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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 5/2/24 and 7/25/24 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “processing devices” in claim 21.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 5-9 and 26-28 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites the limitation “the concatenated set of textual embeddings”. There is insufficient antecedent basis for this limitation in the claim. According to claim 4, there is an “extracted video embedding concatenated with the set of textual embeddings”. However, this appears to be a distinct element referring to a concatenated set of video embeddings and textual embeddings rather than a “concatenated set of textual embeddings”. In view of the context of claim 5, this limitation is being interpreted as “the set of textual embeddings”.
Claim 25 is rejected as analogous to claim 5, and claims 6, 7, 26, and 27 are rejected as dependent on these claims.
Claim 8 recites the following antecedence issues: “the one or more media items”, “the given data”, and “the video frame”, which are all being interpreted as new elements.
Claim 28 is rejected as analogous to claim 8.
Claim 9 recites “the indication”, which lacks antecedence and is being interpreted as “an indication”.
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 1-5, 8-11, 20-25, and 28 are rejected under 35 U.S.C. 101 .
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of determining a segment of a media item that depicts an event, without significantly more.
The claim recites: “A method comprising:
obtaining a set of video embeddings that represents features of one or more video frames of a media item;
obtaining a set of textual embeddings corresponding to an event associated with the media item;
generating fused video-textual data based on the obtained set of video embeddings and the obtained set of textual embeddings, wherein the fused video-textual data indicates features of the one or more video frames of the media item and textual data pertaining to the media item;
providing the fused video-textual data as an input to an artificial intelligence (Al) model trained to perform a plurality of video localization tasks with respect to media items of a platform;
obtaining one or more outputs of the Al model; and
determine, based on the one or more outputs of the Al model, a segment of the media item that depicts the event.”
The limitations, as drafted, are processes that, under their broadest reasonable interpretation, cover performance of the limitation in the mind. A person can combine embeddings and use them to determine outputs, then further determine media item segments containing the event based on the outputs. The two obtaining limitations amount to insignificant, extra-solution activity (data collection). The generation of fused video-textual data can also be interpreted as mathematical calculations, such as adding vectors/matrices.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional element of an AI model, which is generically recited and amounts to any AI model able to take an embedding and produce an output. Accordingly, the 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 claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are recited at a high-level of generality. It is therefore a judicial exception that is not integrated into a practical application, and does not include additional elements that are sufficient to amount to significantly more than the judicial exception. This claim is not patent eligible.
Claims 2-3 are rejected under 35 U.S.C. 101 because the claimed invention is directed to encoding videos and images and predicting correspondences (mental processes), using generically recited encoders and AI models. The claims are not patent eligible.
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to extracting an embedding, concatenating, and updating a dataset (mental processes and mathematical calculations). The claim is not patent eligible.
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to obtaining frame tokens reflecting correspondences (mental process) base, in part, on a generically recited transformer encoder. The claim is not patent eligible.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to the mental process of predicting a correspondence between a media item and a text embedding. The claim is not patent eligible.
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention describes receiving a request and providing an answer (mental processes) using generically recited additional element of a client device. The claim is not patent eligible.
Claims 10-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to the mental processes of determining confidence levels based on criteria. The claims are not patent eligible.
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed a generically recited non-transitory computer readable storage medium (routine and well known) configured to perform the abstract idea of claim 1. The claim is not patent eligible.
Claims 21-25 and 28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a generically recited system with a memory and processor (routine and well-known components) for the performance of the abstract idea of claims 1-5 and 8. The claims are not patent eligible.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-5, 8, 20-25, and 28 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lei (QVHIGHLIGHTS: Detecting Moments and Highlights in Videos via Natural Language Queries).
Regarding claim 1, Lei teaches “A method comprising:
“obtaining a set of video embeddings that represents features of one or more video frames of a media item; obtaining a set of textual embeddings corresponding to an event associated with the media item;” (Lei, Section 4.1 Subsection “Input Representations” pasted below, note Ev and Eq. Also see Figure 3 which shows that the text embeddings correspond to an event associated with the media item. This is similarly shown in Figure 5, wherein the text for embedding corresponds to a media item event.)
