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 .
Response to filed Amendments
Applicant’s Amendments/Remarks filed on 02/16/2026 have been received and made of record.
Claims 1, 8, and 15 have been amended.
Claims 10, and 20 have been cancelled.
New claim 21 has been added.
Claims 1-9, 11-19, and 21 are currently pending.
Please refer to the action below.
Examiner Notes
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. However, the claimed subject matter, not the specification, is the measure of the invention.
Response to Remarks/Arguments
Applicants’ arguments of 02/16/2026, corresponding to pages 7-9 pertaining to the prior arts of record of Aliakseyeu and the claimed limitations of the amended independent claims 1, 8, and 15, have been considered, but they are moot in light of the new ground of rejection.
Applicant arguments regarding the prior art of Alrod of pages 7-9 regarding the current amended independent claims 1, 8, and 15 and/or the newly filed dependent claim 21 citing “Applicant notes that the teachings of Alrod do not teach the limitations of amended claims 1, 8, and 15. For example, while page 4 of the Office Action alleges that Alrod's "target mean color" for participant faces (see Alrod, paragraphs 23 and 86) is mapped to "lighting goal," Applicant asserts that the "target mean color" is not "determined by an artificial intelligence model" as in claim 1, is not determined "based on lighting features within a reference video stream" as in claim 8, and is not determined "based on the scene in the video stream, wherein the lighting goal is based on a context of the scene" as in claim 15. Alrod only discusses the "target mean color" in paragraphs 23 and 86 and does not provide any information regarding how the "target mean color" determined to be applied. Thus, the newly introduced limitations of claims 1, 8, and 15 clearly overcome Alrod”; have been considered, however, these newly added claimed amendments and remarks are moot in light of the new ground of rejections.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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) 1-9, 11-19, and 21 is/are rejected under 35 U.S.C. 103 as obvious over Alrod et al. (US 20170324933, previously cited), in view of Kim et al. (KR 2021/0147537, A1).
Regarding claim 1, Alrod teaches a method (at least the Abstract and para. 0079 teaches at least a smart controlled light system employing the light controller of at least para. 0011 to control and adjust light features),
the method comprising:
identifying a lighting system (identifying and control in at least para. 0021-0023, 0028, and 0086 one or more lighting elements and lighting configuration further indicative of said lighting system according to detected user participant faces in a video scene);
determining a lighting goal (the system further teaches in at least the Abstract and para. 0079 at least a smart controlled light system employing the light controller of at least para. 0011 to control and adjust light features according to at least para. 0021-0023, 0028 and 0086 a target mean color as a lighting goal based on video feature contents of for the participant faces detected in the meeting video);
analyzing a scene in a video stream, wherein one or more lighting features of the video stream are illuminated by the lighting system (analyze further in at least para. 0023, 0028 and 0086 said scene in a video stream, wherein one or more lighting properties or features of the video stream are illuminated by the lighting system):
comparing at least one lighting feature of the scene to the lighting goal (further comparing the lighting properties of further para. 0023, 0028 and 0086 to the target mean color indicative of the lighting goal for the one or more participant faces or facial features of those in the meeting video); and
in response to determining the lighting goal is not satisfied, adjusting the lighting system according to the lighting goal (adjusting further in at least para. 0086 in response to determining the lighting target goal mean is not satisfied, said lighting system according to the lighting goal);
repeating the analyzing and the comparing through one or more iterations (the system further notes “varying the lighting element(s) properties (e.g., on/off state, color, intensity, brightness, etc.) as well as exposure of the image capture device until one or more of the detected face images is approximately equal to a target mean color for the participant face or facial feature (e.g., skin tone)” further insinuating the system repeating said analyzing and said comparing through one or more implied iterations).
Alrod teaches in at least para. 0011-0013, 0021-0023 and 0086 the claimed invention except for the above lined-out items such as wherein said lighting goal is determined by an artificial intelligence model.
