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 Amendment
The office action is in response to Applicant’s amendment filed 07/20/2026 which has been entered and made of record. Claims 1-3,5-11,13-14,17-18, and 20-23 have been amended. No claim has been newly added. Claims 1-11, 13-14 and 17-23 are pending in the application.
Response to Arguments
Applicant’s arguments, filed 07/20/2026, with respect to the rejections under 35 U.S.C. 112(b), and the amendments to the rejected claims, have been fully considered and are persuasive. Therefore, the rejections have been withdrawn.
Applicant’s arguments, filed 07/20/2026, with respect to the rejections under 35 U.S.C. 103 over Oberbrunner et al (US 20150117839 A1, hereinafter Oberbrunner) in view of Shu et al (US 11934958 B2, hereinafter Shu) have been fully considered but they are not persuasive.
Applicant argues that Oberbrunner fails to disclose the amended limitation “in response to a second operation instruction, generating an image based on invoking a second local model to add a second visual effect to a rendered image received from the server, wherein the second local model is run at the terminal device, wherein the rendered image is obtained by the server adding the first visual effect with the second precision to the original image, and wherein the image is used for displaying on the terminal device”. Specifically, applicant argues that Oberbrunner fails to disclose the client device invoking any algorithm to add a second visual effect to the high quality image rendered by the server.
Examiner responds that Oberbrunner does disclose the client device adding a second visual effect to the high quality image rendered by the server. Specifically, Oberbrunner teaches continuously editing a video, where a client device may render lower quality effects while a server processes the effects at a higher quality, and when the higher quality effect is complete it replaces the rendered lower quality effect. Multiple effects may be selected and previewed, and if a server has finished rendering a higher quality effect it replaces the lower quality effect, and a second effect may be added to the higher quality image provided by the server (Par 18 “The video appears in the Video Preview Window (202), and can be played using the Play Button (203a, 203b). Effects appear in the Thumbnail Panel (204); the user may choose one or more effects from that panel to be applied to the video clip (205)”, Par 46 “Whenever the user selects a new look or transition or adjusts any parameter, the server can be immediately notified using the methods of this system and the server renders the selected effects onto the video”, Par 54 “while sending instructions to the server to render higher quality images asynchronously. These higher quality images, when ready, can replace the lower quality ones rendered by the device.”). In related field of endeavor, Shu teaches an algorithm on a client device for adding visual effects to an image (Col.23 Line 40-43 “As an example, the
generative model compression system 106 utilizes the distilled GAN to modify images by
introducing visual content and/or visual properties of the image (e.g., lighting, color,
perspective) to the images”, Col.5 Line 51-54 “the client device 110 receives a pruned and
distilled GAN from the generative model compression system 106 and implements the compact
GAN utilizing local hardware of the client device 110.”) It would have been obvious to one of ordinary skill in the art prior to the time of filing to have used the algorithms described by Shu to apply the lower quality effects described by Oberbrunner, and doing so would allow the client device to use fewer resources (Shu Col.5 Line 33-37 “by pruning and distilling a full-sized
noise-to-image GAN in accordance with one or more embodiments, the generative model
compression system 106 generates a compact and effective GAN that utilizes less storage,
processing, and other computing resources.”)
Conclusions: The rejections set in the previous Office Action are shown to have been proper, and the claims are rejected below. New citations and parenthetical remarks can be considered new grounds of rejection and such new grounds of rejection are necessitated by the Applicant's amendments to the claims. Therefore, the present Office Action is made final.
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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
Claims 1-8, 11, 13-14, 17-23 are rejected under 35 U.S.C. 103 as being unpatentable over Oberbrunner et al (US 20150117839 A1, hereinafter Oberbrunner) in view of Shu et al (US 11934958 B2, hereinafter Shu).
