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 .
Application Status
This office action is responsive to the amendments filed on 05/14/2026.
Claims 1-9 and 19-29 are pending and presented for examination. Claims 10-18 has been canceled.
This action has been made FINAL.
Response to Arguments
Applicant's arguments filed 05/14/2026 have been fully considered but they are not persuasive.
The Applicant alleged the following: “However, Yu does not describe receiving an encoded digital image that has been rendered at a remote device, and performing additional rendering on a decoded version of the encoded digital image.” The examiner is not persuaded. Yu discloses the Applicant’s claim language of “configured to receive an encoded digital image” in Yu Paragraph 0052. Yu goes on to disclose the Applicant’s claim language of “from an additional device that is remote to the device” in Yu Figure 13; Paragraphs 0114-0118. Moreover, Yu discloses the Applicant’s claim language of “generate a decoded digital image from the encoded digital image, the encoded digital image in Figure 1, Items 16; Paragraphs 0070-0074. In Yu Figure 13; Paragraphs 0114-0118, Yu discloses the Applicant’s claim language of “having been rendered at the additional device.” Accordingly, the examiner maintains the rejection.
The Applicant alleged the following: “However, Yu fails to disclose a specific pipeline where the server computing system encodes and renders a digital image for transmission to the user computing device, and the user computing device performs additional rendering.” The examiner is not persuaded. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., specific pipeline) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Moreover, the Applicant is rehashing arguments already addressed above. As mentioned above, Yu discloses the Applicant’s claim language of “configured to receive an encoded digital image” in Yu Paragraph 0052. Yu goes on to teach the Applicant’s claim language of “from an additional device that is remote to the device” in Yu Figure 13; Paragraphs 0114-0118. Moreover, Yu teaches the Applicant’s claim language of “generate a decoded digital image from the encoded digital image, the encoded digital image in Figure 1, Items 16; Paragraphs 0070-0074. In Yu Figure 13; Paragraphs 0114-0118, Yu teaches the Applicant’s claim language of “having been rendered at the additional device.” Accordingly, the examiner maintains the rejection.
The Applicant alleged the following: “Thus, Yu fails to disclose, teach, or suggest (emphasis added) "a device comprising a decoder implemented in hardware and configured to receive an encoded digital image from an additional device that is remote to the device and generate a decoded digital image from the encoded digital image, the encoded digital image having been rendered at the additional device," and "a renderer implemented in hardware and configured to reconstruct a digital image from the decoded digital image by performing additional rendering on the decoded digital image using a machine-learning model," as recited in amended claim 1. Accordingly, Applicant submits that Yu does not alone disclose, or in combination teach or in any way suggest the subject matter of claim 1, particularly as amended. As such, Applicant requests that the § 102 rejection of claim 1 be withdrawn.” The examiner is not persuaded. Yu discloses the Applicant’s claim language of “configured to receive an encoded digital image” in Yu Paragraph 0052. Yu goes on to disclose the Applicant’s claim language of “from an additional device that is remote to the device” in Yu Figure 13; Paragraphs 0114-0118. Moreover, Yu discloses the Applicant’s claim language of “generate a decoded digital image from the encoded digital image, the encoded digital image in Figure 1, Items 16; Paragraphs 0070-0074. In Yu Figure 13; Paragraphs 0114-0118, Yu discloses the Applicant’s claim language of “having been rendered at the additional device.” Yu goes on to disclose the Applicant’s claim language of “a renderer implemented in hardware and configured to reconstruct a digital image” in Yu Paragraph 0090. Figure 1, Items 24 and Paragraphs 0026 -0033; 0070-0074 of Yu discloses the Applicant’s claim language of “from the decoded digital image by performing additional rendering on the decoded digital image.” Yu discloses “using a machine-learning model” in Paragraphs 0008-0011; 0025-0028; 0144-0145. MPEP § 2106 states Office personnel are to give claims their broadest reasonable interpretation in light of the supporting disclosure. In re Morris, 127 F.3d 1048, 1054-55, 44 USPQ2d 1023, 1027-28 (Fed Cir. 1997). Accordingly, the examiner maintains the rejection.
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-5, 19, 21, 22, 24, 25 and 29 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Yu, US 20240112088.
Claim 1:
Yu discloses a device (See Abstract; Summary of Invention) comprising:
a decoder (See Yu Figure 1, Items 24; Paragraphs 0070-0074) implemented in hardware and configured to receive an encoded digital image (See Yu Paragraph 0052) from an additional device that is remote to the device (See Yu Figure 13; Paragraphs 0114-0118) and generate a decoded digital image (See Yu Figure 1, Items 24; Paragraphs 0070-0074) from the encoded digital image (See Yu Figure 1, Items 16; Paragraphs 0070-0074), the encoded digital image (See Yu Figure 1, Items 16; Paragraphs 0070-0074) having been rendered at the additional device (See Yu Figure 13; Paragraphs 0114-0118);
and a renderer implemented in hardware and configured to reconstruct a digital image (See Yu Paragraph 0090) from the decoded digital image (See Yu Figure 1, Items 24; Paragraphs 0070-0074) by performing additional rendering on the decoded digital image (See Yu Figure 1; Paragraphs 00261-0033; 0070-0074) using a machine-learning model (See Yu Paragraphs 0008-0011; 0025-0028; 0144-0145).
