DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This office action is in response to arguments and amendments entered on February 26, 2026 for the patent application 18/368,867 originally filed on September 15, 2023. Claims 1-6, 11, 12, 14, 16, 17 and 20 are amended. Claims 10 and 13 are canceled. Claims 21 and 22 are new. Claims 1-9, 11, 12, and 14-22 remain pending. The first office action of November 26, 2025 is fully incorporated by reference into this office action.
Information Disclosure Statement
The Information Disclosure Statement filed on February 26, 2026 has been considered. An initialed copy of the Form 1449 is enclosed herewith.
Response to Amendment
Applicant’s amendments to the claims have been noted by the Examiner.
The amendments are sufficient to overcome the majority of outstanding 35 USC 112(b) rejections. However, a few issues remain, as set forth below.
The Applicant’s amendments are sufficient to overcome the outstanding 35 USC 101 rejections, as they are now directed to specific types of data processing for AR devices.
Applicant’s amendments are sufficient to overcome the prior art rejections under 35 USC 102 and 35 USC 103. However, new rejections are applied to the claims under 35 USC 103, as set forth below.
Drawings
The drawings filed September 15, 2023 are acknowledged and accepted by the Examiner. All outstanding objections to the drawings are withdrawn.
Claim Rejections - 35 USC § 112
Claims rejected under § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-9, 11, 12, and 14-22 are rejected under 35 U.S.C. 112(a), as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Claim 1, and substantially similar limitations in claim 11, recites limitations for compressing class action data, described in detail in instant specification paragraph [0027]. However, the instant disclosure does not support the new limitations introduced by amendment providing details as to how the class action data is compressed. The new limitations are not adequately described in the specification as originally filed and forms the basis of the rejection. Specifically, there is no mention in Applicants’ disclosure of “compressible portions,” “portion differences,” “reference portions,” or “a redundancy reduction algorithm.” As such, the claimed subject matter is not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention. Therefore, claims 1 and 11 are deemed to recite new matter and is properly rejected under 35 U.S.C. §112(a). Claims 2-9 and 21 are also rejected under 35 U.S.C. §112(a) based on their respective dependencies to claim 1. Claims 12, 14-20, and 22 are also rejected under 35 U.S.C. §112(a) based on their respective dependencies to claim 11.
Claim 21, and substantially similar limitations in claim 22, recites “spatial registration data”. However, the instant disclosure does not contain any mention of “spatial registration data”. The new limitation is not adequately described in the specification as originally filed and forms the basis of the rejection. As such, the claimed subject matter is not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention. Therefore, claims 21 and 22 are deemed to recite new matter and is properly rejected under 35 U.S.C. §112(a).
Claims rejected under § 112(b)
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.
Claims 1-9 and 21 are rejected under 35 U.S.C. § 112(b), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 1, and substantially similar limitations in claims 2-6 and 21, recites the limitation “the at least a processor.” The limitation is originally introduced in claim 1. As such, the subsequent limitations are either (1) not following antecedent basis (i.e. “the at least [[a]] the processor”); or (2) are intended to be new limitations which ambiguously conflict with the previous limitation of claim 1. Therefore, claims 1-6 and 21 are rejected under 35 U.S.C. § 112(b), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Claims 2-9 and 21 are also rejected under 35 U.S.C. § 112(b), based on their respective dependencies to claim 1. Claim 3 is also rejected under 35 U.S.C. § 112(b), based on its dependency to claim 2.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 9, 11, 12, 14-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Plummer (US 2023/0128721) in view of Mammou et al. (hereinafter “Mammou,” US 2017/0302918).