Regarding claim 1, Oberbrunner teaches a method for end-cloud collaboration-based image processing, the method being implemented at a terminal device and comprising (Abstract “Systems and methods for applying visual effects to video in a client/server or cloud-based system are described. Using a web browser, for example, users can apply and control both simple and sophisticated effects with dynamic real-time previews without downloading client-side software.”):
in response to a first operation instruction, displaying a first preview image, wherein the first preview image is (Par 18 “To adjust or steer the effect, one or more Effect Control Sliders (206) are provided; the user can drag them and see the results in real time in the Video Preview Window.” Par 54 “The client may render less-complex effects, or low resolution proxy images”, Par 36-38 “User takes video footage with camera or mobile device (500) with a video capture source. User uses web browser to upload raw video to server (501). Web browser presents user's videos and offers editing and effects processing modes (502)”);
sending an algorithm invoking request to a server based on the first operation instruction (Par 54 “while sending instructions to the server to render higher quality images asynchronously.”, Par 20 “The Render interface code (304) is used as an intermediary between the browser (301) and the Render Library code (305) and responds to asynchronous requests from the browser”), wherein the algorithm invoking request is used for invoking a first remote algorithm model executed at the server to add [[a]]the first visual effect with a second precision to the original image (Par 2 “A collection of one or more effects is defined herein as a look”, Par 54 “The client may render less-complex effects, or low resolution proxy images, while sending instructions to the server to render higher quality images asynchronously”, Par 22 “Messages (403) are sent to the server, which collects the video frames, invokes the Render Library software to apply the looks, and optionally one more text or binary preset files describing the look to be applied and various metadata about that look (404, 405). It then renders one or more test frames which are sent to the user (406)”), and wherein the second precision is greater than the first precision (Par 54 “server to render higher quality images asynchronously”);
and in response to a second operation instruction, generating invoking a second local algorithm model to add a second visual effect to a rendered image received from the server to the algorithm invoking request (Par 18 “The video appears in the Video Preview Window (202), and can be played using the Play Button (203a, 203b). Effects appear in the Thumbnail Panel (204); the user may choose one or more effects from that panel to be applied to the video clip (205)”, Par 46 “Whenever the user selects a new look or transition or adjusts any parameter, the server can be immediately notified using the methods of this system and the server renders the selected effects onto the video”, Par 54 “while sending instructions to the server to render higher quality images asynchronously. These higher quality images, when ready, can replace the lower quality ones rendered by the device.”, where multiple effects can be applied, and if the higher quality image is ready before the user selects a second effect, then the effect is applied onto the higher quality image which replaced the lower quality one),
wherein the rendered image is an image obtained by the server adding the first visual effect with the second precision to the original image (Par 22 “Messages (403) are sent to the server, which collects the video frames, invokes the Render Library software to apply the looks, and optionally one more text or binary preset files describing the look to be applied and various metadata about that look (404, 405). It then renders one or more test frames which are sent to the user (406)”, Par 54 “while sending instructions to the server to render higher quality images asynchronously. These higher quality images, when ready, can replace the lower quality ones rendered by the device.”),
and wherein the target image is an image used for displaying on the terminal device (Claim 1 “the first modified video data is being displayed”).
Oberbrunner discloses that a client device may render less-complex or lower resolution effects while sending instructions to the server to render higher quality images ([0054] “The client may render less-complex effects, or low resolution proxy images, while sending instructions to the server to render higher quality images asynchronously.”), and multiple algorithms for applying visual effects (Par 2 “Each frame or set of frames of digitized video is processed by computer algorithms which produce output frames corresponding to the input frames, processed by the effect(s) in question”) but fails to explicitly teach the first visual effect with the first precision is obtained based on a first local algorithm model run at the terminal device and wherein the second local algorithm model is run at the terminal device.
In related field of endeavor, Shu teaches a local algorithm model that is run at a terminal device (Col.23 Line 40-43 “As an example, the generative model compression system 106 utilizes the distilled GAN to modify images by introducing visual content and/or visual properties of the image (e.g., lighting, color, perspective) to the images”, Col.5 Line 51-54 “the client device 110 receives a pruned and distilled GAN from the generative model compression system 106 and implements the compact GAN utilizing local hardware of the client device 110.”) It would have been obvious to one of ordinary skill in the art to have modified Oberbrunner to include algorithm models run at the terminal device as taught by Shu. Doing so would allow the device to use fewer computing resources (Col.5 Line 33-37 “by pruning and distilling a full-sized noise-to-image GAN in accordance with one or more embodiments, the generative model compression system 106 generates a compact and effective GAN that utilizes less storage, processing, and other computing resources.”)