Kim teaches in the disclosure matching, using an artificial intelligence model, currently played movie scene features with ambient light control effects scene such as “the lighting control device 110 includes an artificial intelligence module. As an embodiment, the artificial intelligence module can set the color, illuminance, and number of blinking lights matching the movie being played by learning information about the genre of the movie input to the lighting control device. For example, the genre of a movie may be learned by analyzing the color distribution of a poster of a movie or a specific frame in a time period corresponding to a climax of a running time”, further insinuates said intelligence model capably setting or determining the lighting goal according to a detected specific frame/scene of a movie being played and watched by the user, the model as understood may iteratively or continuously adjusts the lighting system according to the lighting goal and detected movie frame/scene of a movie being played and watched by the user. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Alrod in in view of Kim to include wherein said wherein said lighting goal is determined by an artificial intelligence model, as discussed above, as Alrod in in view of Kim are in the same field of endeavor of employing a smart lighting control methods and systems for controlling and adjusting light feature effects associated with a video scene according to a lighting goal, Kim’s combination of artificial intelligence controlled lighting coupled and matched with played/streaming video scenes complements the smart lighting control methods and systems of Alrod, in the sense that said combination of artificial intelligence controlled lighting coupled and matched with played/streaming video scenes of Kim when combined with the smart lighting control methods and systems of Alrod further enables continuous and iterative adjustment of the lighting system based on realtime video scenes or contents according to the said lighting goal wherein ultimately realizing a high quality user video conference experience according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 2 (according to claim 1), Alrod further teaches wherein the video stream is part of an internet meeting (the meeting of at least para. 0086 further supported by para. 0001 further comprises the video stream as part of at least an internet meeting).
Regarding claim 3 (according to claim 1), Alrod further teaches wherein the lighting goal includes a reference to a target video stream (lighting target color goal of at least para. 0086 and 0023 further includes a reference to a target video meeting stream).
Regarding claim 4 (according to claim 1), Alrod further teaches wherein evaluating the scene includes evaluating a sequence of multiple frames in the scene (evaluated meeting video session streams of further para. 0023 and 0086 further entails inherently evaluating scenes of at least para. 0044 further including evaluating a sequence of multiple video frames in the scene).
Regarding claim 5 (according to claim 1), Alrod further teaches wherein adjusting includes reverting a previous adjustment that did not bring the scene closer to the lighting goal (adjusting of further para. 0086 further comprises in a case reverting a previous adjustment that did not bring the scene closer to the target color lighting goal).
Regarding claim 6 (according to claim 1), Alrod further teaches wherein the repeating further comprises repeating the analyzing and the repeating occurs until the lighting goal is met (the system further notes “varying the lighting element(s) properties (e.g., on/off state, color, intensity, brightness, etc.) as well as exposure of the image capture device until one or more of the detected face images is approximately equal to a target mean color for the participant face or facial feature (e.g., skin tone)” further insinuating the system repeating said analyzing and said comparing through one or more implied iterations).
Regarding claim 7 (according to claim 1), Alrod further implies wherein further comprising: pausing for a pause period wherein adjusting does not occur during the pause period (the adjustment period of at least para. 0086 may obviously comprises at least a period of analyzing and comparing during which the system may obviously pause said adjusting as a case where the adjusting does not occur during the pause period).