Regarding claim 1, and substantially similar limitations in claim 11, Plummer discloses an apparatus for fitness class generation (Plummer Abstract, “a method to generate a custom video workout program”), the apparatus comprising:
…
a computing device communicatively connected to the AR device (Plummer [0121], “the computer system 1300 may be part of any of the video cameras 106,” for specifically “AR” device, see Mammou below), wherein the computing device comprises:
at least a processor (Plummer [0122], “The computer system 1300 may include a processor 1302”); and
a memory communicatively connected to the at least processor (Plummer [0122], “The computer system 1300 may include a processor 1302, a memory 1304”), the memory containing instructions configuring the at least processor to:
receive class action data from the AR device (Plummer [0115], “recording a video of a trainer performing a workout. For example, action 1202 may include a video camera 106 recording video 1002 that includes a trainer 108 performing a workout or is combined with video of a trainer 108 performing a workout and/or the local server 116 and/or the remote server 112 storing video 1002 of the trainer 108 performing the workout. The video 1002 may be of or include an event that may be unknown or well-known, such as a well-known running, biking, rowing, or other race or event. The video 1002 and the workout may be relatively long, e.g., long enough that many users may desire to experience it in smaller segments,” for specifically “AR” device, see Mammou below);
…
analyze the compressed class action data using an action module (Plummer [0089], “the segments 308 of FIG. 3 may be tagged and/or may include metadata or attribute values indicative of attributes of the segment 308 that relate to the user criteria. For example, attribute values of each segment 308 may include one or more values for interests and/or needs the segment 308 relates to or satisfies, one or more values for types of exercise machines (e.g., treadmill, rower machine, stationary bike, etc.) the segment 308 may be executed at, one or more values for an environment or scenery depicted in the segment 308, one or more values for an objective, purpose, or goal of the segment 308, one or more values for educational content included in the segment 308, one or more values for trainers featured in the segment 308, or other values for other attributes,” the segments must be analyzed in order to assign attributes to them);
determine a class action data modifier based on an analysis of the class action data (Plummer [0089], “When selecting segments 308 to include in a given custom video workout program 304, values of the user criteria may be compared to and/or matched against attribute values of the segments 308. In some embodiments, segments 308 that include the highest match scores, that exceed a threshold score, or that satisfy some other criteria may be selected as the segments 308 for inclusion in a corresponding one of the custom video workout programs 304,” using match scores and user criteria to determine how to modify the original workout video to generate a new custom workout video); and
generate fitness class content as a function of the class action data modifier (see Plummer Fig. 3 and paragraph [0090], “Each of the video frames 500 may be of a different one of multiple segments of video workout programs that were selected based on user criteria of a given user and spliced together to form the custom video workout program. For example, the video frame 500a may be of one of the segments 308a of the video workout program 302a of FIG. 3, the video frame 500b may be of one of the segments 308b of the video workout program 302b of FIG. 3, and the video frame 500c may be of one of the segments 308c of the video workout program 302c of FIG. 3,” generating a new video workout program).
Plummer does not teach every limitation of an augmented reality (AR) device; and … compress the class action data, wherein compressing the class action data comprises: identifying one or more compressible portions as a function of the class action data; determining portion differences as a function of one or more reference portions and the one or more compressible portions; encoding the portion differences to form encoded data; and generating, by a redundancy reduction algorithm, compressed class action data as a function of the encoded data.
However, Mammou discloses an augmented reality (AR) device; and … compress the class action data, wherein compressing the class action data comprises: identifying one or more compressible portions as a function of the class action data; determining portion differences as a function of one or more reference portions and the one or more compressible portions; encoding the portion differences to form encoded data; and generating, by a redundancy reduction algorithm, compressed class action data as a function of the encoded data (Mammou [0051], “Images may be superimposed on a real-world view, as part of an augmented reality or mixed reality display.” for AR device; also Mammou [0094], “Video compression uses different coding techniques or coding modes to reduce redundancy in video data. Because the difference between frames is typically the result of either movement of a camera or movement of an object in the frame, motion searching is employed to facilitate the encoding of the video data for video compression. Motion searching attempts to predict a current frame in a video stream based on previous and/or future frames by accounting for motion of a camera and/or objects in the video. The prediction includes estimating the motion of portions (e.g., macroblocks) between frames (e.g., between current frame to be encoded and a previously encoded reference frame) by searching for matching portions around co-located portions in the reference frame (i.e., portions at the same location in the reference frame). While motion searching may facilitate reducing the number of bits to be encoded, the process is computationally expensive and resource extensive.”).
Mammou is analogous to Plummer, as both are drawn to the art of video processing. It would be obvious to try by one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method as taught by Plummer, to include an augmented reality (AR) device; and … compress the class action data, wherein compressing the class action data comprises: identifying one or more compressible portions as a function of the class action data; determining portion differences as a function of one or more reference portions and the one or more compressible portions; encoding the portion differences to form encoded data; and generating, by a redundancy reduction algorithm, compressed class action data as a function of the encoded data, as taught by Mammou, in order to improve encoding efficiency of video while decreasing the memory bandwidth requirements and processing time (Mammou [0001]). Doing so is a predictable solution that one of ordinary skill in the art could have pursued with a reasonable expectation of success.