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“generating fused video-textual data based on the obtained set of video embeddings and the obtained set of textual embeddings, wherein the fused video-textual data indicates features of the one or more video frames of the media item and textual data pertaining to the media item;” (Lei, Section 4.1 Subsection “Transformer encoder-decoder” pasted below. Note that Eenc is mapped to the fused video-textual data, which is based on the Einput (concatenated video and textual embeddings obtained in the previous limitation). Also see Figure 3.)
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“providing the fused video-textual data as an input to an artificial intelligence (Al) model trained to perform a plurality of video localization tasks with respect to media items of a platform; obtaining one or more outputs of the Al model; and determine, based on the one or more outputs of the Al model, a segment of the media item that depicts the event.” (Lei, Figures 3 and 5, and Section 4.1 Subsection “Prediction heads” pasted below. Note that the prediction heads are mapped to the AI model, which receives the Eenc (fused video-textual data) as input; the output is mapped to the saliency scores; the saliency scores identify media segments depicting the event as shown in Figure 5, wherein clips (media segments) that depict the event are highlighted.)
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Regarding claim 2, Lei teaches “The method of claim 1, further comprising:
“providing the one or more video frames as an input to an image encoder, wherein the set of video embeddings is obtained based on one or more outputs of the image encoder; and providing textual data corresponding to the event associated with the media item as an input to a text encoder, wherein the set of textual embeddings is obtained based on one or more outputs of the text encoder.” (Lei, Section 4.1 Subsection “Input Representations” pasted below, note Ev and Eq which are generated using respective encoders.)
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Regarding claim 3, Lei teaches “The method of claim 2,”
“wherein the image encoder and the text encoder are components of an additional Al model that is trained to predict a correspondence between given text data and given image data.” (Lei, note the CLIP encoder recited above is mapped to the additional AI model.)
Regarding claim 4, Lei teaches “The method of claim 1,”
“wherein generating the fused video-textual data comprises: extracting, from the obtained set of video embeddings, a video embedding representing features of at least one of the one or more video frames; performing one or more concatenation operations to concatenate the extracted video embedding with the set of textual embeddings; and updating a dataset to include the extracted video embedding concatenated with the set of textual embeddings.” (Lei, Section 4.1 Subsection “Input Representations”, pasted above, and Section 4 introductory Paragraph, pasted below. Each 2 second clip embedding (video embedding representing features of at least one of the one or more video frames) is extracted and evaluated for correspondence to the set of textual embeddings of the natural language query (resulting in the clip-wise saliency score). Accordingly, each 2 second clip embedding is concatenated with the set of textual embeddings in the concatenation step. These are used as an input dataset Einput (claimed dataset) for subsequent processing. This is mathematically supported by dimensions of Ev, Eq, and Einput, as they show a matrix-based concatenation which concatenates respective 2 second clip embeddings with the textual embeddings.)
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Regarding claim 5, Lei teaches “The method of claim 4,”
“further comprising: providing the updated dataset as an input to a transformer encoder;” (Lei, see last sentence of Section 4.1 Subsection “Input Representations”, pasted above.)
“and obtaining, based on one or more outputs of the transformer encoder, a set of frame tokens reflecting a correspondence between a respective video embedding extracted from the set of video embeddings and the concatenated set of textual embeddings. (Lei, Section 4.1 “Subsections “Transformer encoder-decoder” and “Prediction heads”, and Figures 3 and 5. Note that the output of the transformer encoder (Eenc) is used for obtaining the saliency, which amounts to the set of frame tokens claimed, as they indicate a plurality of scores that indicate correspondence between each 2 second clip video embedding and the textual embeddings. See Figures 3 and 5, wherein each clip has a corresponding salience score (frame token).)
