Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
DETAILED ACTION
This office action is responsive to application No. 18/922,007 filed on 05/07/2026. Claim(s) 7-8 have been cancelled. Claim(s) 1-6 and 9-22 is/are pending and have been examined.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/07/2026 has been entered.
Priority
Based on the pending claim limitation(s) presented. Support for the limitation(s) including, but not limited to “user agreed to participate in a media viewership measurement study”, could not be found in now abandoned parent application 13/552,579.
However, mention of “user agreed to participate in a media viewership measurement study” is found in subsequent parent application 13/831,259 now US Patent 10,034,049.
Therefore, the earliest priority date for the pending application is 03/14/2013.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-6 and 9-22 have been considered but are moot in view of the new ground(s) of rejection.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claim(s) 1-4, 6, 9-12, 14-18, 20, and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Burger et al. (US 2012/0324494), in view of Oh et al. (US 2014/0053173), in view of Conness et al. (US 2014/0176813), in view of Strat et al. (US 2010/0046797), and further in view of Nozaki (US 2009/0185033).
Consider claims 1, 9, and 15, Burger teaches a method, electronic device, and non-transitory computer-readable medium comprising computer executable instructions that, when executed by a processor, cause the processor to perform a method comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions for (Paragraph 0063-0069):
determining, by a client system, that a first user agreed to participate in a media viewership study (Paragraph 0020-0021 teaches collecting sensor data at the video viewing environment sensor. Paragraph 0022 teaches the viewer may elect to participate by opting-in, to provide various information described herein, including emotional response information);
displaying, on the client system, media content for viewing by the first user of the client system; an event list associated with the media content (Fig.1, Paragraph 0011 teaches viewers shown watching advertisements. Fig.3, Paragraph 0025 teaches a time sequence of various events, scenes, and actions occurring within the advertisement. Where time index 1 to time index T, corresponds to scenes 1 to scene Z in an advertisement);
based on the first user agreeing to participate in the media viewership study: gathering, physical indicia information associated with the first user while viewing the media content (Paragraph 0009 teaches utilizing viewing environment sensors, such as image sensors, depth sensors, acoustic sensors, and potentially other sensors such as motion and biometric sensors. Such sensors may allow systems to identify individuals, detect and understand human emotional expressions, and provide real-time feedback while a viewer is watching video. Based on such feedback, an entertainment system may determine a measure of a viewer's enjoyment of the advertisement, and provide real-time responses to the perceived viewer emotional responses. Paragraph 0020-0021 teaches collecting sensor data at the video viewing environment sensor. Paragraph 0022 teaches the viewer may elect to participate by opting-in, to provide various information described herein, including emotional response information);
correlating the physical indicia information to events included in the event list (Paragraph 0024 teaches viewer emotional response profile 304 is generated by a semantic mining module 302 running on one or more of media computing device 104 and server computing device 130 using sensor information received from one or more video viewing environment sensors. Using emotional response data from the sensor and also advertisement information 303, e.g., metadata identifying a particular advertisement the viewer was watching when the emotional response data was collected and where in the advertisement the emotional response occurred, semantic mining module 302 generates viewer emotional response profile 304, which captures the viewer's emotional response as a function the time position within the advertisement. Paragraph 0025 teaches semantic mining module 302 assigns emotional identifications to various behavioral and other expression data (e.g., physiological data) detected by the video viewing environment sensors. Semantic mining module 302 also indexes the viewer's emotional expression according to a time sequence synchronized with the advertisement, for example, by times for various events, scenes, and actions occurring within the advertisement. Thus, in the example shown in FIG. 3, at time index 1 of an advertisement, semantic mining module 302 records that the viewer was bored and distracted based on physiological data, e.g., heart rate data, and human affect display data, e.g., a body language score. At later time index 2, viewer emotional response profile 304 indicates that the viewer was happy and interested in the advertisement, while at time index 3 the viewer was scared but her attention was raptly focused on the advertisement);