Regarding claim 2, and substantially similar limitations in claim 12, Plummer in view of Mammou discloses a display, wherein the memory contains instructions configuring the at least processor to transmit fitness class content to the display, wherein the display is configured to provide a visual interface, wherein the display is configured to transmit visual interface interaction data to the computing device (Plummer Fig. 4A and paragraph [0083], “FIG. 4A is a screenshot of an example user interface (UI) 400 of an interactive fitness platform that may be used to collect user criteria from an online fitness profile of a user for customizing video workout programs. The UI 400 may be presented to the user on, e.g., the tablet 124 or the console 122 of FIG. 1 or other display device. The interactive fitness platform may include or have access to video workout programs, such as the video workout program library 306 and/or the video workout programs 302 of FIG. 3.”).
Regarding claim 3, and substantially similar limitations in claim 14, Plummer in view of Mammou discloses wherein the memory contains instructions configuring the at least processor to generate fitness class content as a function of the class action data modifier and the visual interface interaction data (Plummer [0111], “the user may provide input to combine two or more of the video workout programs 302 into a custom video workout program 304. In response to the input, the video segments 1004 of the two or more video workout programs 302 may be spliced together without any intervening warmups 1006 or cooldowns 1008 between a first one of the video segments 1004 and a last one of the video segments 1004 of the two or more video workout programs 302,” user input used in creating custom workout video; also Plummer [0133], “two or more segments may be spliced together to generate a custom video workout program based on user criteria and according to the workout templates and/or intensities of the segments”).
Regarding claim 4, and substantially similar limitations in claim 15, Plummer in view of Mammou discloses a display, wherein the memory contains instructions configuring the at least processor to transmit fitness class content to the display, wherein the memory contains instructions configuring the at least processor to receive class action data on a live fitness class from the video capture device, wherein the display is capable of being viewed by the live fitness class (Plummer [0057], “where the video or the combined video is being produced to be utilized as a live video workout program, the producer may input the exercise machine control commands using the computer 114 synchronously or substantially synchronously with the video camera 106b, 106c capturing the video of the trainer 108a, 108b performing the workout (e.g., during a live event) and/or with generation of the combined video when one is generated. In this example, the producer may also give corresponding instructions to the trainer 108a, 108b, such as through an earpiece worn by the trainer 108a, 108b, to help the trainer 108a, 108b and the producer be in sync following a common script or plan for the workout.”).
Regarding claim 5, and substantially similar limitations in claim 16, Plummer in view of Mammou discloses a storage device, wherein the memory contains instructions configuring the at least processor to receive class action data from the storage device (Plummer [0078], “The segments 308 may be stored in a segment library 310, which may be stored on or accessible to the remote server”).
Regarding claim 6, and substantially similar limitations in claim 17, Plummer in view of Mammou discloses wherein the memory contains instructions configuring the at least processor to generate fitness class content as a function of the class action data modifier and the class action data (Plummer [0047], “split existing video workout programs into segments and combine the segments in new combinations to generate custom video workout programs. While the segments themselves may not be new, each new combination of segments may feel like a new video workout program to users which may reduce the boredom and/or complacency that users otherwise experience when repeating the same video workout program. The segments may have various attributes and may be combined based on user criteria.”).
Regarding claim 9, and substantially similar limitations in claim 20, Plummer in view of Mammou discloses wherein determining a class action data modifier based on an analysis of the class action data utilizes a machine learning model trained on past class action data (Plummer [0128], “the application 1314 may include a machine learning model. In general, the machine learning model may be trained based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. The machine learning model may employ machine learning algorithms, and may be supervised or unsupervised. The machine learning model may be trained over time to become more and more accurate. The machine learning model may be trained, for example, using a Decision Tree, Naive Bayes Classifier, K-Nearest Neighbors, Support Vector Machines, or Artificial Neural Networks. The machine learning model may be employed in any of the methods herein to perform actions with increasing effectiveness and accuracy over time, as the machine learning model learns and is periodically retrained to make more accurate predictions or decisions.”).
Claims 7 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Plummer in view Mammou, and in further view of Zia et al. (hereinafter “Zia,” US 11,017,690).
Regarding claim 7, and substantially similar limitations in claim 18, Plummer in view of Mammou does not teach wherein the action module is configured to categorize a pose depicted by the class action data using a computer vision model.
However, Zia discloses wherein the action module is configured to categorize a pose depicted by the class action data using a computer vision model (Zia col. 8 line 45 through col. 9 line 7, “The task evaluation subsystem is also configured to identify a type of activity step executed by the one or more actors… The task evaluation subsystem is capable of performing action classification, spatial-temporal video alignment, synthetic data augmentation, visual object discovery, detection, tracking, fine-grained categorization, worker pose estimation, motion tracking, and semantically-grounded 3D reconstruction into a novel visual programming paradigm that generates neuro-symbolic code to confirm the correct performance of an activity by the one or more actors in the live video and searches for improvements to the original process itself.”).