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Regarding claim 8, Lei teaches “The method of claim 1,”
“wherein the plurality of video localization tasks comprise at least one of: predicting a correspondence between a segment of the one or more media items and one or more events indicated by one or more textual embeddings of the given data, predicting a set of time stamps indicating the segment of the one or more media items that depicts one or more events indicated by the one or more textual embeddings of the given data, predicting an action pertaining to one or more objects depicted by a video frame of the one or more media items, or predicting a region of the video frame of the one or more media items depicting one or more actions that are of interest to one or more users of a platform. (Lei, Figures 3 and 5 show saliency scores which indicate correspondence between respective segments and the event indicated by the textual query. Note that this maps to the underlined option, but also covers the subsequent option because these segments inherently have time stamps identified by their position in the video sequence.)
Regarding claim 10, Lei teaches “The method of claim 1,”
“wherein the output of the AI model comprises an indication of one or more segments of the media item and, for each of the one or more segments of the media item, a level of confidence that video frames of the respective segment of the media item depicts content corresponding to the event.” (Lei, Figures 3 and 5 show saliency scores for a plurality indicated of segments, wherein the saliency scores assigned to the segments amount to the claimed confidence level.)
Regarding claim 20, claim 20 recites a non-transitory computer readable storage medium storing a program with instructions corresponding to the steps recited in Claim 1. Therefore, the recited programming instructions of this claim are mapped to the analogous steps in the corresponding method claim. Additionally, Lei teaches a non-transitory computer readable storage medium (The machine learning software of Lei is necessarily stored on a non-transitory storage).
Regarding Claims 21-25 and 28, Claims 21-25 and 28 recite a system with memory and a processing device with elements corresponding to the steps recited in Claims 1-5 and 28. Therefore, the recited elements of this claim are mapped to the analogous steps in the corresponding method claim. Additionally, Lei teaches a system with memory and a processing device (The machine learning software of Lei fundamentally requires these elements).
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.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lei in view of Chang (US20200401809A1).
Regarding claim 9, Lei teaches “The method of claim 1,”
“receiving, from a client device connected to a platform, a request for content pertaining to the event;” (Lei, Introduction Paragraph 1, pasted below, in particular the last sentence. The user inputs a query (request), inherently via a device connected to a video platform, as the invention of Lei performs computational processes on a video. The request pertains to locating moments (content) of a specific event (precise moment relevant to the user).)
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While Lei discloses extracting segments that depict the event (see rejection of claim 1), and implies the presentation of these segments to the user (otherwise the invention would serve no purpose if the user gets no response to the query), Lei does not expressly disclose the presentation of the segments via the client device.
Chang expressly discloses providing augmented video content to a user’s client device responsive to a user input on the same client device (Chang, Paragraphs 274 and 497, “The video transformation module 5208 receives the video feeds and the index and may output a video to the GUI module 5202. In embodiments, the video transformation module 5208 is configured to generate augmented video content and/or switch between different video feeds of the same event (e.g., different camera angles of the event). In embodiments, the video transformation module 5208 may overlay one or more GUI elements that receive user selections into the video being output. For example, the video transformation module 5208 may overlay one or more visual selection elements over the video feed currently being output by the GUI module 5202. The visual selection elements may allow a user to view information relating to the event depicted in the video feed, to switch views, or to view a recent highlight. In response to the user providing a command via the user interface of the client device 5100, the video transformation module 5208 may augment the currently displayed video feed with augmentation content, switch the video feed to another video feed, or perform other video transformation related operations.”; “In various embodiments, the individual augmentations may be rendered separately by a server and then transmitted to a client along with suitable temporal and spatial indexing and alignment information. A suitable application on the user's client device may then use the provided temporal and spatial indexing and alignment information to display and/or display the augmentation over, or in conjunction with, the base video.”)
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to perform the media content output to a client device of Chang with respect to the media segment output and client device of Lei.