Regarding claim 8, Alrod teaches in at least para. 0011 a computer system comprising:
a processor set (any set of one, or more, storage media collectively included in a set of one, or more, storage devices that collectively include machine readable code corresponding to instructions and/or data for performing computer operations specified in a given medium of at least para. 0036-0037 and 0065),
one or more computer-readable storage media (memory 228 of at least para. 0036-0037, and 0065); and program instructions (para. 0036-0037, and 0065); stored on the one or more computer-readable storage media to cause the processor set to perform operations comprising:
identifying a lighting system (identifying and control in at least para. 0021-0023, 0028, and 0086 one or more lighting elements and lighting configuration further indicative of said lighting system according to detected user participant faces in a video scene);
determining a lighting goal (the system further teaches in at least the Abstract and para. 0079 at least a smart controlled light system employing the light controller of at least para. 0011 to control and adjust light features according to at least para. 0021-0023, 0028 and 0086 a target mean color as a lighting goal based on video feature contents of the participant faces detected in the meeting video);
analyzing a scene in a video stream, wherein one or more lighting features of the video stream are illuminated by the lighting system (analyze further in at least para. 0023 and 0086 said scene in a video stream, wherein one or more lighting properties or features of the video stream are illuminated by the lighting system):
comparing at least one lighting feature of the scene to the lighting goal (further comparing the lighting properties of further para. 0023 and 0086 to the target mean color indicative of the lighting goal for the one or more participant faces or facial features of those in the meeting video); and
in response to determining the lighting goal is not satisfied, adjusting the lighting system according to the lighting goal (adjusting further in at least para. 0086 in response to determining the lighting target goal mean is not satisfied, said lighting system according to the lighting goal);
repeating the analyzing and the comparing through one or more iterations (the system further notes “varying the lighting element(s) properties (e.g., on/off state, color, intensity, brightness, etc.) as well as exposure of the image capture device until one or more of the detected face images is approximately equal to a target mean color for the participant face or facial feature (e.g., skin tone)” further insinuating the system repeating said analyzing and said comparing through one or more implied iterations).
Alrod teaches in at least para. 0011-0013, 0021-0023 and 0086 the claimed invention except for the above lined-out items such as wherein determining said lighting goal specifically based on lighting features within a reference video stream.
Kim teaches in the disclosure matching, using an artificial intelligence model, currently played movie scene features with ambient light control effects scene such as “the lighting control device 110 includes an artificial intelligence module. As an embodiment, the artificial intelligence module can set the color, illuminance, and number of blinking lights matching the movie being played by learning information about the genre of the movie input to the lighting control device. For example, the genre of a movie may be learned by analyzing the color distribution of a poster of a movie or a specific frame in a time period corresponding to a climax of a running time”, Kim essentially may learn and set/determine in realtime lighting goals according to a currently played movie scene the user is watching, the system further adapted for analyzing a scene in a video stream, wherein one or more lighting features as implied subsequently are illuminated or adjusted by the lighting system based on the lighting goal corresponding to the streamed/played movie scene. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Alrod in in view of Kim to include wherein determining said lighting goal specifically based on lighting features within a reference video stream, as discussed above, as Alrod in in view of Kim are in the same field of endeavor of employing a smart lighting control methods and systems for controlling and adjusting light feature effects associated with a video scene according to a lighting goal, Kim’s combination of artificial intelligence controlled lighting coupled and matched with played/streaming video scenes complements the smart lighting control methods and systems of Alrod, in the sense that said combination of artificial intelligence controlled lighting coupled and matched with played/streaming video scenes of Kim when combined with the smart lighting control methods and systems of Alrod further enables continuous and iterative adjustment of the lighting system based on realtime video scenes or contents according to the said lighting goal wherein providing personalized lighting control according to context of a streaming video/movie scene, thereby ultimately realizing a high quality user video conference experience according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 9 (according to claim 8), Alrod further teaches wherein the video stream is part of an internet meeting (the meeting of at least para. 0086 further supported by para. 0001 further comprises the video stream as part of at least an internet meeting).
Regarding claim 10 (according to claim 8), Alrod further teaches wherein the lighting goal includes a reference to a target video stream (lighting target color goal of at least para. 0086 and 0023 further includes a reference to a target video meeting stream).
Regarding claim 11 (according to claim 8), Alrod further teaches wherein evaluating the scene includes evaluating a sequence of multiple frames in the scene (evaluated meeting video session streams of further para. 0023 and 0086 further entails inherently evaluating scenes of at least para. 0044 further including evaluating a sequence of multiple video frames in the scene).
