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 .
DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 January 21, 2026 has been entered.
Claims 1-15 are pending.
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.
Claims 1-3, 6, 7 and 11-15 are rejected under 35 U.S.C. 103 as being unpatentable over Stathacopoulos et al. (Pub. No.: US 2017/0118512) in view of Arora (Pub. No.: US 2020/0082279) and Knapp et al. (Pub. No.: US 2013/0232194).
Regarding claim 1, Stathacopoulos discloses a display device comprising: a display (Fig. 5, element 500); a communication module (Fig. 3, elements 302, 304 and 306, para. [0071]); a memory storing one or more instructions (Fig. 3, elements 304 and 308, para. [0074]); and at least one processor (Fig. 3, element 306, para. [0072]) configured to execute the one or more instructions to: process multiple video signals of received multiple videos, generate a mixed video from the processed multiple video signals (paras. [0075] and [0087]; “Multiple tuners may be provided to handle simultaneous tuning functions (e.g., watch and record functions, picture-in-picture (PIP) functions, multiple-tuner recording, etc.).”), display the generated mixed video on the display in a multi-view (paras. [0075] and [0087]), extract multiple fingerprints corresponding to the multiple video signals, respectively (Fig. 5, elements 502, 504 and 506, paras. [0105]-[0106]; the extraction of multiple fingerprints could obviously occur during display of a picture-in-picture.), control the communication module to transmit the multiple fingerprints to a server (Fig. 6, element 604, para. [0128]), obtain multiple pieces of matching information for the multiple fingerprints, respectively, from the server through the communication module (Fig. 6, elements 606, 608 and 610, paras. [0129]-[0130]).
Stathacopoulos does not disclose wherein the processor is configured to execute the one or more instructions to recommend, on the display, content based on the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. However, in analogous art, Arora discloses that “protected data may include premium media content, such as television shows or movies, that may be rendered or displayed on the user device 200 or a display device (not shown for simplicity) coupled to the user device 200. In some embodiments, the neural network application 224 may infer objects of interest (e.g., people, places, logos, and the like) from the premium content. For example, the neural network application 224 may identify logos or symbols associated with a content provider (e.g., a television broadcast network, movie production studio, and the like). The neural network application 224 may determine, based on the identified logos or symbols, that the user of the user device 200 has a preference for television shows broadcast on a particular television station or network. Accordingly, the neural network application 224 may recommend other shows to the user from the same television network (para. [0041]),” and that “the neural network application 224 may identify logos or symbols associated with product brands and/or advertisements. In some aspects, the neural network application 224 may determine, based on the identified logos or symbols, that the user of the user device 200 has a preference or interest in a particular brand or type of product. Accordingly, the neural network application 224 may present targeted advertisements to the user for the particular brand or type of product (or related brands and/or products). In some other aspects, the neural network application 224 may determine, based on the identified logos or symbols, which advertisements and/or product branding is most likely to have been viewed by the user of the user device 200. Accordingly, the neural network application 224 may provide attribution to the television network that broadcasted the media content for the advertisement or product placement (para. [0042]),” which teaches that information such as logos or symbols identified in content may be used to recommend other content, wherein obviously more than one identified logo or symbol may be used, i.e. a combination of the obtained multiple pieces of matching information. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos to allow for the processor to be configured to execute the one or more instructions to recommend, on the display, content based on the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. This would have produced predictable and desirable results, in that it would allow for users to be informed about items of potential interest to the user, which could increase user satisfaction with the system.
It could be argued that Stathacopoulos and Arora do not explicitly disclose recommending content based on a combination of the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. However, in analogous art, Knapp discloses that “a recommendation engine 312 may utilize a combination of and variety of attributes/aspects in order to determine and recommend particular media content. For example, user profiles may be established, and based on similar profiles, the media content viewed by one user 102/132 may be recommended to another user 102/132. The analysis may further determine media content to recommend based on various combinations of the time of day, day of the week, prior media content viewing history (that may also be based on the time of day and or other profile information), location of the user 102/132 (e.g., in a car, in a particular city, identified as a tourist, on business, commuting, at an office, etc.), friends of the user 102/132, gender, age, etc. (para. [0055]),” which teaches that a combination of attributes may be using in order to recommend content. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos and Arora to allow for recommending content based on a combination of the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. This would have produced predictable and desirable results, in that it would allow for the recommendation to be based on a larger sample of a user’s viewing history, which could increase the quality of the recommendations and thus potentially increase user satisfaction with the system.
