mathematical concept, all of the current claims are once again reciting a mathematical concept. So far, Applicant fails to consider, much less challenge, the fact above. Instead, while listing part of the limitations, which the Office never associated with a mathematical concept (see the limitations Applicant listed on pages 13-14 of the current argument), Applicant is attempting to challenge the Office’s finding regarding the limitation that recites a mathematical concept. Consequently, Applicant’s arguments are not persuasive.
In addition, regarding mental processes, Applicant is asserting that “the features of amended claim 1 cannot practically be performed in the human mind and thus do not recite a judicial exception. For example, Applicant respectfully submits that a human mind cannot practically perform ‘receiving, by a content creation program, a request for a volumetric video illustrating an event at a target location and target time frame,’ ‘determining, by the content creation program, one or more requirements for the volumetric video,’ ‘retrieving, based on the one or more requirements, a plurality of crowdsourced videos illustrating the event from a social media network’ . . . ‘analyzing one or more frames of the synchronized media content to create a 3D point cloud and extracting closed-loop contour information from the 3D model by identifying a silhouette of a subject in each frame of the reconstructed 3D model and verifying contour consistency across the synchronized media content,’ and ‘creating the volumetric video of the event, creating the volumetric video comprising encoding sequential 3D models in a volumetric video format that stores 3D geometry and texture information for each frame of the volumetric video,’ as recited in amended claim 1” (emphasis added).
However, here also Applicant appears to fail to properly apply the inquiry under Prong One. In particular, besides referring to the limitations that the Office never considered to be mental processes, Applicant is relying on the computer elements, which are part of the additional elements, to challenge the Office’s finding regarding mental processes. However, similar to the point made above, the eligibility inquiry under Prong One does not necessarily require all the limitations of the claim to recite a mental process. Instead, it only requires one to identify the limitation(s) that recite a mental process. Accordingly, the current claims incorporate (i) limitations that recite a mental process, and (ii) limitations that are beyond a mental process, which include the additional elements. In contrast, while excluding the additional elements, the inquiry under Prong One is requiring the Office to identify only the limitations that recite a mental process—i.e., limitations that recite the concept of observation, evaluation and/or judgement etc. Consequently, as part of its finding regarding mental processes, the Office identifies the limitations that recite the process of: determining one or more requirements for a given content item (e.g. a video); extracting metadata that includes multiple pieces of information (e.g., geographical information, capture orientation, timestamp information); and determining, based on temporal information, a chronological sequence of clustered content items (e.g., videos) within the location clusters during the target time frame, etc. (see above the finding under Prong One; also see page 5 of the office action dated 07/01/2026). So far, Applicant fails to challenge, much less negate, the Office’s findings presented under Prong One of Step 2A. Instead, while blending the additional elements with part of the abstract idea (e.g., see the limitations that Applicant listed on pages 15 and 16 of the current argument), Applicant is attempting to challenge the Office’s finding regarding mental processes. Consequently, Applicant’s arguments are not persuasive.
Applicant also appears to be admitting, at least implicitly, that the claims do recite the abstract idea per the group certain methods of organizing human activity. This is because Applicant does not challenge the Office’s finding in this regard.
Secondly, regarding Prong Two of Step 2A, Applicant is asserting that “amended claim 1 includes additional elements that integrate the alleged abstract idea into a practical application . . . claim 1 is directed to improvements in the technical field of
image-processing and geometric-reconstruction operations to transform synchronized two-dimensional video frames into a textured, depth-resolved, frame-by-frame 3D representation. Paragraph 2 of the specification describes the technical problem by reciting that ‘the usefulness and quality of any volumetric video is dependent on how many directional videos are considered and their respective quality of video, and the processing engine which generates the volumetric video.’ Paragraphs 11-13 of the specification, for example, describe a technical solution by disclosing that ‘in obtaining content for a volumetric video creation, crowdsource information gathering is an effective way of gathering input, and different crowdsource users can capture a geographic area from different direction . . . advantages are obtained by performing a comparative evaluation of crowdsourced media content based at least on quality (e.g., pixel density, stable frames, zoom level) and the duration, and select which media content is to be considered for the case study creation . . . the specification discloses a technical solution that improves input selection for volumetric-video creation by evaluating video quality, duration, coverage, capture direction, and closed-loop suitability to identify technically usable input sets” (emphasis added). Applicant has also listed the limitations that supposedly support the above alleged technological improvement (see pages 18 to 19 of the current argument).