analyzing an interest of the first user in the media content using the physical indicia information (Paragraph 0028 teaches in embodiments in which an image sensor is included as a video viewing environment sensor, suitable eye tracking and/or face position tracking techniques may be employed, potentially in combination with a depth map of the video viewing environment, to determine a degree to which the viewer's attention is focused on the display device and/or the advertisement. Paragraph 0025 teaches indexing the viewer's emotional expression according to a time sequence synchronized with the advertisement, for example, by times for various events, scenes, and actions occurring within the advertisement. Thus, in the example shown in FIG. 3, at time index 1 of an advertisement, semantic mining module 302 records that the viewer was bored and distracted based on physiological data, e.g., heart rate data, and human affect display data, e.g., a body language score. At later time index 2, viewer emotional response profile 304 indicates that the viewer was happy and interested in the advertisement, while at time index 3 the viewer was scared but her attention was raptly focused on the advertisement. Viewer emotional response profile 304 is based on analysis of various environment sensors that determines user’s emotional interest for the particular event(s) within the advertisement);
providing, to a server system, the interest of the first user in the media content for inclusion in the media viewership study (Fig.3, Paragraph 0028 teaches an emotional response profile 304 for an advertisement in graphical form at 306. Paragraph 002 teaches receiving for a plurality of advertisements, emotional response profiles from each of a plurality of viewers. Paragraph 0033 teaches aggregating a plurality of emotional response profiles for the advertisements to form an aggregated emotional response profiles for those advertisements. Paragraph 0034 teaches aggregated emotional response profile 314, may help advertisement content creators to identify emotionally stimulating and/or interesting portions of an advertisement for a group of viewers at any suitable level of granularity. Paragraph 0009 teaches emotional responses of viewers to advertisements may be aggregated and fed to advertisement creators. For example, advertisement creators may receive information on campaigns and concepts that inspired viewer engagement with a brand, ads that inspired strong emotional reactions, and aspects of ads that inspired brand affinity by the viewer).
Burger does not explicitly teach displaying, on the client system, media content for viewing by the first user of the client system and a second user;
determining that the second user is an unknown user;
receiving a list of events in an event list associated with the media content;
transmitting, to the server system, presence information of the first user and presence information of the second user for including in a total count statistic; and
temporarily retaining information of the second user to avoid redundantly including the presence information of the second user in the total count statistic.
In an analogous art, Oh teaches displaying, on a client system, media content for viewing by a first user of the client system and a second user; determining that the second user is an unknown user; transmitting, to the server system, presence information of the first user and presence information of the second user for including in a total count statistic; including the presence information of the second user in the total count statistic (Paragraph 0036 teaches comparing face of the viewer with stored personal information to identify the viewer. Identified viewer may be largely classified into a registered viewer and an unregistered viewer. Registered viewer denotes a viewer whose personal information is previously stored in a data processing unit 112 through a registration procedure. For the unregistered viewer, the viewer information can not be found out only through its identification. Paragraph 0037 teaches collecting information on number of viewers who are viewing the broadcast program. Table 1, Paragraph 0043 teaches a total number of viewer is 5, the number of registered viewers, A1, A3, and A5, is 3, and thus the number of unregistered viewer is 2. For registered viewers, additional information about viewing behavior is stored as a lower record item. Paragraph 0045-0046 teaches data processing unit 112 delivering the viewing behavior data to the server 130).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Burger to include displaying, on a client system, media content for viewing by a first user of the client system and a second user; determining that the second user is an unknown user; transmitting, to the server system, presence information of the first user and presence information of the second user for including in a total count statistic; including the presence information of the second user in the total count statistic, as taught by Oh, for the advantage of improving on systems where reliability had previously depended on cooperation degree of the sample group, which required viewers to input their viewer information when multiple viewers were viewing a broadcast program (Oh – Paragraph 0008), allowing the system to compare and identify registered and unregistered viewers (Oh – Paragraph 0036), easily distinguishing different viewers, while also including all viewing users in the tally, giving a better reflection of amount of viewers, providing greater count accuracy.
Burger and Oh do not explicitly teach receiving a list of events in an event list associated with the media content;
temporarily retaining information of the second user to avoid redundantly including the presence information of the second user.
