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 .
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nguyen (US 20180349946 A1).
Regarding claims 18, 1, 11,
Nguyen teaches:
A system comprising a processor set, one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media,(Nguyen ¶5 “In a further aspect, an embodiment of a system, apparatus, or network platform is disclosed which comprises, inter alia, suitable hardware such as processors and persistent memory having program instructions for executing an embodiment of the methods set forth herein.”) the program instructions executable to: obtain information associated with a user's environment, wherein the information includes: (i) user actions (Nguyen Abstract “The system is operative for receiving real world object identification and spatial mapping data relative to a plurality of real world scenarios sensed in respective AR sessions engaged by corresponding users using a plurality of AR devices.” ¶26 “For example, the FOV may be constantly changing in relation to the head/ocular movement of the user as well as depending on whether or not the user is also moving (i.e., walking, running, etc.).” ¶39 “the consumer interactive behavior may be detected, monitored or otherwise determined based on a variety of dynamic and static components, including but not limited to, gaze behavior, eye/pupil tracking (e.g., pupil dilation, etc.), click behavior (e.g., selecting or highlighting an ad using an input device such as a mouse, digital glove, microphone, etc.), voice command inputs, bio/physiological cues, and the like.” Note: Nguyen teaches a large variety of user actions have info collected on them such as head and eye movements, walking, running, interacting with an input device like a mouse, microphone, etc…), (ii) environmental factors, (¶30 “Other third-party data sources 122 may comprise or provide additional information relative to the subscribers' geolocations, e.g., ambient environmental/weather or climate data, news, and other location-based data. One skilled in the art will recognize that these various additional data sources 122, 124, 126 may be disposed or deployed at different parts or nodes of the AR network architecture 100”) and (iii) surface context within the user's field of view;(¶26 “detect or otherwise identify surfaces and objects in the real world environment perceived in a FOV of the client AR/MR device 102. In one example embodiment, SMS 110 is further operative to map the physical objects, i.e., where they are relative to one another in the FOV … Essentially, the SMS module 110 is configured to perform spatial mapping of the physical environment in order to understand where the objects are in the real world and how the environment is laid out (e.g., surfaces and spaces, relative distances and orientations in a 2D/3D view) and provide the spatial mapping data to the ARNAP node 112” Note: Surface context in an AR/MR environment refers to the environmental and geometric info that defines the physical surfaces in the environment. Nguyen teaches that not only are surfaces mapped to understand their relative distances and the environment layout, but specifically teaches that the surfaces identified and processed are in the user’s FOV.) generate potential spatial and display contexts by modeling possible variations and customizations within an immersive environment based on the information associated with a user's environment, wherein the immersive environment is being viewed by the user; (Nguyen ¶7 “Beneficial features of an embodiment of the present invention may include but not limited to one or more of the following: (i) the disclosed AR ad placement architecture is configured to learn the environment and detect objects that would match the relevant products and services to be advertised, in addition to identifying possible locations for those ads to be placed; (ii) the AR ad placement architecture allows for placement rules to be applied so the sponsored product(s) may be placed in a way that the experience of the consumer is not disrupted (i.e., the sponsored products look like native content in their natural “habitat”); (iii) the AR ad placement architecture may be configured to take into consideration consumer data for personalized native ad experience (i.e., two different consumers in the same environment may see different ads or views of the same ad); (iv) the AR ad placement architecture allows a natural integration within current ad exchange market” ¶38 “A placement module, sub-system or sub-module 252 is operative to receive or otherwise obtain a number of inputs, exemplified as a list of ads to be placed (i.e., AR ad content) 254, AR environmental data 256 relative to subscribers' AR environments, subscriber/consumer profile data 258, ad policy management data 259, as well as various pieces of other, possibly third-party data” ¶45 “As described previously, output of the placement module 252 preferably comprises the list of native ads 262 to be placed in respective AR environments. In one arrangement, such output 262 may include a single placement option per ad or a list of possible placement locations per ad. Skilled artisans will recognize that other variations, alternatives, modifications, and the like (e.g., geolocation targeting, subscriber targeting, AR content-specific ad selection, etc.) with respect to the output list 262 are possible within the scope of the present invention” Note: Nguyen teaches generating different possible spatial/display info to change the spatial/display context of the immersive AR environment. Nguyen specifically teaches that different possible ad at different possible display locations can be displayed to the user. Nguyen in ¶7 it is taught that the ads are placed “natively” in the environment to give the appearance that they are in a “natural habitat” and do not clash with the immersive environment. Other than the spatial context of the environment playing a part in determining possible variations and customizations to the environment in the form of inserted ad content, Nguyen in ¶45 teaches that further environmental info like geolocation and third party info (previously clarified to include things such as weather info) can be used to determine an output list of possible content to display.) generate, based on the potential spatial and display contexts, a customized immersive visual display;(Nguyen ¶7, cited above, not only teaches that the new info inserted is based on the spatial and display contexts, but can also be customized to specific users. Nguyen ¶45 further teaches that the content displayed in the immersive AR environment can be further customized based on other context like geolocation, environmental info, etc…) and present the immersive visual display within the immersive environment to provide an immersive visual display experience.(Nguyen ¶7 and ¶45, cited previously, teach that the generating potential spatial and display contexts by modelling possible variations within the immersive AR environment is done specifically to present one of these possible variations (which can be different possible ads, placement locations of ads, and style of displaying ads, etc…) to a user in the AR environment.)
