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 .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 04/08/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/26/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any combination of references applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 1, 3, 5, 7-12, 14, 16-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Chalom et al. (“Chalom”, US 2016/0284095) in view of Sethia et al. (“Sethia”, US 11,871,104) and further in view of Mikhailiuk et al. (“Mikhailiuk”, US 2025/0077794).
Regarding claim 1, Chalom discloses a client device comprising:
one or more processors (Chalom: processor 710);
one or more media capture devices (Chalom: an image capture device 20, see par. [0013]); and
one or more memory (Chalom: memory 712) configured to cause the one or more processors to:
obtain one or more media specifications of an application (Chalom: see fig. 1A and par. [0013], obtain reference images 16);
provide, as input to at least one generative artificial intelligence model, the one or more media specifications to aggregate one or more capture specifications for capturing media content, wherein the at least one generative artificial intelligence model extracts the one or more capture specifications from the one or more media specifications (Chalom: see fig. 1A and par. [0013], provide, as input to generative artificial intelligence module 10, the reference images 16 to aggregate capture parameters for capturing candidate images 18, wherein the generative artificial intelligence module 10 extracts capturing parameters from the reference images 16),
cause an instance of the media content to be captured by the one or more media capture devices based on applying the one or more capture specifications (Chalom: see fig. 1A and par. [0013]-[0014], cause the candidate images to be captured by the image capture device based on applying the capturing parameters); and
provide the instance of the media content to the application (Chalom: see fig. 1A and par. [0013], provide the candidate images to the training image data 12).
Chalom does not explicitly disclose
obtaining, as output from neural network, a prompt to specify user guidance for adjusting one or more attributes of the media content based on the one or more capture specifications;
outputing, via the client device, the prompt;
cause, in response to outputting the prompt, an instance of the media content to be captured by the one or more media capture devices.
However, Sethia teaches
obtaining, as output from neural network, a prompt to specify user guidance for adjusting one or more attributes of the media content based on the one or more capture specifications (Sethia: see fig. 9 and col. 11, lines 48-53, obtaining, as output from neural network, a prompt 916 to specify user guidance for adjusting posture based on the capture specifications 910);
outputting, via the client device, the prompt (Sethia: see fig. 9, column 31, lines 28-38, outputting, via the client device 100, the prompt 916);
causing, in response to outputting the prompt, an instance of the media content to be captured by the one or more media capture devices (Sethia: see fig. 5, column 21, lines 35-54, causing, in response to outputting the prompt 916, an instance of the media content to be captured by the media capture device 100).
One would have been modified to include artificial intelligence model as taught by Sethia in the apparatus of Chalom to mimic human intelligence.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the teachings of Sethia with the Chalom’s system to include obtaining, as output from neural network, a prompt to specify user guidance for adjusting one or more attributes of the media content based on the one or more capture specifications; outputting, via the client device, the prompt; causing, in response to outputting the prompt, an instance of the media content to be captured by the one or more media capture devices.
Chalom in the combination with Sethia does not explicitly disclose that generative artificial intelligence model including a prompt engineer large language model.
On the other hand, Mikhailiuk teaches that generative artificial intelligence model including a prompt engineer large language model (Mikhailiuk: see par. [0297], wherein the second machine learning model comprises a Large Language Model (LLM); and causing display of the textual response within the interaction function to the first user).
One would have been modified to include LLM as taught by Mikhailiuk in the apparatus of Chalom and Sethia to represents a shift from narrow, task-specific AI to general-purpose foundation models capable of understanding, generating, and reasoning across text, code, and multimodal data.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the teachings of Mikhailiuk with the Chalom and Sethia’s system to include a prompt engineer large language model.
Regarding claim 3, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 1.
Sethia further teaches the prompt includes a text output for display at a user interface of the client device (Sethia: see fig. 9).
The motivation is the same as that of claim 1.
Regarding claim 5, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 1, wherein the one or more processors are further configured to process the instance of the media content based on the one or more capture specifications (Chalom: see fig. 1A and pars. [0013]-[0014], the processor is further configured to process the candidate images based on the capturing parameters).