Regarding claim 2, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, and further discloses wherein the at least one processor is configured execute the one or more instructions to: obtain multiple video frames corresponding to the multiple videos, respectively, based on the processed multiple video signals, and extract the multiple fingerprints based on the obtained multiple video frames (Stathacopoulos, para. [0114]).
Regarding claim 3, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, and further discloses wherein the at least one processor is configured to execute the one or more instructions to: obtain a video frame of the mixed video from the mixed video, obtain multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video, and extract the multiple fingerprints based on the multiple video frames (Stathacopoulos, para. [0114]; “Control circuitry 304 may then isolate the elements of the image that comprise device indicator 506 from the other elements of the image, and capture a fingerprint of only the elements of device indicator 506.” Isolating is obviously similar to cropping.).
Regarding claim 6, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, and further discloses wherein the at least one processor is configured to execute the one or more instructions to: control the communication module to transmit each of the extracted multiple fingerprints for each of the multiple videos to the server (Stathacopoulos, Fig. 6, elements 612 and 614, paras. [0130] and [0131]. It would be an obvious design choice whether to send the fingerprints separately or as a whole.).
Regarding claim 7, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, and further discloses wherein the at least one processor is configured to execute the one or more instructions to: control the communication module to transmit the extracted multiple fingerprints as a whole to the server (Stathacopoulos, Fig. 6, elements 604 and 606, paras. [0128] and [0129]. It would be an obvious design choice whether to send the fingerprints separately or as a whole.).
Regarding claim 11, Stathacopoulos discloses an operation method comprising: receiving multiple video signals of multiple videos (Fig. 3, elements 302, 304 and 306, para. [0071]); processing the received multiple video signals; generating a mixed video from the processed multiple video signals (paras. [0075] and [0087]; “Multiple tuners may be provided to handle simultaneous tuning functions (e.g., watch and record functions, picture-in-picture (PIP) functions, multiple-tuner recording, etc.).”); displaying the generated mixed video on the display in a multi-view (paras. [0075] and [0087]), extracting multiple fingerprints corresponding to the multiple video signals, respectively (Fig. 5, elements 502, 504 and 506, paras. [0105]-[0106]; the extraction of multiple fingerprints could obviously occur during display of a picture-in-picture); transmitting the extracted multiple fingerprints to a server (Fig. 6, element 604, para. [0128]); and obtaining multiple pieces of matching information for the multiple fingerprints, respectively, from the server (Fig. 6, elements 606, 608 and 610, paras. [0129]-[0130]).
Stathacopoulos does not disclose recommending, on the display, content based on the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. However, in analogous art, Arora discloses that “protected data may include premium media content, such as television shows or movies, that may be rendered or displayed on the user device 200 or a display device (not shown for simplicity) coupled to the user device 200. In some embodiments, the neural network application 224 may infer objects of interest (e.g., people, places, logos, and the like) from the premium content. For example, the neural network application 224 may identify logos or symbols associated with a content provider (e.g., a television broadcast network, movie production studio, and the like). The neural network application 224 may determine, based on the identified logos or symbols, that the user of the user device 200 has a preference for television shows broadcast on a particular television station or network. Accordingly, the neural network application 224 may recommend other shows to the user from the same television network (para. [0041]),” and that “the neural network application 224 may identify logos or symbols associated with product brands and/or advertisements. In some aspects, the neural network application 224 may determine, based on the identified logos or symbols, that the user of the user device 200 has a preference or interest in a particular brand or type of product. Accordingly, the neural network application 224 may present targeted advertisements to the user for the particular brand or type of product (or related brands and/or products). In some other aspects, the neural network application 224 may determine, based on the identified logos or symbols, which advertisements and/or product branding is most likely to have been viewed by the user of the user device 200. Accordingly, the neural network application 224 may provide attribution to the television network that broadcasted the media content for the advertisement or product placement (para. [0042]),” which teaches that information such as logos or symbols identified in content may be used to recommend other content, wherein obviously more than one identified logo or symbol may be used, i.e. a combination of the obtained multiple pieces of matching information. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos to allow for recommending, on the display, content based on the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. This would have produced predictable and desirable results, in that it would allow for users to be informed about items of potential interest to the user, which could increase user satisfaction with the system.