The motivation for doing so would have been to present the search output to the user. Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Lei with the above teaching of Chang to fully disclose, “and responsive to extracting the indication of the segment of the media item that depicts the event, providing the indicated segment of the media item for presentation via the client device in accordance with the received request.”
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lei in view of Lin (BMN: Boundary-Matching Network for Temporal Action Proposal Generation)
Regarding claim 11, Lei teaches “The method of claim 10,”
Lei does not expressly disclose “wherein the output of the AI model further comprises, for each of the one or more segments of the media item, an additional level of confidence that a duration of the one or more segments satisfies one or more duration criteria associated with a platform.”
Lin discloses an AI model that outputs, for each of one or more video segments, a confidence level that the segment(s) satisfies a duration criteria associated with a platform (Lin, Section 3,3, Paragraph 1, “In this section, we introduce the Boundary-Matching (BM) mechanism to generate confidence scores for densely distributed proposals. First we denote a temporal proposal ϕ as a matching pair of its starting boundary ts and ending boundary te. Then, as shown in Fig 2, the goal of BM mechanism is to generate the two dimensional BM confidence map MC, which is constructed by BM pairs with different starting boundary and temporal duration. In BM confidence map, the value of point MC(i,j) is denoted as the confidence score of proposal ϕi,j with starting boundary ts = tj, duration d = ti and ending boundary te = tj + ti. Thus, we can generate confidence scores for densely distributed proposals via generating BM confidence map.” Figure 1 additionally shows confidence scores for video segments. Note that these confidence scores refer to the satisfying of a duration criterion (likelihood that the segment (proposal) contains the temporal action of interest), which is associated with a platform (Boundary Matching Network, BMN).)
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to calculate confidence scores for segments in accordance with a duration criterion, taught by Lin, with respect to the segments and using the AI model of Lei.
The motivation for doing so would have been to supply an additional level of confirmation for more accurate results. Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Lei with the above teaching of Lin to fully disclose, “wherein the output of the AI model further comprises, for each of the one or more segments of the media item, an additional level of confidence that a duration of the one or more segments satisfies one or more duration criteria associated with a platform.”
Allowable Subject Matter
Claims 6-7 and 26-27 are objected to as being dependent upon a rejected base claim and rejected under 35 USC 112(b), but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and amended to overcome the 35 USC 112(b) rejections.
The following is a statement of reasons for the indication of allowable subject matter: With respect to claims 6 and 26, as well as the respective dependent claims, in addition to other limitations in the claims the Prior Art of Record fails to teach, disclose or render obvious the applicant's invention as claimed, in particular:
Claim 6 (and similarly claim 26) recites: “The method of claim 5, further comprising:
performing one or more sampling operations with respect to the set of frame tokens to obtain, for each of the set of frame tokens, a plurality of sampled frame tokens, wherein each of the plurality of sampled frame tokens has a distinct resolution from other sampled frame tokens of the plurality of frame tokens,
wherein the generated fused video-textual data comprises the plurality of sampled frame tokens obtained for each of the set of frame tokens.”
Lei teaches a computational method for identifying video segments based on a user query based on text and video embeddings. Chang teaches video augmentation according to a user input on a client device. Lin teaches determination of video segments wherein a particular action or event occurs. Shvetsova (Everything at Once– Multi-modal Fusion Transformer for Video Retrieval) teaches fusion of cross-modality embeddings for applications including zero-shot step action localization (labeling video segments based on a list of action steps). Daher (US 20120323897 A1) teaches the extraction of segments from a video for presentation to a user, wherein the extraction is based on a user’s search query. However, none of these references disclose the bolded limitations above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AARON JOSEPH SORRIN whose telephone number is (703)756-1565. The examiner can normally be reached Monday - Friday 9am - 5pm.
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/AARON JOSEPH SORRIN/
Examiner, Art Unit 2672
/SUMATI LEFKOWITZ/Supervisory Patent Examiner, Art Unit 2672
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