In an analogous art, Conness receiving a list of events in an event list associated with the media content (Paragraph 0086 teaches location, size, and/or shape of each display element may be defined using a coordinate system. Data describing location, size, and/or shape of the display elements in multiple video images may be associated with video image data or display element data. Paragraph 0087 teaches data structure of display elements may include a record for each display element. Display element records may contain information identifying which video images the display element is visible in and, for each of these video images, where the display element is located in the image. The video images may be identified using, for example, frame number or time. Paragraph 0088 teaches data structure may include a record for each video image. The video images may be identified using, for example, frame number or time. Paragraph 0091-0094 teaches several display elements that may be displayed on display 312, where display screen may contain different display elements with corresponding boundaries. Paragraph 0095 teaches boundaries may be defined using a coordinate system discussed above, where boundaries may be stored as part of the data structures described above in relation to Fig.6).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Burger and Oh to include receiving a list of events in an event list associated with the media content, as taught by Conness, for the advantage of identifying a part of the screen that the user is viewing, where user’s gaze point may indicate a person or item on the screen that the user is particularly interested in or engaged by (Conness – Paragraph 0001), enabling the system to finely discern user interest regarding different objects displayed onscreen, providing more detailed tracking data.
Burger, Oh, and Conness do not explicitly teach temporarily retaining information of the second user to avoid redundantly including the presence information of the second user.
In an analogous art, Strat teaches retaining information of a second user to avoid redundantly including presence information of the second user (Paragraph 0019 teaches aspects of invention include real-time or recorded TV audience monitoring for automatic estimation of various parameters, such as size, demographics, and dwell time of a TV audience. Paragraph 0022 teaches detecting human heads and tracking them over time, based on appearance and motion signature, so that individual person may be identified and counted. Accordingly, double counting of individuals can be avoided. Paragraph 0025 teaches generating a report of one or more people in the field of vision, duration of their appearance in the field of vision, gaze direction and duration, and the like. Paragraph 0030 teaches tracking number of times person enters/exits field of vision).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Burger, Oh, and Conness to include retaining information of a second user to avoid redundantly including presence information of the second user, as taught by Strat, for the advantage of providing an accurate counting per unit of time and space of one or more members (Strat – Paragraph 0008), so that double counting of individuals can be avoided (Strat – Paragraph 0022), ensuring greater accuracy in tracking/monitoring of viewers.
Burger, Oh, Conness, and Strat do not explicitly teach temporarily retaining information of the second user.
In an analogous art, Nozaki teaches temporarily retaining information of a second user (Paragraph 0090 teaches camera to perform photography to capture a photographic image. Paragraph 0092 teaches performing face extraction upon the photographic image. Paragraph 0094 teaches acquiring characteristic feature data from the facial region that has been extracted and temporarily storing the data that is acquired in a memory. A comparison is performed with a data base of reference images of registered persons registered in the data base. Paragraph 0095 makes a determines whether extracted face(s) matches with reference image(s) registered in the data base to a certain degree. Paragraph 0096 teaches no reference image registered in the data base that matches person B. Paragraph 0095, 0098-0099 teaches deleting from memory, the photographic image that was received, the characteristic feature data that was temporarily stored, and the normalized image(s) that were generated from this data).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Burger, Oh, Conness, and Strat to include temporarily retaining information of a second user, as taught by Nozaki, for the advantage of enabling the system to maintain memory systems, by storing information as necessary for use, as well as ridding itself of data that is no longer needed, enabling continued future usage without bogging down the system
Consider claims 2, 10, and 16, Burger, Oh, Conness, Strat, and Nozaki teach wherein the method further comprises:
receiving a facial image of the first user; and in response to determining that the first user agreed to participate in the media viewership study based on the facial image (Burger - Paragraph 0013 teaches video viewing environment sensor system 106 may include any suitable sensors, including but not limited to one or more image sensors, depth sensors, and/or microphones or other acoustic sensors. Paragraph 0021 teaches determining an identity of a viewer in the video viewing environment from the input of sensor data. In some embodiments, the viewer's identity may be established from a comparison of image data collected by the sensor data with image data stored in the viewer's personal profile. For example, a facial similarity comparison between a face included in image data collected from the video viewing environment and an image stored in the viewer's profile may be used to establish the identity of that viewer. Paragraph 0022 teaches the viewer may elect to participate by opting-in), identifying viewership data associated with the first user including (i) non-personally identifiable demographic information of the first user (Burger - Paragraph 0030), (ii) the presence information of the first user (Burger - Paragraph 0013, 0015, 0021, 0028), and (iii) information identifying the media content (Burger - Fig.3, Paragraph 0024-0025).