It could be argued that Stathacopoulos and Arora do not explicitly disclose recommending content based on a combination of the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. However, in analogous art, Knapp discloses that “a recommendation engine 312 may utilize a combination of and variety of attributes/aspects in order to determine and recommend particular media content. For example, user profiles may be established, and based on similar profiles, the media content viewed by one user 102/132 may be recommended to another user 102/132. The analysis may further determine media content to recommend based on various combinations of the time of day, day of the week, prior media content viewing history (that may also be based on the time of day and or other profile information), location of the user 102/132 (e.g., in a car, in a particular city, identified as a tourist, on business, commuting, at an office, etc.), friends of the user 102/132, gender, age, etc. (para. [0055]),” which teaches that a combination of attributes may be using in order to recommend content. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos and Arora to allow for recommending content based on a combination of the obtained multiple pieces of matching information corresponding to the multiple video signals that are simultaneously displayed in the mixed video. This would have produced predictable and desirable results, in that it would allow for the recommendation to be based on a larger sample of a user’s viewing history, which could increase the quality of the recommendations and thus potentially increase user satisfaction with the system.
Regarding claim 12, the combination of Stathacopoulos, Arora and Knapp discloses the operation method of claim 11, and further discloses wherein the extracting of the multiple fingerprints includes: obtaining multiple video frames corresponding to the multiple videos, respectively; and extracting the multiple fingerprints based on the obtained multiple video frames (Stathacopoulos, para. [0114]).
Regarding claim 13, the combination of Stathacopoulos, Arora and Knapp discloses the operation method of claim 11, and further discloses wherein the extracting of the multiple fingerprints includes: obtaining a video frame of the mixed video from the mixed video; obtaining multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video; and extracting the multiple fingerprints based on the multiple video frames (Stathacopoulos, para. [0114]; “Control circuitry 304 may then isolate the elements of the image that comprise device indicator 506 from the other elements of the image, and capture a fingerprint of only the elements of device indicator 506.” Isolating is obviously similar to cropping.).
Regarding claim 14, the combination of Stathacopoulos, Arora and Knapp discloses the operation method of claim 13, and further discloses wherein the generating of the mixed video includes: generating the mixed video based on screen split information for the multiple videos (Stathacopoulos, paras. [0075] and [0087]; “Multiple tuners may be provided to handle simultaneous tuning functions (e.g., watch and record functions, picture-in-picture (PIP) functions, multiple-tuner recording, etc.).” Picture-in-picture functions will obviously have screen split information.), and the extracting of the multiple fingerprints includes: obtaining multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video according to the screen split information (Stathacopoulos, Fig. 5, elements 502, 504 and 506, paras. [0105]-[0106]; the extraction of multiple fingerprints could obviously occur during display of a picture-in-picture.).
Regarding claim 15, the combination of Stathacopoulos, Arora and Knapp discloses a non-transitory computer-readable recording medium having recorded thereon a program for executing the operation method of claim 11, on a computer (See the rejection of claim 11, above).
Claims 2-5, 9 and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Stathacopoulos et al. (Pub. No.: US 2017/0118512) in view of Arora (Pub. No.: US 2020/0082279), Knapp et al. (Pub. No.: US 2013/0232194) and Yen (Pub. No.: US 2020/0314507).