However, except for the attempt made to summarize some parts from the specification, Applicant fails to demonstrate whether the specification is describing any feature—or any combination of features—that supposedly provides a technological improvement over the relevant existing technology. For instance, the first point that Applicant identified from the specification states that “the usefulness and quality of any volumetric video is dependent on how many directional videos are considered and their respective quality of video”; however, this has nothing to do with technological improvement. This is because the part above is merely indicating the need to have several high-quality directional videos. Accordingly, it is essentially requiring one to gather from others—namely the Internet—multiple directional videos that are assumed to be high-quality videos (e.g., videos captured with high resolution and/or high framerate, etc.). In fact, this seems to be the main reason why the objective of the disclosed system/method is indicated as, “[t]e present invention relates generally to the field of data processing . . . for creating educational case study media content based on collecting crowdsourced information” (see [0001], emphasis added). Thus, unlike Applicant’s assertion, the act of selecting—from external sources (the Internet)—various high-quality directional videos does not constitute a technological improvement. In fact, the disclosed system/method does not appear to implement a specific camera to capture the videos needed, let alone a new or an advanced camera system designed for capturing high-quality directional videos.
Of course, the specification also mentions that the usefulness and quality of any volumetric video also depends on the processing engine that generates the volumetric video. Although different processing engines may have different quality ratings, the original specification is still silent regarding the implementation of any new or advanced image/video processing engine, let alone an advanced engine for reconstructing 3D volumetric videos. Instead, it is still relying on techniques/algorithms that are part of the existing computer technology (e.g., see [0053] and [0056], emphasis added),
“. . . content creation program 122 reconstructs a three-dimensional (3D) model of the subject from the synchronized media content. In an embodiment, content creation program 122 utilizes a Structure from Motion (SfM) technique to reconstruct a 3D model of the subject from the synchronized media content. In another embodiment, content creation program 122 utilizes a Multi-View Stereo (MVS) technique to reconstruct a 3D model of the subject from the synchronized media content. In an embodiment, content creation program 122 analyzes one or more frames of the synchronized media content, i.e., the crowdsourced videos, to create a 3D point cloud or mesh”
“ . . . content creation program 122 converts the 3D model with into a volumetric video. In an embodiment, content creation program 122 converts the 3D model with a textured mapping into the volumetric video format. In an embodiment, content creation program 122 utilizes the volumetric video format to store the 3D geometry and the texture information of each frame. The volumetric video is then output to the user as discussed with respect to Figure 2 at step 250”
Thus, it is evident from the excerpts above that the core engine, which appears to be the “content creation program”, is indeed implementing the existing computer technology. In particular, it is part of the existing computer technology (e.g., the existing computer vision and/or photogrammetry technology) to implement the Structure from Motion (SfM) technique and/or the Multi-View Stereo (MVS) technique to construct one or more 3D structures from multiple 2D images. For instance, the Structure from Motion (SfM) technique produces a sparse point cloud (e.g., a skeleton of a captured object) by calculating where the camera was positioned for each image; and it achieves this by determining matching points across the different images. On the other hand, Multi-View Stereo (MVS) technique produces a dense point cloud (e.g., detailed 3D surface model) by analyzing the camera data above (i.e., the camera position that SfM calculated for each image) and calculating depth based on considering every single pixel.
In the instant case, except for presenting generic descriptions regarding the use of such existing techniques to reconstruct a 3D volumetric video, Applicant’s original specification does not provide any new/advanced technique or algorithm that is assumed to be beyond the existing computer technology. Note also that the additional paragraphs that Applicant cited from the specification ([0011] to [0013]) also fail to demonstrate a technological feature (if any)—or a combination of features (if any)—that provides a technological improvement over the relevant existing technology. Instead, the paragraphs above are describing the need to evaluate the appropriateness of media/content items for a given educational case study. In particular, the paragraphs are describing the various factors that one must consider when selecting media/content items from the Internet. Of course, depending on the desired educational case study, the disclosed system/method may select specific content items from the Internet based on specific parameters—such as: the topic of the case study, the level of criticality of the case study, the geographical boundary that the case study is covering, the duration of the case study, etc. ([0037] of the specification). However, such selection of specific content items from the Internet, based on one or more parameters that are specific to the case study, does not constitute a technological improvement. This is once again because the underlying technology, which the currently claimed (and the originally disclosed) system/method is implementing to reconstruct a 3D volumetric video (from a plurality of directional videos), is still the existing computer/network technology.