Regarding claim 2, Oberbrunner as modified by Shu teaches the method of claim 1. Oberbrunner further teaches wherein after displaying the first preview image, the method further comprises: in response to a third operation instruction on the first preview image, displaying a second preview image, wherein the second preview image the second visual effect to the first preview image, (Par 18 “The video appears in the Video Preview Window (202), and can be played using the Play Button (203a, 203b). Effects appear in the Thumbnail Panel (204); the user may choose one or more effects from that panel to be applied to the video clip (205). To adjust or steer the effect, one or more Effect Control Sliders (206) are provided; the user can drag them and see the results in real time in the Video Preview Window. When the user is satisfied with the effect, he may render the completed video using the Render Video button (207).”, where at least 2 effects can be applied and previewed in real time, and where applying a first effect creates a first preview image through a first operation instruction, and applying a second effect creates a second preview image through a third operation instruction.);
wherein the generating a target image based on the rendered image responded by the server to the algorithm invoking request comprises: generating a target image based on the third operation instruction and the rendered image, the target image being an image obtained by adding the first visual effect and the second visual effect with the second precision to the original image. (Par 2 “A collection of one or more effects is defined herein as a look.”, Par 18 “The video appears in the Video Preview Window (202), and can be played using the Play Button (203a, 203b). Effects appear in the Thumbnail Panel (204); the user may choose one or more effects from that panel to be applied to the video clip (205). To adjust or steer the effect, one or more Effect Control Sliders (206) are provided; the user can drag them and see the results in real time in the Video Preview Window.” Par 20 “The Render Library code (305) implements the processing of the effects and processes the video pixel data for each frame, using the selected effect and parameters provided by the user.”, Par 22 “The user indicates, such as by pointing, drag-and-drop or similar means, the intent to apply a particular look to a particular set of video frames. Messages (403) are sent to the server, which collects the video frames, invokes the Render Library software to apply the looks”, Par 41 “final rendering happens automatically in the background (without user interaction) or the user explicitly signals server to begin final render (506).” Par 42 “After rendering is complete, the processed video is ready for viewing and optional download or distribution (507).”)
Oberbrunner fails to explicitly teach using the second local algorithm model . Oberbrunner does teach multiple algorithms for applying visual effects (Par 2 “Each frame or set of frames of digitized video is processed by computer algorithms which produce output frames corresponding to the input frames, processed by the effect(s) in question”), but fails to explicitly teach that the algorithms are executed at the terminal device. In related field of endeavor, Shu teaches a visual effect algorithm model executed at the terminal device (Col.23 Line 40-43 “As an example, the generative model compression system 106 utilizes the distilled GAN to modify images by introducing visual content and/or visual properties of the image (e.g., lighting, color, perspective) to the images”, Col.5 Line 51-54 “the client device 110 receives a pruned and distilled GAN from the generative model compression system 106 and implements the compact GAN utilizing local hardware of the client device 110.”)
It would have been obvious to one of ordinary skill at the time of filing to have modified
Oberbrunner to include a visual effect algorithm model executed at the terminal device as
taught by Shu. Doing so would allow the device to use fewer computing resources (Col.5 Line
33-37 “by pruning and distilling a full-sized noise-to-image GAN in accordance with one or more
embodiments, the generative model compression system 106 generates a compact and
effective GAN that utilizes less storage, processing, and other computing resources.”)
Regarding claim 3, Oberbrunner as modified by Shu teaches the method of claim 1.
Oberbrunner further teaches wherein the first operation instruction indicates an (Par 20 “The Render Library code (305)
implements the processing of the effects and processes the video pixel data for each frame,
using the selected effect and parameters provided by the user.”), and wherein the in response to [[a]] the first operation instruction, displaying [[the first preview image comprises: in response to the first operation instruction, acquiring the (Par 20 “The Render Library code (305) implements the processing of the effects and processes the video pixel data for each frame, using the selected effect and parameters provided by the user”, Par 28 “The render code on the server initializes the effect rendering library, sets the library up to render that effect with given parameters, and creates the user- visible controls from the control definitions”); determining the first local algorithm model based on the target effect identifier; and invoking the first local algorithm model to render the original image, and displaying the first preview image (Par 20 “The Render Library code (305) implements the processing of the effects and processes the video pixel data for each frame, using the selected effect and parameters provided by the user”, Par 28 “The render code on the server initializes the effect rendering library, sets the library up to render that effect with given parameters, and creates the user-visible controls from the control definitions”, Par 18 “To adjust or steer the effect, one or more Effect Control Sliders (206) are provided; the user can drag them and see the results in real time in the Video Preview Window.”).
Regarding claim 4, Oberbrunner as modified by Shu teaches The method of claim 1.