Regarding claim 2, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, but it could be argued that the combination does not explicitly disclose wherein the at least one processor is configured execute the one or more instructions to: obtain multiple video frames corresponding to the multiple videos, respectively, based on the processed multiple video signals, and extract the multiple fingerprints based on the obtained multiple video frames. However, in analogous art, Yen discloses a system for identifying altered content, wherein “the system locates a plurality of content items that match the fingerprint (para. [0054]),” and “the system may identify that the first unverified content item has been inserted into another content item as a picture-in-picture (PiP) inset. The system may determine that frames from the PiP inset should be used for comparison. The system may therefore crop the content item down to just the PiP inset. The system may additionally or alternatively normalize the quality of the content items so that each content item has the same resolution (para. [0054]).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for the processor to obtain multiple video frames corresponding to the multiple videos, respectively, based on the processed multiple video signals, and extract the multiple fingerprints based on the obtained multiple video frames. This would have produced predictable and desirable results, in that it would allow for the system to operate as intended under different display parameters, which could improve the usefulness of the system.
Regarding claim 3, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, but it could be argued that the combination does not explicitly disclose wherein the at least one processor is configured to execute the one or more instructions to: obtain a video frame of the mixed video from the mixed video, obtain multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video, and extract the multiple fingerprints based on the multiple video frames. However, in analogous art, Yen discloses a system for identifying altered content, wherein “the system locates a plurality of content items that match the fingerprint (para. [0054]),” and “the system may identify that the first unverified content item has been inserted into another content item as a picture-in-picture (PiP) inset. The system may determine that frames from the PiP inset should be used for comparison. The system may therefore crop the content item down to just the PiP inset. The system may additionally or alternatively normalize the quality of the content items so that each content item has the same resolution (para. [0054]).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for the processor to obtain a video frame of the mixed video from the mixed video, obtain multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video, and extract the multiple fingerprints based on the multiple video frames. This would have produced predictable and desirable results, in that it would allow for the system to operate as intended under different display parameters, which could improve the usefulness of the system.
Regarding claim 4, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, and further discloses wherein the at least one processor is configured to execute the one or more instructions to: generate the mixed video based on screen split information for the multiple videos (Stathacopoulos, paras. [0075] and [0087]; “Multiple tuners may be provided to handle simultaneous tuning functions (e.g., watch and record functions, picture-in-picture (PIP) functions, multiple-tuner recording, etc.).” Picture-in-picture functions will obviously have screen split information.), but it could be argued that the combination does not explicitly disclose wherein the at least one processor is configured to execute the one or more instructions to obtain a video frame of the mixed video from the mixed video, obtain multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video according to the screen split information, and extract the multiple fingerprints based on the multiple video frames. However, in analogous art, Yen discloses a system for identifying altered content, wherein “the system locates a plurality of content items that match the fingerprint (para. [0054]),” and “the system may identify that the first unverified content item has been inserted into another content item as a picture-in-picture (PiP) inset. The system may determine that frames from the PiP inset should be used for comparison. The system may therefore crop the content item down to just the PiP inset. The system may additionally or alternatively normalize the quality of the content items so that each content item has the same resolution (para. [0054]).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for the processor to obtain a video frame of the mixed video from the mixed video, obtain multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video according to the screen split information, and extract the multiple fingerprints based on the multiple video frames. This would have produced predictable and desirable results, in that it would allow for the system to operate as intended under different display parameters, which could improve the usefulness of the system.
Regarding claim 5, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, but it could be argued that the combination does not explicitly disclose wherein the at least one processor is configured to execute the one or more instructions to: obtain a video frame of the mixed video from the mixed video, detect at least one border line between the multiple videos in the video frame of the mixed video, obtain multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video based on the detected at least one border line, and extract the multiple fingerprints based on the multiple video frames. However, in analogous art, Yen discloses a system for identifying altered content, wherein “the system locates a plurality of content items that match the fingerprint (para. [0054]),” and “the system may identify that the first unverified content item has been inserted into another content item as a picture-in-picture (PiP) inset. The system may determine that frames from the PiP inset should be used for comparison. The system may therefore crop the content item down to just the PiP inset. The system may additionally or alternatively normalize the quality of the content items so that each content item has the same resolution (para. [0054]).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for the at least one processor to be configured to execute the one or more instructions to obtain a video frame of the mixed video from the mixed video, detect at least one border line between the multiple videos in the video frame of the mixed video, obtain multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video based on the detected at least one border line, and extract the multiple fingerprints based on the multiple video frames. This would have produced predictable and desirable results, in that it would allow for the system to operate as intended under different display parameters, which could improve the usefulness of the system.