Regarding claims 19, 4, 12,
Nguyen teaches:
The system of claim 18, wherein the program instructions are executable to further modify the immersive visual display as the information associated with the user's environmental changes.(Nguyen ¶97 “Whereas in a pure VR environment the content is already predetermined, and therefore ad placement can also be determined in advance, the AR environments can be dynamically changing, thus requiring real-time object identification and spatial mapping.” ¶30 “Other third-party data sources 122 may comprise or provide additional information relative to the subscribers' geolocations, e.g., ambient environmental/weather or climate data, news, and other location-based data. One skilled in the art will recognize that these various additional data sources 122, 124, 126 may be disposed or deployed at different parts or nodes of the AR network architecture 100, and may therefore be provided with appropriate communication networks 130 for communicating with ARNAP 112.” ¶38 “A placement module, sub-system or sub-module 252 is operative to receive or otherwise obtain a number of inputs, exemplified as a list of ads to be placed (i.e., AR ad content) 254, AR environmental data 256 relative to subscribers' AR environments, subscriber/consumer profile data 258, ad policy management data 259, as well as various pieces of other, possibly third-party data” Note: Nguyen ¶38 teaches that “third-party data” may influence potential changes to the spatial/display context, where the potential changes are different ads displayed in different ways. Nguyen ¶30 clarifies that this “third-party data” can be defined as “environmental/weather or climate data”, and ¶97 further clarifies that when content is “determined” for an AR environment it is not fixed and can instead change dynamically. Thus, Nguyen teaches that a dynamically changing immersive AR environment that can be changed based on environmental data.)
Regarding claims 20, 5, and 13,
Nguyen teaches:
The system of claim 18, wherein the program instructions are executable to further obtain information related to the user and using the information related to the user(Nguyen ¶38 “A placement module, sub-system or sub-module 252 is operative to receive or otherwise obtain a number of inputs, exemplified as a list of ads to be placed (i.e., AR ad content) 254, AR environmental data 256 relative to subscribers' AR environments, subscriber/consumer profile data 258, ad policy management data 259, as well as various pieces of other, possibly third-party data 260, at least part of which inputs may be mediated via ARNAP 112 where APMS 200B is deployed as a separate network entity.” Note: Nguyen teaches that user information such as subscriber or consumer data about the user may be obtained from third party sources and used to determine how to customize the immersive visual display by placing ad content custom to the environment and user information.) and the information associated with the user's environment in generating the customized immersive visual display.(Nguyen ¶97, cited previously, teaches that the immersive AR environment being displayed to the user is dynamically changing, and is not determined once like a VR environment. As Nguyen ¶38 teaches that part of determining the environment involves obtaining user information, like subscriber/consumer profile data, to determine changes based on the user info, Nguyen teaches that the process of obtaining user information and using it to determine the environment by customizing it can be done multiple times.)
Regarding claims 2, 16,
Nguyen teaches:
The computer-implemented method of claim 1, wherein the environmental factors comprise one or more selected from the group consisting of weather conditions, location, future weather forecast, lighting, time of day, and artificially adjusted conditions. (Nguyen ¶30 “Other third-party data sources 122 may comprise or provide additional information relative to the subscribers' geolocations, e.g., ambient environmental/weather or climate data, news, and other location-based data. One skilled in the art will recognize that these various additional data sources 122, 124, 126 may be disposed or deployed at different parts or nodes of the AR network architecture 100, and may therefore be provided with appropriate communication networks 130 for communicating with ARNAP 112.” ¶24 “With respect to the sensory devices 104-1 to 104-N, example devices may include but not limited to cameras, microphones, accelerometers, Global Positioning System (GPS) locators, touch sensors, mood sensors, temperature sensors,” Note: Nguyen teaches its environmental data is based on the user’s geolocation, and is specifically “environmental/weather or climate data”, also teaching that temperature data can be directly obtained from a sensor. Thus, Nguyen teaches the claims language that weather conditions and location data comprise the environmental data.)
Regarding claims 3, 17,
Nguyen teaches:
The computer-implemented method of claim 1, wherein the surface contexts comprise one or more selected from the group consisting of polygons, vectors, space, and depth of objects. (Nguyen ¶26 “techniques may be employed for performing spatial mapping of the physical objects (e.g., using depth/perception sensors, movement sensors, etc.)” Note: Nguyen teaches that surface contexts, the info/context that makes up the surfaces in the immersive environment, can be determined by depth of objects in the room.)