Oberbrunner fails to explicitly teach wherein the first remote algorithm model is an image
style transfer model based on a generative antagonistic network; the first local algorithm model is a light-weight model obtained by performing model distillation on the first remote algorithm model. In related field of endeavor, Shu teaches wherein the first remote algorithm model is an image style transfer model based on a generative antagonistic network (Col.23 Line 45-47 “utilizes the distilled GAN to modify images by transferring visual attributes or portions of one image to another image”); the first local algorithm model is a light-weight model obtained by performing model distillation on the first remote algorithm model (Col.4 Line 7-10 “For example, the generative model compression system deploys the compact and efficient distilled GAN onto a mobile device such that the distilled GAN operates locally on the mobile device”)
It would have been obvious to one of ordinary skill in the art prior to the effective filing
date to have modified Oberbrunner to include wherein the first remote algorithm model is an
image style transfer model based on a generative antagonistic network; the first local algorithm
model is a light-weight model obtained by performing model distillation on the first remote
algorithm model. Doing so would provide a model which outputs images of a similar visual
quality with minor performance loss (Col 4 Line 59-63 “the generative model compression
system generates a pruned and distilled GAN that outputs a similar generated visual quality and
minor performance loss in image generation and image projection compared to a full-size
noise-to-image GAN.”)
Regarding claim 5, Oberbrunner as modified by Shu teaches The method of claim 2.
Oberbrunner further teaches wherein the third operation instruction comprises an effect
identifier and an effect parameter corresponding to the second visual effect (Par 18 “Effects
appear in the Thumbnail Panel (204); the user may choose one or more effects from that panel
to be applied to the video clip (205). To adjust or steer the effect, one or more Effect Control Sliders (206) are provided; the user can drag them and see the results in real time in the Video
Preview Window.”, Par 20 “The Render Library code (305) implements the processing of the
effects and processes the video pixel data for each frame, using the selected effect and
parameters provided by the user.”); wherein the sending [[an]] the algorithm invoking request to [[a]] the server based on the first operation instruction comprises: sending, through a first process, an algorithm invoking request corresponding to the first operation instruction to the server (Par 46 “Whenever the user selects a new look or transition or adjusts any parameter, the server can be immediately notified using the methods of this system and the server renders the selected effects onto the video”); wherein the in response to [[a]] the third operation instruction on the first preview image, displaying [[a]] the second preview image comprises: invoking, through a second process, [[a]] the second local algorithm model corresponding to the effect identifier, rendering the first preview image based on the effect parameter, and displaying the second preview image (Par 23 “each update of a control is sent to the server (408), which renders one or more frames (409)”, Par 46 “Whenever the user selects a new look or transition or adjusts any parameter, the server can be immediately notified using the methods of this system and the server renders the selected effects onto the video”).
Regarding claim 6, Oberbrunner as modified by Shu teaches the method of claim 1.
Oberbrunner further teaches wherein the sending [[an]] the algorithm invoking request to [[a]] the server based on the first operation instruction comprises: generating, based on the first operation instruction and the original image, an algorithm request parameter corresponding to the first remote algorithm model (Par 2 “A collection of one or more effects is defined herein as a look.”, Par 22 “Messages (403) are sent to the server, which collects the video frames, invokes the Render Library software to apply the looks, and optionally one more text or binary preset files describing the look to be applied and various metadata about that look”, Par 26-27 “JavaScript (JS) or other scripting language code to run in the browser. [0027] The JavaScript (JS) code asynchronously sends information to the server to set up the current effect and any preset parameters. (403)”, Par 28 “the server initializes the effect rendering library, sets the library up to render that effect with given parameters”); and sending the algorithm invoking request to the server based on the algorithm request parameter (Par 22 “Messages (403) are sent to the server, which collects the video frames, invokes the Render Library software to apply the looks, and optionally one more text or binary preset files describing the look to be applied and various metadata about that look”, Par 28 “the server initializes the effect rendering library, sets the library up to render that effect with given parameters”); wherein after sending the algorithm invoking request to [[a]] the server based on the first operation instruction, the method further comprises: receiving the rendered image responded by the server to the algorithm invoking request, and buffering the rendered image (Par 54 “the device may do local playback of cached rendered frames rather than constantly streaming from the server”).
Regarding claim 7, Oberbrunner as modified by Shu teaches the method of claim 2.