Regarding claim 9, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, but it could be argued that the combination does not explicitly disclose further comprising: an audio output interface, wherein the at least one processor is configured to execute the one or more instructions to: identify a video with which sound is output from the audio output interface from among the multiple videos, and obtain the multiple pieces of matching information for the multiple fingerprints by setting a preset weight for matching information for the identified video. However, in analogous art, Yen discloses that “[t]he system may first generate a fingerprint for an unverified audio clip (e.g., audio clip 310, audio clip 314, or audio clip 318). The system may then search through a database (e.g., media content source 602), the Internet, or another source for a reference audio clip with a similar or matching fingerprint. The system may run comparisons between each unverified audio clip and the reference audio clip (e.g., audio clip 308, audio clip 312, and audio clip 316). The system may compare the shape of the profile, the strength of the volume at each given time, lyrics identified in the metadata, and any other identifying factors for each audio clip. The system may scale the profiles to the same strength, volume, style, or other factor before performing the comparison. For example, if the system receives the audio profiles from different sources, the profiles may be displayed, stored, or played back differently. The system may first run a normalizing process on the audio profiles in order to convert them to the same format for comparison. In the first comparison (e.g., comparison 302), the system compares a reference profile (e.g., audio profile 308) and an unverified profile (e.g., audio profile 310). Based on analyzing the shapes, volumes, lyrics, and other factors, the system may determine that the profiles (e.g., audio profile 308 and audio profile 310) do not contain any matching portions. The system may therefore determine that the audio has been significantly altered in a way that is not intended to deceive a listener. For example, a song may have been remixed, dubbed, used as a background track, or turned into a parody. The system may therefore determine that the content has been altered in an acceptable manner and may assign a high veracity score or no veracity score at all (para. [0027]).” Yen further discloses that “when the system compares a frame from another content item (e.g., frame 110) with a reference frame, the system may identify a mismatch. The system may identify that an object in the frame has been altered. For example, frame 110 contains object 116, which has been altered to read “DON'T VOTE!” instead of “GO VOTE!” The system may determine the importance of this alteration to the frame and to the content item. For example, the system calculates the percentage of the area of the frame that has been altered. Additionally or alternatively, the system may analyze the metadata to determine if the altered object has been tagged as important or unimportant. Based on the system's determination, the system may generate for display an indication of the extent to which the frame has been altered. For example, the system determines that the change from “GO VOTE!” to “DON'T VOTE!” is significant and may therefore score the veracity of the content item as 33% (e.g., indication 124). In another example, the system may determine a less significant mismatch between a frame of a content item (e.g., frame 112) and a frame of a reference item. The system may identify that most objects in the frame (e.g., object 118) match the objects in the reference frame. The system may identify an object (e.g., object 120) that does not appear in the reference frame. The system may calculate a percentage of the area of the frame that the object covers, compare the object to objects in an external database (e.g., media content source 602) to identify the meaning of the object, determine if the object covers any important objects that match the objects in the reference frame, and perform a series of other analyses. Based on these analyses, the system may determine that the addition of object 120 does not significantly alter the frame. The system may then display a higher score (e.g., indication 126) for the veracity of the content item. Based on the indications associated with each content item (e.g., indications 122, 124, and 126), a user may select which content item to view. If accuracy is a deciding factor, the user may choose to watch content item 102. However, if the user identifies a content item with a lower veracity score (e.g., content items 104 or 106) as a spoof or parody, the user may opt to view a content item with a lower veracity score because the content item may be more appealing to the user by other standards (paras. [0024] and [0025]),” wherein determining a veracity score can be seen as using weighting. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for an audio output interface, wherein the at least one processor is configured to execute the one or more instructions to: identify a video with which sound is output from the audio output interface from among the multiple videos, and obtain the multiple pieces of matching information for the multiple fingerprints by setting a preset weight for matching information for the identified video. This would have produced predictable and desirable results, in that it would allow for a more precise match, by using both audio and video comparisons, while also allowing the system to determine an indication of how accurate a certain match was, which could increase user confidence with the system.