Zia is analogous to Plummer in view of Mammou, as both are drawn to the art of video analysis. It would be obvious to try by one of ordinary skill in the art at the time of filing to have modified the method as taught by Plummer in view of Mammou, to include wherein the action module is configured to categorize a pose depicted by the class action data using a computer vision model, as taught by Zia, in order to enable enhancement of the activity model based on feedback provided upon evaluation of the video (Zia col. 2 lines 45-54). Doing so is a predictable solution that one of ordinary skill in the art could have pursued with a reasonable expectation of success.
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Plummer in view of Mammou, and in further view of Putnam et al. (hereinafter “Putnam,” US 2021/0342952).
Regarding claim 8, and substantially similar limitations in claim 19, Plummer in view of Mammou does not teach wherein the action module is configured to interpret speech using a language model.
However, Putnam discloses wherein the action module is configured to interpret speech using a language model (Putnam [0291], “In some cases, the GUI may also enable at least a portion of the users within a group to join a particular fitness class together… The mirror 100 may be able to recognize and distinguish different users based on video and/or imagery acquired via the camera 130 and analyzed as described above for user recognition and tracking, based on voice input acquired via the microphone 160 and analyzed as described above for voice recognition, via each user expressly identifying themselves (e.g., by logging into their profile via the same mirror 100), and/or the like.”).
Putnam is analogous to Plummer in view of Mammou, as both are drawn to the art of interactive exercise systems. It would be obvious to try by one of ordinary skill in the art at the time of filing to have modified the method as taught by Plummer in view of Mammou, to include wherein the action module is configured to interpret speech using a language model, as taught by Putnam, because it uses a known technique of speech interpretation to improve similar interactive exercise devices in the same way. Doing so is a predictable solution that one of ordinary skill in the art could have pursued with a reasonable expectation of success.
Claims 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Plummer in view of Mammou, and in further view of Russell et al. (hereinafter “Russell,” US 6,697,072).
Plummer in view of Mammou does not explicitly teach every limitation of wherein the action module comprises a computer vision model comprising a user avatar registered to a view feed, and wherein the at least a processor is further configured to: determine the class action data modifier based on an analysis of the class action data and spatial registration data, wherein the spatial registration data is associated with the user avatar within a field coordinate system of the view feed; and generate the fitness class content as a function of the class action data modifier, and the spatial registration data.
However, Russell discloses wherein the action module comprises a computer vision model comprising a user avatar registered to a view feed, and wherein the at least a processor is further configured to: determine the class action data modifier based on an analysis of the class action data and spatial registration data, wherein the spatial registration data is associated with the user avatar within a field coordinate system of the view feed; and generate the fitness class content as a function of the class action data modifier, and the spatial registration data (see Russell claim 1, “A method for controlling an avatar using computer vision, said method comprising: receiving a video stream representing a background and a foreground; segmenting a user in said foreground from said background; tracking a head position of the user to produce effector information; performing coordinate conversion on the effector information; performing inverse kinematics on the effector inforamtion; and controlling said avatar based on said effector information”; also Russell col. 2 lines 46-57, “Computer vision technology system 140 processes a video stream received from video camera 130, and produces information necessary to render an avatar 150 on monitor 160.”; also Russell col. 3 lines 1-15, “The effector information may be expressed in any number of coordinates, such as in two- or three-dimensional coordinates. Controller 240 controls an avatar based on the effector information. As such, controller 240 outputs image data 250 for use by, for example, a display”).
Russell is analogous to Plummer in view of Mammou, as both are drawn to the art of video processing. It would be obvious to try by one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method as taught by Plummer in view of Mammou, to include wherein the action module comprises a computer vision model comprising a user avatar registered to a view feed, and wherein the at least a processor is further configured to: determine the class action data modifier based on an analysis of the class action data and spatial registration data, wherein the spatial registration data is associated with the user avatar within a field coordinate system of the view feed; and generate the fitness class content as a function of the class action data modifier, and the spatial registration data, as taught by Russell, in order to allow more natural and direct control of an avatar (Russell col. 1 lines 12-51). Doing so is a predictable solution that one of ordinary skill in the art could have pursued with a reasonable expectation of success.
Response to Arguments
The Applicant’s arguments filed on February 26, 2026 have been fully considered and addressed below.
Applicant’s arguments with respect to the claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Stephen Alvesteffer whose telephone number is (571)272-8680. The examiner can normally be reached M-F 8:00-6:00.
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/SA/Examiner, Art Unit 3715
/PETER S VASAT/Supervisory Patent Examiner, Art Unit 3715
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