Oberbrunner further teaches wherein the generating the image based on the third
operation instruction and the rendered image comprises: determining the
second local algorithm model based on the third operation instruction; and invoking the
second local algorithm model to add the second visual effect to the rendered image, to
generate the (Par 2 “A collection of one or more effects is defined herein as a look.”, Par 2 “Each frame or set of frames of digitized video is processed by computer
algorithms which produce output frames corresponding to the input frames, processed by the
effect(s)”, Par 22 “Messages (403) are sent to the server, which collects the video frames,
invokes the Render Library software to apply the looks, and optionally one more text or binary
preset files describing the look to be applied and various metadata about that look”, Par 46
“Whenever the user selects a new look or transition or adjusts any parameter, the server can
be immediately notified using the methods of this system and the server renders the selected
effects onto the video”).
Regarding claim 8, Oberbrunner as modified by Shu teaches the method of claim 7.
Oberbrunner further teaches wherein the third operation instruction comprises an effect
identifier and an effect location (Par 2 “A collection of one or more effects is defined herein as
a look.”, Par 22 “Messages (403) are sent to the server, which collects the video frames, invokes
the Render Library software to apply the looks, and optionally one more text or binary preset
files describing the look to be applied and various metadata about that look (404, 405) … the
parameter values may include brightness, saturation, strength, position (e.g., for an X/Y
control”, Par 27-28 “The JavaScript (JS) code asynchronously sends information to the server to
set up the current effect and any preset parameters. (403) [0028] The render code on the
server initializes the effect rendering library, sets the library up to render that effect with given
parameters”); and the determining the second local algorithm model based on the third operation instruction comprises: determining the second local algorithm model based on the effect identifier, wherein the second local algorithm model is used for adding an the image (Par 22 “Messages(403) are sent to the server, which collects the video frames, invokes the Render Library software to apply the looks, and optionally one more text or binary preset files describing the look to be applied and various metadata about that look (404, 405) … the parameter values may include brightness, saturation, strength, position (e.g., for an X/Y control”, Par 27-28 “The JavaScript (JS) code asynchronously sends information to the server to set up the current effect and any preset parameters. (403) [0028] The render code on the server initializes the effect rendering library, sets the library up to render that effect with given parameters”, The prior art used here uses look and effect interchangeably, see paragraph 2.); wherein the invoking the second local algorithm model to add the second visual effect to the rendered image, to generate the second local algorithm model, adding the (Par 22 “For example, the parameter values may include brightness, saturation, strength, position (e.g., for an X/Y control), width, length”, Par 28 “The render code on the server initializes the effect rendering library, sets the library up to render that effect with given parameters”)
Regarding claim 11, Oberbrunner as modified by Shu teaches the method of claim 1.
Oberbrunner further teaches wherein before in response to [[a]] the first operation instruction, displaying the first preview image, the method further comprises: loading and displaying an image effect tool; and in response to a tool operation instruction on the image effect tool, displaying an image acquisition interface for acquiring the original image (Par 22 “The browser (301) initiates the conversation with the server code (307), such as via an HTTP GET command (401). The server returns (402) code (e.g., HTML+CSS+JavaScript) which is interpreted by the browser to show the user's videos and a selection of possible looks to apply.”, Par 36-38 “User takes video footage with camera or mobile device (500) with a video capture source . User uses web browser to upload raw video to server (501). Web browser presents user's videos and offers editing and effects processing modes (502)”).
Regarding claim 13, the electronic device (Oberbrunner Par 53 “Different servers might be made up of hardware with different capabilities, such as graphics processing units, faster floating point hardware, or increased memory”, Par 65 “Aspects of the invention may be stored or distributed on computer-readable media”) claim 13 is similar in scope to the method claim 1, and is rejected under similar rationale.
Regarding claim 14, the non-transitory computer readable medium (Oberbrunner Par 65 “Aspects of the invention may be stored or distributed on computer-readable media”) claim 14 is similar in scope to the device claim 13, and is rejected under similar rationale.
Regarding claim 17, the device claim 17 is similar in scope to the method claim 2, and is
rejected under similar rationale.
Regarding claim 18, the device claim 18 is similar in scope to the method claim 3, and is
rejected under similar rationale.
Regarding claim 19, the device claim 19 is similar in scope to the method claim 4, and is
rejected under similar rationale.
Regarding claim 20, the device claim 20 is similar in scope to the method claim 5, and is
rejected under similar rationale.
Regarding claim 21, the device claim 21 is similar in scope to the method claim 6, and is
rejected under similar rationale.
Regarding claim 22, the device claim 22 is similar in scope to the method claim 7, and is
rejected under similar rationale.
Regarding claim 23, the device claim 23 is similar in scope to the method claim 8, and is
rejected under similar rationale.