Regarding claim 12, the combination of Stathacopoulos, Arora and Knapp discloses the operation method of claim 11, but it could be argued that the combination does not explicitly disclose wherein the extracting of the multiple fingerprints includes: obtaining multiple video frames corresponding to the multiple videos, respectively; and extracting the multiple fingerprints based on the obtained multiple video frames. However, in analogous art, Yen discloses a system for identifying altered content, wherein “the system locates a plurality of content items that match the fingerprint (para. [0054]),” and “the system may identify that the first unverified content item has been inserted into another content item as a picture-in-picture (PiP) inset. The system may determine that frames from the PiP inset should be used for comparison. The system may therefore crop the content item down to just the PiP inset. The system may additionally or alternatively normalize the quality of the content items so that each content item has the same resolution (para. [0054]).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for obtaining multiple video frames corresponding to the multiple videos, respectively, based on the processed multiple video signals, and extracting the multiple fingerprints based on the obtained multiple video frames. This would have produced predictable and desirable results, in that it would allow for the system to operate as intended under different display parameters, which could improve the usefulness of the system.
Regarding claim 13, the combination of Stathacopoulos, Arora and Knapp discloses the operation method of claim 11, but it could be argued that the combination does not explicitly disclose wherein the extracting of the multiple fingerprints includes: obtaining a video frame of the mixed video from the mixed video; obtaining multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video; and extracting the multiple fingerprints based on the multiple video frames. However, in analogous art, Yen discloses a system for identifying altered content, wherein “the system locates a plurality of content items that match the fingerprint (para. [0054]),” and “the system may identify that the first unverified content item has been inserted into another content item as a picture-in-picture (PiP) inset. The system may determine that frames from the PiP inset should be used for comparison. The system may therefore crop the content item down to just the PiP inset. The system may additionally or alternatively normalize the quality of the content items so that each content item has the same resolution (para. [0054]).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for obtaining a video frame of the mixed video from the mixed video, obtaining multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video, and extracting the multiple fingerprints based on the multiple video frames. This would have produced predictable and desirable results, in that it would allow for the system to operate as intended under different display parameters, which could improve the usefulness of the system.
Regarding claim 14, the combination of Stathacopoulos, Arora and Knapp discloses the operation method of claim 11, wherein the generating of the mixed video includes: generating the mixed video based on screen split information for the multiple videos (Stathacopoulos, paras. [0075] and [0087]; “Multiple tuners may be provided to handle simultaneous tuning functions (e.g., watch and record functions, picture-in-picture (PIP) functions, multiple-tuner recording, etc.).” Picture-in-picture functions will obviously have screen split information.), but it could be argued that the combination does not explicitly disclose the extracting of the multiple fingerprints includes: obtaining multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video according to the screen split information, and extracting the multiple fingerprints based on the multiple video frames. However, in analogous art, Yen discloses a system for identifying altered content, wherein “the system locates a plurality of content items that match the fingerprint (para. [0054]),” and “the system may identify that the first unverified content item has been inserted into another content item as a picture-in-picture (PiP) inset. The system may determine that frames from the PiP inset should be used for comparison. The system may therefore crop the content item down to just the PiP inset. The system may additionally or alternatively normalize the quality of the content items so that each content item has the same resolution (para. [0054]).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for the extracting of the multiple fingerprints includes: obtaining multiple video frames corresponding to the multiple videos, respectively, by cropping the video frame of the mixed video according to the screen split information, and extracting the multiple fingerprints based on the multiple video frames. This would have produced predictable and desirable results, in that it would allow for the system to operate as intended under different display parameters, which could improve the usefulness of the system.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Stathacopoulos et al. (Pub. No.: US 2017/0118512) in view of Arora (Pub. No.: US 2020/0082279), Knapp et al. (Pub. No.: US 2013/0232194) and Ives et al. (Pub. No.: US 2014/0366052).