Consider claims 3, 11, and 17, Burger, Oh, Conness, Strat, and Nozaki teach wherein the client system further comprises a presence sensor (Burger - Paragraph 0013 teaches viewing environment sensor system 106 may include any suitable sensors, including but not limited to one or more image sensors, depth sensors, and/or microphones or other acoustic sensors); and
wherein the method further comprises detecting the first user and the second user by detecting, via the presence sensor, the presence information of the first user the presence information of the second user indicating that the first user and the second user are in proximity to the client system (Burger - Paragraph 0013, 0015, 0021, 0028; Oh – Paragraph 00036-0037, 0043-0046; Strat – Paragraph 0022, 0025).
Consider claims 4, 12, and 18, Burger, Oh, Conness, Strat, and Nozaki teach wherein the presence sensor is a camera device (Burger - Paragraph 0013 teaches viewing environment sensor system 106 may include any suitable sensors, including but not limited to one or more image sensors, depth sensors, and/or microphones or other acoustic sensors. Paragraph 0063 teaches computing system may include user devices such as cameras); and
wherein the method further comprises:
gathering the physical indicia information associated with the first user by analyzing at least one image captured by the camera device; identifying a body position of the first user based on the physical indicia information (Burger - Paragraph 0013, 0015); and
determining the interest of the first user in the media content based on the body position of the first user (Burger - Fig.3, Paragraph 0025 teaches a body language score, as well as attention of the user. Paragraph 0028 teaches determining viewer’s attention based on eye tracking and/or face position tracking techniques).
Consider claims 6, 14, and 20, Burger, Oh, Conness, Strat, and Nozaki teach wherein an event included in the event list further includes description information that includes at least one category for describing the event; and wherein analyzing an interest of the first user in the media content further includes determining that the at least one category for describing the event is of interest to the first user (Burger - Paragraph 0028 teaches in embodiments in which an image sensor is included as a video viewing environment sensor, suitable eye tracking and/or face position tracking techniques may be employed, potentially in combination with a depth map of the video viewing environment, to determine a degree to which the viewer's attention is focused on the display device and/or the advertisement. Paragraph 0025 teaches indexing the viewer's emotional expression according to a time sequence synchronized with the advertisement, for example, by times for various events, scenes, and actions occurring within the advertisement. Thus, in the example shown in FIG. 3, at time index 1 of an advertisement, semantic mining module 302 records that the viewer was bored and distracted based on physiological data, e.g., heart rate data, and human affect display data, e.g., a body language score. At later time index 2, viewer emotional response profile 304 indicates that the viewer was happy and interested in the advertisement, while at time index 3 the viewer was scared but her attention was raptly focused on the advertisement. Viewer emotional response profile 304 is based on analysis of various environment sensors that determines user’s emotional interest for the particular event(s) within the advertisement; Conness – Paragraph 0086-0088).
Consider claim 22, Burger, Oh, Conness, Strat, and Nozaki teach wherein determining that the second user is an unknown user comprises determining that physical indicia information associated with the second user while viewing the media content was not gathered (Oh – Paragraph 0043).
Claim(s) 5, 13, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Burger et al. (US 2012/0324494), in view of Oh et al. (US 2014/0053173), in view of Conness et al. (US 2014/0176813), in view of Strat et al. (US 2010/0046797), in view of Nozaki (US 2009/0185033), and further in view of Hammond (US 2014/0282645).