Regarding claim 12 (according to claim 8), Alrod further teaches wherein adjusting includes reverting a previous adjustment that did not bring the scene closer to the lighting goal (adjusting of further para. 0086 further comprises in a case reverting a previous adjustment that did not bring the scene closer to the target color lighting goal).
Regarding claim 13 (according to claim 8), Alrod further teaches wherein the repeating further comprises repeating the analyzing and the repeating occurs until the lighting goal is met (the system further notes “varying the lighting element(s) properties (e.g., on/off state, color, intensity, brightness, etc.) as well as exposure of the image capture device until one or more of the detected face images is approximately equal to a target mean color for the participant face or facial feature (e.g., skin tone)” further insinuating the system repeating said analyzing and said comparing through one or more implied iterations).
Regarding claim 14 (according to claim 8), Alrod further implies wherein further comprising: pausing for a pause period wherein adjusting does not occur during the pause period (the adjustment period of at least para. 0086 may obviously comprises at least a period of analyzing and comparing during which the system may obviously pause said adjusting as a case where the adjusting does not occur during the pause period).
Regarding claim 15, Alrod teaches in at least para. 0011 a computer program product (memory 228 of at least para. 0036-0037, and 0065) comprising: one or more computer-readable tangible storage media (para. 0036-0037, and 0065);
and program instructions stored on the one or more tangible storage media to perform operations (para. 0065) comprising:
identifying a lighting system (identifying and control in at least para. 0021-0023, 0028, and 0086 one or more lighting elements and lighting configuration further indicative of said lighting system according to detected user participant faces in a video scene);
analyzing a scene in a video stream, wherein one or more lighting features of the video stream are illuminated by the lighting system (analyze further in at least para. 0023, 0028 and 0086 said scene in a video stream, wherein one or more lighting properties or features of the video stream are illuminated by the lighting system);
determining a lighting goal (the system further teaches in at least the Abstract and para. 0079 at least a smart controlled light system employing the light controller of at least para. 0011 to control and adjust light features according to at least para. 0023, 0028 and 0086 a target mean color as a lighting goal based on video feature contents of for the participant faces detected in the meeting video);
comparing at least one lighting feature of the scene to the lighting goal (further comparing the lighting properties of further para. 0023 and 0086 to the target mean color indicative of the lighting goal for the one or more participant faces or facial features of those in the meeting video); and
in response to determining the lighting goal is not satisfied, adjusting the lighting system according to the lighting goal (adjusting further in at least para. 0086 in response to determining the lighting target goal mean is not satisfied, said lighting system according to the lighting goal);
repeating the analyzing and the comparing through one or more iterations (the system further notes “varying the lighting element(s) properties (e.g., on/off state, color, intensity, brightness, etc.) as well as exposure of the image capture device until one or more of the detected face images is approximately equal to a target mean color for the participant face or facial feature (e.g., skin tone)” further insinuating the system repeating said analyzing and said comparing through one or more implied iterations).
Alrod teaches in at least para. 0011-0013, 0021-0023 and 0086 the claimed invention except for the above lined-out items such as wherein determining said lighting goal specifically based on the scene in the video stream, wherein the lighting goal is based on a context of the scene.