Consequently, neither the current claims nor the original disclosure as a whole supports Applicant’s conclusory assertion regarding the alleged “improvements in the technical field of image-processing and geometric-reconstruction operations to transform synchronized two-dimensional video frames into a textured, depth-resolved, frame-by-frame 3D representation” (emphasis added). Of course, given the lack of technological improvement per the claimed—and the disclosed—system/method, none of the current claims—when considered as a whole—integrates the abstract idea into a patent-eligible practical application.
Thirdly, regarding Step 2B, Applicant is asserting that “amended claim 1, as a whole, includes additional elements that amount to significantly more than the alleged judicial exception under step 2B . . . claim 1 as a whole includes additional elements that amount to significantly more than the alleged judicial exception, because the claim is directed to improvements in the technical field of image-processing and geometric-reconstruction operations to transform synchronized two-dimensional video frames into a textured, depth-resolved, frame-by-frame 3D representation. Paragraph 2 of the specification describes the technical problem by reciting that ‘the usefulness and quality of any volumetric video is dependent on how many directional videos are considered and their respective quality of video, and the processing engine which generates the volumetric video.’ Paragraphs 11-13 of the specification, for example, describe a technical solution by disclosing that ‘in obtaining content for a volumetric video creation, crowdsource information gathering is an effective way of gathering input . . . advantages are obtained by performing a comparative evaluation of crowdsourced media content based at least on quality (e.g., pixel density, stable frames, zoom level) and the duration, and select which media content is to be considered for the case study creation . . . the specification discloses a technical solution that improves input selection for volumetric-video creation by evaluating video quality, duration, coverage, capture direction, and closed-loop suitability to identify technically usable input sets” (emphasis added). Here also Applicant has listed the limitations that supposedly achieve the alleged technological improvement (see pages 21 to 23 of the current argument).
However, except for simply repeating the same argument presented with respect to Prong Two of Step 2A, Applicant does not appear to provide a new rationale (if any) to substantiate the alleged eligibility of the claims. Thus, the Office directs Applicant’s attention to the analysis presented above regarding Prong Two since the same analysis applies to Applicant’s arguments directed to Step 2B. In particular, Applicant still fails to demonstrate where the claimed (or the disclosed) system/method is implementing any technological feature—or any combination of technological features—that amounts to an inventive concept. It is worth noting that an inventive concept (if any) is shown if any of the claims is directed to a non-conventional and non-generic arrangement of the additional elements. In contrast, given the currently claimed and originally disclosed system/method, each of the current claims is directed to the conventional and generic arrangement of the additional elements. This is again because the claimed (and the originally disclosed) system/method is relying on the conventional computer/network technology—merely as a tool—to facilitate an abstract idea—such as, customizing educational content based on the analysis of one or more requirements specified for the educational content (see above the findings presented under Prong One of Step 2A).
Of course, the lack of an inventive concept is also evident given the lack of technological improvement per the claimed—and the disclosed—system/method. In particular, similar to the case of Prong Two of Step 2A, Step 2B also evaluates whether the claim is providing a technological improvement in order to determine whether the claim is implementing an inventive concept (see MPEP 2106.05(a), emphasis added),
While improvements were evaluated in Alice Corp. as relevant to the search for an inventive concept (Step 2B), several decisions of the Federal Circuit have also evaluated this consideration when determining whether a claim was directed to an abstract idea (Step 2A). See, e.g., Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016); McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-16, 120 USPQ2d 1091, 1102-03 (Fed. Cir. 2016) . . . Thus, an examiner should evaluate whether a claim contains an improvement to the functioning of a computer or to any other technology or technical field at Step 2A Prong Two and Step 2B, as well as when considering whether the claim has such self-evident eligibility that it qualifies for the streamlined analysis.
Accordingly, given the lack of technological improvement, along with the conventional and generic arrangement of the additional elements, none of the current claims—when considered as a whole—implements an inventive concept that amounts to “significantly more” than an abstract idea.
It is further worth noting that the analysis presented above applies to each of the current claims.
Thus, at least for the reasons discussed above, the Office concludes that the current claims fail to comply with section §101.
Prior Art
● Similar to the point made in the previous office action, when each of the current claims is considered as a whole, the prior art does not teach or suggest the current claims (regarding the state of the prior art, see the office-action dated 05/21/2025).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRUK A GEBREMICHAEL whose telephone number is (571) 270-3079. The examiner can normally be reached from 7:00 AM - 3:00 PM.
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/BRUK A GEBREMICHAEL/Primary Examiner, Art Unit 3715