Claim 2:
Yu discloses wherein the digital image is panoramic as capturing a plurality of viewpoints of an environment (See Yu Paragraph 01072) and the renderer is configured to adjust a respective said viewpoint with respect to the environment captured by the digital image (See Yu Paragraph 01073).
Claim 3:
Yu discloses a sensor implemented in hardware to detect movement and wherein the renderer is configured to adjust the respective said viewpoint (See Yu Paragraph 01074) based on the detected movement (See Yu Paragraphs 0147; 0151).
Claim 4:
Yu discloses wherein the machine-learning model (See Yu Paragraphs 0008-0011; 0025-0028; 0144-0145) is configured to reconstruct high dynamic range pixels of the digital image (See Yu Paragraph 0055; 0065; 0090; 0104) from standard dynamic range pixels (See Yu Paragraph 0055; 0065; 0104) included in the encoded digital image (See Yu Figure 1, Items 16; Paragraphs 0070-0074).
Claim 5:
Yu discloses wherein the machine-learning model (See Yu Paragraphs 0008-0011; 0025-0028; 0144-0145) is configured to reconstruct illumination with respect to one or more objects in an environment captured by the digital image (See Yu Paragraph 0090).
Claims 19 and 21:
Claims 19 and 21 are rejected on the same basis as claim 1.
Claim 22:
Yu discloses communicating, by the first device, client capability data to the second device, the client capability data describing machine-learning functionality supported by the first device, the encoded digital image based on the client capability data (See Yu Paragraphs 0008-0011; 0025-0028; 0144-0145).
Claim 24 and 25:
Claims 24 and 25 are rejected on the same basis as claims 4 and 5.
Claim 29:
Claim 29 is rejected on the same basis as 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.
Claim(s) 6-9, 20, 23, 26 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Yu, US 20240112088, in view of Cerny, US 20210241415.
Claim 6:
Yu failed to disclose cast a transient illumination effect back into the environment. However, Cerny discloses this feature in paragraph 0079. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified Yu by the teachings of Cerny to enable improved graphic processing when rendering an image, more effectively (See Cerny Technical Field of Invention). In addition, both of the references teach features that are directed to analogous art and they are directed to the same field of endeavor, such as graphic processing. This close relation between both references highly suggests an expectation of success.
As modified:
The combination of Yu and Cerny discloses wherein the machine-learning model (See Yu Paragraphs 0008-0011; 0025-0028; 0144-0145) is configured to reconstruct the illumination using image-based lighting (IBL) or cast a transient illumination effect back into the environment (See Cerny Paragraph 0079).
Claim 7:
Yu failed to disclose a geometry buffer. However, Cerny discloses this feature in paragraph 0098. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified Yu by incorporating geometry buffer, as taught by Cerny, to enable improved graphic processing when rendering an image, more effectively (See Cerny Technical Field of Invention). In addition, both of the references teach features that are directed to analogous art and they are directed to the same field of endeavor, such as graphic processing. This close relation between both references highly suggests an expectation of success.
As modified:
The combination of Yu and Cerny discloses wherein the machine-learning model (See Yu Paragraphs 0008-0011; 0025-0028; 0144-0145) is configured to reconstruct one or more geometry buffer assets from a geometry buffer configured to store geometric data of one or more objects in an environment captured by the digital image (See Cerny Paragraph 0098).
Claim 8:
The combination of Yu and Cerny wherein the one or more geometry buffer assets define albedo, normal vectors, depth, or secularity of the one or more objects in the environment (See Cerny Paragraph 0098).
Claim 9:
The combination of Yu and Cerny wherein the machine-learning model (See Yu Paragraphs 0008-0011; 0025-0028; 0144-0145) is configured to compute shading in the environment captured by the digital image using the one or more geometry buffer assets (See Cerny Paragraph 0098).
Claim 20:
Claim 20 is rejected on the same basis as claim 6.
Claim 23:
Claim 23 is rejected on the same basis as claim 9.
Claims 26 and 27:
Claims 26 and 27 are rejected on the same basis as claims 6 and 7.
Claim(s) 28 is rejected under 35 U.S.C. 103 as being unpatentable over Yu, US 20240112088, in view of Cerny, US 20210241415 and in further view of Kreis, US 20250111588.
Claim 28:
The combination of Yu and Cerny failed to disclose path tracing using generative artificial intelligence. However, Kreis discloses this feature in paragraph 0025. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified Yu and Cerny by the teachings of Kreis to generate new image using generative AI, more effectively (See Kreis Abstract).
As modified:
The combination of Yu, Cerny and Kreis discloses wherein the encoded digital image is configured using path tracing and the machine-learning functionality is to smooth the path tracing using generative artificial intelligence (Kreis Paragraph 0025).
Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Fortin, US 20100135379 discloses a method and a system for encoding and decoding a digital image frame.
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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHEREE N BROWN whose telephone number is (571)272-4229. The examiner can normally be reached M-F 5:30-2:00 PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SAID BROOME can be reached at (571) 272-2931. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHEREE N BROWN/Primary Examiner, Art Unit 2612 June 4, 2026
1 Yu Paragraph 0026 recites “the machine-learned image processing model further comprises a decoder portion configured to generate reconstructed image patches based on the one or more quantized codes or to generate synthetic image patches based at least in part on the one or more predicted quantized codes.”
2 Yu recites in Paragraph 0107 “zooming in on some of the images.”
3 Yu recites in Paragraph 0107 “zooming in on some of the images.”
4 Yu recites in Paragraph 0107 “zooming in on some of the images.”
Prosecution Insights