Regarding claim 8, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, wherein in the displayed mixed video, the multiple video signals are displayed in corresponding split screen areas, respectively (Stathacopoulos, paras. [0075] and [0087]; “Multiple tuners may be provided to handle simultaneous tuning functions (e.g., watch and record functions, picture-in-picture (PIP) functions, multiple-tuner recording, etc.).”), but it could be argued that Stathacopoulos and Arora do not explicitly disclose the at least one processor is configured to execute the one or more instructions to: determine multiple weights for the multiple pieces of matching information, respectively, based on sizes of screen split areas, and apply the determined multiple weights to the multiple pieces of matching information, respectively, to thereby obtained weighted multiple pieces of matching information, and the recommended content is based on the each of the weighted multiple pieces of matching information. However, in analogous art, Ives discloses that “a content weight analyzer (depicted as 146 in FIG. 4) may also be included in the analyzer (depicted as 140 in FIG. 4). The content weight analyzer assigns a weight to the known text, wherein the weight defines a measure of how prominently the known text appeared on-screen in the video content. Various aspects may be used to determine this weight, including, but not limited to, on-screen relative size (e.g., percentage of the screen/frame that the known text occupies), on-screen duration (e.g., how long the known text appears on screen), and on-screen contrast (e.g., was the known text displayed with high contrast or watermarked in the video frame). The weight measurement is then stored in the storage 112 for later use by the server(s) 100 in conducting social media analytics (para. [0053]),” which teaches that on-screen images may be weighted based on factors such as a relative size or percentage of the screen which they encompass. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for the at least one processor to be configured to execute the one or more instructions to: determine multiple weights for the multiple pieces of matching information, respectively, based on sizes of screen split areas, and apply the determined multiple weights to the multiple pieces of matching information, respectively, to thereby obtained weighted multiple pieces of matching information, and the recommended content is based on the each of the weighted multiple pieces of matching information. This would have produced predictable and desirable results, in that it would allow the system to base recommendation on how prevalent on the display the relevant matching information was, which could increase the accuracy and effectiveness of the recommendations.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Stathacopoulos et al. (Pub. No.: US 2017/0118512) in view of Arora (Pub. No.: US 2020/0082279), Knapp et al. (Pub. No.: US 2013/0232194) and Aberman et al. (Pub. No.: US 2023/0370663).
Regarding claim 10, the combination of Stathacopoulos, Arora and Knapp discloses the display device of claim 1, but it could be argued that the combination does not explicitly disclose wherein the multiple pieces of matching information include at least one of genre information for the multiple videos and channel information for the multiple videos. However, in analogous art, Aberman discloses that “[c]arrying out a data enrichment from web sources can require content identification across multiple web sources. Data available for such content identification can be very limited (e.g., only using content name). The forecasting system can use a content finder and/or matcher algorithm based on multiple web sources that tries to find similar aired content based on a series of attributes being evaluated (e.g., similar channel, similar date & time, similar year of release, similar genres, similar cast, similar director). The output of this process can be matched pointers to the content in multiple web sources that can be used for data enrichment (para. [0039]),” which teaches that a similarity between both channels and genres can be used to find similar content. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Stathacopoulos, Arora and Knapp to allow for the multiple pieces of matching information to include at least one of genre information for the multiple videos and channel information for the multiple videos. This would have produced predictable and desirable results, in that it would allow for even more relevant information to be used to help improve the quality of the match.
Response to Arguments
Applicant’s arguments with respect to all claims have been considered but are moot in view of the new grounds of rejection in view of Knapp.
Conclusion
Claims 1-15 are rejected.
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/Joshua D Taylor/Primary Examiner, Art Unit 2426 May 1, 2026
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