Consider claims 5, 13, and 19, Burger, Oh, Conness, Strat, and Nozaki do not explicitly teach wherein the method further comprises discarding the presence information of the first user and the presence information of the second user after a predetermined amount of time.
In an analogous art, Hammond teaches method further comprises discarding the presence information of the first user and the presence information of the second user after a predetermined amount of time (Paragraph 0019 teaches panelists refer to people who have agreed to have their media exposure monitored. Paragraph 0026 teaches people meter 108 counts the number of audience members. Paragraph 0020 teaches people meter captures an image of the audience and attempts to identify and/or identifies the audience member(s) based on the captured image. Paragraph 0044 teaches detecting images of the panelist 112 and/or other audience members in the monitored area 102. Paragraph 0036 teaches storage of information in a storage device or storage disk for any duration, e.g., for brief instances, for temporarily buffering, and/or for caching of information).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Burger, Oh, Conness, Strat, and Nozaki to include method further comprises discarding the presence information of the first user and the presence information of the second user after a predetermined amount of time, as taught by Hammond, for the advantage of effectively managing system resource(s), freeing up data storage systems of unnecessary data, making room for new data, enabling efficient use of system resources.
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Burger et al. (US 2012/0324494), in view of Oh et al. (US 2014/0053173), in view of Conness et al. (US 2014/0176813), in view of Strat et al. (US 2010/0046797), in view of Nozaki (US 2009/0185033), and further in view of Wick et al. (US 7,669,213)
Consider claim 21, Burger, Oh, Conness, Strat, and Nozaki teach wherein determining that the second user is an unknown user (Oh – Paragraph 00036-0037, 0043-0046), but do not explicitly teach comprises determining that the second user did not agree to participate in the media viewership study.
In an analogous art, Wick teaches comprises determining that a second user did not agree to participate in a media viewership study (Col 8: lines 49-65 teaches users when opted-in of participation may do so on a context by context basis, and to whom they want to share their presence information. Col 9: lines 20-23 teaches while user 105 views the television program, dynamic user identification system 420 may identify the user 105 other viewers 110 presently viewing the same program. Col 13: lines 39-47 teaches context database services may store and record information when an individual has opened a webpage within the online context 315. Similarly, the context record may be removed when the individual has closed the web page within the online context 315. Col 15: lines 45-50 teaches a total count of other individuals 110 within the Sports: NFL context 605. Col 19: lines 42-46 teaches a total count of viewers who are tuned to the currently tuned program, e.g., “Channel 52: Survivor”. Col 20: lines 35-46 teaches dynamic user identification system updates the context database services to reflex the new context corresponding to the channel, program, or television network when viewer selects one of the buttons 1250 or 1255, or otherwise interacts with television 1122 and/or set-top box 1102 in a manner that changes the channel, program, or television network. Client services 1105 updates the WhoIsWatching window 1200 accordingly to reflect the new channel, program, or television network. User is in proximity of device displaying media content, as dynamic user identification system and WhoIsWatching automatically updates context as user interacts with the display system. Col 5: lines 4-7 teaches context determination service 125 may determine online context 115 of the user 105 and communicate information indicative of the online context 115. Col 10: lines 8-12 teaches interface services 325 may communicate online activity of the user 105 or of the other individuals 110 to one or more WhoIsHere services 330 or support services 350 of the backend 323. Fig.4, Col 12: lines 18-38 teaches dynamic user identification system 420 is implemented using one or more context transaction services 435 and one or more context database services 440. Context transaction services 435 and one or more context database services 440 may or may not be incorporated within the same hardware and/or software device. Context transaction services 435 may determine information indicative of online presence and may communicate that information with the context database services 440).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Burger, Oh, Conness, Strat, and Nozaki to include comprises determining that a second user did not agree to participate in a media viewership study, as taught by Wick, for the advantage of enabling the system to better distinguish and separate what to do with user data belonging to two different groups, allowing for data handling to be better specified and conducted.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON K LIN whose telephone number is (571)270-1446. The examiner can normally be reached on Monday-Friday 9AM-5PM.
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/JASON K LIN/Primary Examiner, Art Unit 2425
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