Claims 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Oberbrunner as modified by Shu as applied to claim 2 above, and further in view of Yen-Cheng Lee (US 11854177 B2, hereinafter Lee).
Regarding claim 9, Oberbrunner as modified by Shu teaches the method of claim 2,
wherein the generating the image based on the third operation instruction and the
rendered image comprises: determining (Oberbrunner , Par 2 “Each frame or set of frames of
digitized video is processed by computer algorithms which produce output frames
corresponding to the input frames, processed by the effect(s)”, Par 46 “Whenever the user
selects a new look or transition or adjusts any parameter, the server can be immediately
notified using the methods of this system and the server renders the selected effects onto the
video”); invoking the second local algorithm model to add the second visual effect to the
original image, to generate a first image (Oberbrunner, Par 2 “Each frame or set of frames of
digitized video is processed by computer algorithms which produce output frames
corresponding to the input frames, processed by the effect(s)”, Par 46 “Whenever the user
selects a new look or transition or adjusts any parameter, the server can be immediately
notified using the methods of this system and the server renders the selected effects onto the
video”).
Oberbrunner and Shu fails to explicitly teach splicing the first image and the rendered
image, to generate the . In related field of endeavor, Lee teaches splicing the first image and the rendered image, to generate the target image (Col.6 Line 26-28 “the processor 104 may splice at least the first prediction image region 531a and the second prediction image region 532a into a spliced image 540”).
It would have been obvious to one of ordinary skill in the art prior to the time of filing to have modified Oberbrunner and Shu to include splicing the first image and the rendered image, to generate the as taught by Lee. Doing so would create a spliced image with relatively low distortion (Col.6 Line 49-50 “Thereby, the spliced image 540 has relatively low distortion.”)
Regarding claim 10, The combination of Oberbrunner, Shu and Lee teach the method of claim 9. Lee further teaches wherein the splicing the first image and the rendered image, to generate the (Col.5 Line 54-58 “Then, in step S430, the processor 104 may find a first image region 511a that does not include the second sub-overlap region 522 in the first cropped image 511, and find a second image region 512a that does not include the first sub-overlap region 521 in the second cropped image 512”, Col.5 Line 59-64 “the first image region 511a is, for example, an image region remaining after the second sub- overlap region 522 is removed from the first cropped image 511, and the second image region 512a is, for example, an image region remaining after the first sub-overlap region 521 is removed from the second cropped image 512”); and splicing, based on the first effect region and the second effect region, the first image and the rendered image to generate the (Col.6 Line 26-33 “splice at least the first prediction image region 531a and the second prediction image region 532a into a spliced image 540. A first relative position between the first prediction image region 531a and the second prediction image region 532a in the spliced image 540 corresponds to a second relative position between the first image region 511a and the second image region 512a in the to-be-predicted image 510.”).
It would have been obvious to one of ordinary skill in the art prior to the time of filing to have modified Oberbrunner and Shu to include wherein the splicing the first image and the rendered image, to generate the image comprises: acquiring a first effect region and a second effect region, wherein the first effect region is an image region where a second visual effect is located in the first image, and the second effect region is an image region where a first visual effect is located in the rendered image; and splicing, based on the first effect region and the second effect region, the first image and the rendered image to generate the image as taught by Lee. Doing so would create a spliced image with relatively low distortion (Col.6 Line 49-50 “Thereby, the spliced image 540 has relatively low distortion.”)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Oh et al (US 20170352379 A1, hereinafter Oh) teaches a method of video editing using a mobile terminal and remote computer, where the user of a mobile terminal can select visual effects to apply to a video and view a preview on the terminal device, and when a user confirms the preview a request is sent to a server to generate the visual effect on the video. (Abstract "A method for video editing using a mobile terminal and a remote computer is disclosed. A user selects a user video to edit using a mobile application of the mobile terminal. The user selects a visual effect and parameters of the visual effect using the mobile application. Subsequently, the mobile application provides a preview of the visual effect superimposed over the user video using a series of still images representing the visual effect. When the user confirms the preview, the mobile terminal generates a request for video editing and sends the .
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 JOHN PATRICK GOCO whose telephone number is (571)272-5872. The examiner can normally be reached M-Th, 7:00 am - 5:00 pm.
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, Kee Tung can be reached at (571)272-7794. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/J.P.G./ Examiner, Art Unit 2611
/KEE M TUNG/ Supervisory Patent Examiner, Art Unit 2611
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