Regarding claim 6,
Nguyen teaches:
The computer-implemented method of claim 1, wherein the information associated with the user's environment is obtained from one or more selected from the group consisting of LIDAR, a camera, and a microphone. (Nguyen ¶24 “With respect to the sensory devices 104-1 to 104-N, example devices may include but not limited to cameras, microphones, accelerometers, Global Positioning System (GPS) locators, touch sensors, mood sensors, temperature sensors,”)
Regarding claim 7,
Nguyen teaches:
The computer-implemented method of claim 1, wherein the generating a customized immersive visual display comprises selecting one of the one or more potential spatial and display contexts based on preset requirements. (Nguyen ¶32 “In an example implementation, APMS 114 may be provided with configurable rules (e.g., policy-based) for native ad placement. For example, if the objective is to place an ad for a pair of running shoes (that is, assuming that ACMS/SSP 116 is configured to provide or fill one or more suitable locations for the shoes from a shoe supplier based on an exchange-mediated ad transaction), APMS 114 may be configured to identify matching objects that represent suitable placeholders for the shoes ad in the real world environment of an AR/MR environment. In an illustrative scenario, the rules-based recommendations from APMS 114 may contain other details such as placing the advertisement next to real world shoes in an empty space (i.e., devoid of a physical object, or separate from other physical objects by a predetermined marginal space, etc.). In accordance with the teachings of the present invention, ARNAP 112 is operative to compile the recommendations received from APMS 112 and determine an optimal decision as to which ads to be placed and where to place them.” Note: Nguyen teaches that the generating of customized immersive displays can be done by selecting spatial and display contexts based on preset requirements. Here, there preset requirements are configurable rules, or policies, that determine how content that will customize the immersive display (ads placed in the AR environment) will be placed. The preset requirements dictating how the ad will be placed are taught to specifically be based on spatial contexts. In the provided example the system examines the context of the scene to identify objects, and find an acceptable “empty space” that is a predefined marginal space away from the objects to place content in.)
Regarding claims 8, 14,
Nguyen teaches:
The computer-implemented method of claim 1, further comprising logging the immersive visual display experience. (Nguyen ¶39 “By way of example, the consumer interactive behavior may be detected, monitored or otherwise determined based on a variety of dynamic and static components, including but not limited to, gaze behavior, eye/pupil tracking (e.g., pupil dilation, etc.), click behavior (e.g., selecting or highlighting an ad using an input device such as a mouse, digital glove, microphone, etc.), voice command inputs, bio/physiological cues, and the like. One skilled in the art will recognize that various techniques such as, e.g., “big data” analytics, machine learning, artificial intelligence, neural networks, fuzzy logic learning, pattern recognition and related techniques may be employed in a suitable combination or sub-combination with respect to effectuating a learning process as part of the learning module 268. Responsive to the inputs 262, 264, 266, the learning module 268 is operative to generate appropriate feedback control signals as output 270 that can be fed back as adjustments or refinements to the placement module 252” Note: Nguyen teaches that the visual display experience can be logged, specifically how the user interacts with the immersive visual display experience such as gaze behacior, what they click one, etc… It is known that this data is not just observed once and is actually stored/logged as it is taught that this data can be used as a training data set to provide to a machine learning model.)
Regarding claim 9, 15,
Nguyen teaches:
The computer-implemented method of claim 8, wherein the logging comprises recording one or more selected from the group consisting of user's gaze time, dwell time, user's interaction with the immersive visual display, and user's purchasing based on the immersive visual display.(Nguyen ¶39, cited above, teaches specifically that the user’s interaction with the immersive visual display is logged, citing specific interactions such as “click behavior (e.g., selecting or highlighting an ad using an input device such as a mouse, digital glove, microphone, etc.), voice command inputs,”.)
Regarding claim 10,
Nguyen teaches:
The computer-implemented method of claim 1, wherein the immersive environment is displayed on one or more selected from the group consisting of a computer, a smartphone, a tablet, a headset, and smart glasses. (Nguyen ¶21 “For purposes of one or more embodiments of the present invention, an example client device may therefore comprise any known or heretofore unknown AR/MR device including such as, e.g., a Google Glass device, Microsoft HoloLens device, etc., as well as holographic computing devices,” Note: Nguyen teaches that the client device for AR, the means through which the immersive environment is displayed, includes smart glasses such as the Google Glass and Microsoft HoloLens.)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALAN GREGORY HAKALA whose telephone number is (571)272-7863. The examiner can normally be reached 8:00am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, King Poon can be reached at (571) 270-0728. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALAN GREGORY HAKALA/Examiner, Art Unit 2617 /KING Y POON/Supervisory Patent Examiner, Art Unit 2617
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