Kim teaches in the disclosure matching, using an artificial intelligence model, currently played movie scene features with ambient light control effects scene such as “the lighting control device 110 includes an artificial intelligence module. As an embodiment, the artificial intelligence module can set the color, illuminance, and number of blinking lights matching the movie being played by learning information about the genre of the movie input to the lighting control device. For example, the genre of a movie may be learned by analyzing the color distribution of a poster of a movie or a specific frame in a time period corresponding to a climax of a running time”, Kim essentially may learn and set/determine in realtime lighting goals according to a currently played movie scene and/or based on a context of the movie scene the user is watching, the system further adapted for analyzing a scene in a video stream, wherein one or more lighting features as implied subsequently are illuminated or adjusted by the lighting system based on the lighting goal corresponding to the streamed/played movie scene. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Alrod in in view of Kim to include wherein determining said lighting goal specifically determining said lighting goal specifically based on the scene in the video stream, wherein the lighting goal is based on a context of the scene as discussed above, as Alrod in in view of Kim are in the same field of endeavor of employing a smart lighting control methods and systems for controlling and adjusting light feature effects associated with a video scene according to a lighting goal, Kim’s combination of artificial intelligence controlled lighting coupled and matched with played/streaming video scenes complements the smart lighting control methods and systems of Alrod, in the sense that said combination of artificial intelligence controlled lighting coupled and matched with played/streaming video scenes of Kim when combined with the smart lighting control methods and systems of Alrod further enables continuous and iterative adjustment of the lighting system based on realtime video scenes or contents according to the said lighting goal wherein providing personalized lighting control according to context of a streaming video/movie scene, thereby ultimately realizing a high quality user video conference experience according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 16 (according to claim 15), Alrod further teaches wherein the video stream is part of an internet meeting (the meeting of at least para. 0086 further supported by para. 0001 further comprises the video stream as part of at least an internet meeting).
Regarding claim 17 (according to claim 15), Alrod further teaches wherein the lighting goal includes a reference to a target video stream (lighting target color goal of at least para. 0086 and 0023 further includes a reference to a target video meeting stream).
Regarding claim 18 (according to claim 15), Alrod further teaches wherein evaluating the scene includes evaluating a sequence of multiple frames in the scene (evaluated meeting video session streams of further para. 0023 and 0086 further entails inherently evaluating scenes of at least para. 0044 further including evaluating a sequence of multiple video frames in the scene).
Regarding claim 19 (according to claim 15), Alrod further teaches wherein adjusting includes reverting a previous adjustment that did not bring the scene closer to the lighting goal (adjusting of further para. 0086 further comprises in a case reverting a previous adjustment that did not bring the scene closer to the target color lighting goal).
Regarding claim 21 (according to claim 1), Alrod is silent regarding wherein the artificial intelligence model is trained on feedback obtained from past iterations of continuous light adjustment.
Kim further teaches at least in the disclosure analyzing the analyzing a scene in a video stream, wherein one or more lighting features of the video stream are illuminated by the lighting system such as (“the genre of a movie may be learned by analyzing the color distribution of a poster of a movie or a specific frame in a time period corresponding to a climax of a running time”….and “can set the color, illuminance, and number of blinking lights matching the movie being played by learning information about the genre of the movie input to the lighting control device” and “Of course, in addition to this, various types of learning data for learning may be used” thereby implying the artificial intelligence model is adapted to be trained by various types of learning data for learning may be used such as obviously by reinforcement learning including at least feedback obtained from past iterations of continuous light adjustment. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Alrod in in view of Kim to include wherein the artificial intelligence model is trained on feedback obtained from past iterations of continuous light adjustment, as discussed above, as Alrod in in view of Kim are in the same field of endeavor of employing a smart lighting control methods and systems for controlling and adjusting light feature effects associated with a video scene according to a lighting goal, Kim’s combination of artificial intelligence controlled lighting corresponding to feedback obtained from past iterations of continuous light adjustment coupled and matched with played/streaming video scenes complements the smart lighting control methods and systems of Alrod, in the sense that said combination of artificial intelligence controlled lighting coupled and matched with played/streaming video scenes of Kim when combined with the smart lighting control methods and systems of Alrod further enables continuous and iterative adjustment of the lighting system based on realtime video scenes or contents according to the said lighting goal wherein providing personalized lighting control according to context of a streaming video/movie scene, thereby ultimately realizing a high quality user video conference experience according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARCELLUS AUGUSTIN whose telephone number is (571)270-3384. The examiner can normally be reached 9 AM- 5 PM.
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/MARCELLUS J AUGUSTIN/Primary Examiner, Art Unit 2682 04/17/2026
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