Regarding claim 7, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 5, wherein the one or more capture specification includes threshold dimension of the instance of the media content (Chalom: see par. [0020]).
Regarding claim 8, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 1, wherein to cause the instance of the media content to be captured by the one or more media capture devices of the client device, the one or more processors are further configured to determine to capture the instance of the media content based on the instance of the media content satisfying the one or more capture specifications (Chalom: see fig. 1A and pars. [0013]-[0014], in which to cause the candidate images to be captured by the image capture device, the processor is further configured to determine to capture the candidate images based on the reference images satisfying the capturing parameters).
Regarding claim 9, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 1, wherein to cause the instance of the media content to be captured by the one or more media capture devices of the client device, the one or more processors are further configured to receive user input triggering capture of the instance of the media content (One of ordinary skill in the art would understand that the one or more processors are further configured to receive user input triggering capture of the instance of the media content).
Regarding claim 10, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 1, wherein the one or more processors are further configured to receive, via the client device, user input indicating the one or more media specifications (Chalom: see fig. 8 and par. [0059], wherein GUI allows the user to control and provide data).
Regarding claim 11, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 10, wherein the user input is associated with a context corresponding to the media content, and wherein the user input includes one or more of string data or character data (One of ordinary skill in the art would understand that the user input is associated with a context corresponding to the media content, and wherein the user input includes one or more of string data or character data).
Regarding claim 12, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 1, wherein, to aggregate the one or more capture specifications, the one or more processors are further configured to:
adapt, based on training data including media specifications different from the one or more media specifications, the at least one generative artificial intelligence model to aggregate the one or more capture specifications (Chalom: see fig. 1A and pars. [0013]-[0014], adapt, based on training image data 12 including media specifications different from the one or more media specifications as parameters of the updated candidate images, the machine learning device to aggregate the capturing parameters); and
receive, as output from the at least one generative artificial intelligence model, the one or more capture specifications (Chalom: see fig. 1A and pars. [0013]-[0014], receive, as output from the machine learning device 10, the capturing parameters).
Regarding claims 14 and 16-17, claims 14, 16-17 are directed to a method corresponding to the apparatus claimed in claims 1, 3, 8, respectively. Claims 14, 16-17 are similar scope to claims 1, 3 and 8, respectively, and are therefore rejected under similar rationale.
Regarding claims 18 and 20, claims 18 and 20 recite the similar subject matter as previously discussed in claims 1 and 3.
Claims 2, 13, 15 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Chalom et al. (“Chalom”, US 2016/0284095) in view of Sethia et al. (“Sethia”, US 11,871,104), Mikhailiuk et al. (“Mikhailiuk”, US 2025/0077794) and further in view of Li et al. (“Li”, US 2024/0394490).
Regarding claim 2, Chalom in the combination with Sethis and Mikhailiuk discloses the client device of claim 1.
Chalom in the combination with Sethis and Mikhailiuk does not explicitly disclose that, to apply the one or more capture specifications, the one or more processors are further configured to initialize the one or more media capture devices according to the one or more capture specifications, and wherein the one or more capture specifications include an orientation of the one or more media capture devices.
On the other hand, Li teaches that, to apply the one or more capture specifications, the one or more processors are further configured to initialize the one or more media capture devices according to the one or more capture specifications, and wherein the one or more capture specifications include an orientation of the one or more media capture devices (Li: see par. [0008], based on the posture change information and the screen orientation of the terminal device, to call the front-facing camera to capture an image).
One would have been modified to include a teaching as taught by Li in the apparatus of Chalom, Sethia and Mikhailiuk to have more functions for the image device.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the teachings of Li with the Chalom, Sethia and Mikhailiuk’s system to include that, to apply the one or more capture specifications, the one or more processors are further configured to initialize the one or more media capture devices according to the one or more capture specifications, and wherein the one or more capture specifications include an orientation of the one or more media capture devices.
Regarding claim 13, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 1.
Chalom in the combination with Sethia and Mikhailiuk does not explicitly disclose that the one or more media capture devices include one or more of a front image capture system or a rear image capture system, and wherein the one or more capture specifications includes an indication of one or more of the front image capture system or the rear image capture system to use for causing the instance of the media content to be captured.
However, Li teaches that the one or more media capture devices include one or more of a front image capture system or a rear image capture system, and wherein the one or more capture specifications includes an indication of one or more of the front image capture system or the rear image capture system to use for causing the instance of the media content to be captured (Li: see figs. 6b-6c and par. [0008], where in the device includes front camera and rear camera, and wherein based on posture change information and the screen orientation of the terminal device to call the front camera to capture an image).
One would have been modified to include a capture device as taught by Li in the apparatus of Chalom, Sethia and Mikhailiuk to use different cameras to capture images.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the teachings of Li with the Chalom, Sethia and Mikhailiuk’s system to include that the one or more media capture devices include one or more of a front image capture system or a rear image capture system, and wherein the one or more capture specifications includes an indication of one or more of the front image capture system or the rear image capture system to use for causing the instance of the media content to be captured.
Regarding claims 15 and 19, claims 15 and 19 recite the similar subject matter as previously discussed in claim 2.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Chalom et al. (“Chalom”, US 2016/0284095) in view of Sethia et al. (“Sethia”, US 11,871,104), Mikhailiuk et al. (“Mikhailiuk”, US 2025/0077794) and further in view of Agrawal et al. (“Agrawal”, US 11,507,266).
Regarding claim 4, although Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 3, Chalom in the combination with Sethia and Mikhailiuk is silent regarding adjusting the one or more attributes of the media content includes removing an object from the media content to satisfy the one or more capture specifications. However, it is obvious to remove an object based on capture specification as suggested by Agrawal in col. 7, lines 57 as specifying particular image features such as specify objects.
Therefore, it would have been obvious to one of ordinary skill in the art to add that feature into the Chalom, Sethia and Mikhailiuk system’s, thereby providing more options for the system.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Chalom et al. (“Chalom”, US 2016/0284095) in view of Sethia et al. (“Sethia”, US 11,871,104), Mikhailiuk et al. (“Mikhailiuk”, US 2025/0077794) and further in view of Borges et al. (“Borges”, US 2023/0362480).
Regarding claim 6, Chalom in the combination with Sethia and Mikhailiuk discloses the client device of claim 5.
Chalom in the combination with Sethia and Mikhailiuk does not explicitly disclose that, to process the instance of the media content, the one or more processors are further configured to: detect a first portion of the instance of the media content associated with an object and a second portion of the instance of the media content associated with a background of the object; and modify a color associated with the second portion of the instance of the media content based on the one or more capture specifications.
However, Borges teaches that to process the instance of the media content, the one or more processors are further configured to: detect a first portion of the instance of the media content associated with an object and a second portion of the instance of the media content associated with a background of the object; and modify a color associated with the second portion of the instance of the media content based on the one or more capture specifications (Borges: see par. [0044], wherein the instructions may include at least one of changing a position of the camera, changing focus of the camera, changing a background of an object in the captured image, and changing lighting. In addition, one of ordinary skill in the art would understand that modify a color associated with the second portion of the instance of the media content based on the one or more capture specifications).
One would have been modified to include a processor as taught by Borges in the apparatus of Chalom, Sethia and Mikhailiuk to obtain image data as requirement.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to combine the teachings of Borges with the Chalom, Sethia and Mikhailiuk’s system to include that, to process the instance of the media content, the one or more processors are further configured to: detect a first portion of the instance of the media content associated with an object and a second portion of the instance of the media content associated with a background of the object; and modify a color associated with the second portion of the instance of the media content based on the one or more capture specifications.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHAN T H NGUYEN whose telephone number is (571)272-3452. The examiner can normally be reached M-F 8AM-4PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lin Ye can be reached at 571-272-7372. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHAN T NGUYEN/Patent Examiner, Art Unit 2638
/LIN YE/Supervisory Patent Examiner, Art Unit 2638
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