DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 06/25/2026, 05/06/2026, 04/10/2026, 01/09/2026, 11/14/2025, 07/11/2025, 04/21/2025, and 02/27/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 12-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 12 specifies a computer-readable storage medium. Given the broadest reasonable interpretation consistent with the specification and state-of-the-art at the time of invention, the full scope of “computer readable storage medium” covers both non-transitory tangible media (e.g., RAM, ROM, hard drive) and transitory propagating signals (e.g., carrier waves, signals) per se. Transitory propagating signals do not fall within the definition of a process, machine, manufacture or composition of matter and therefore must be rejected under 35 U.S.C. 101 as covering non-statutory subject matter (See In re Nuijten, 500 F.3d 1346, 1356-57 (Fed. Cir. 2007) (transitory embodiments are not directed to statutory subject matter) and Interim Examination Instructions for Evaluating Subject Matter Eligibility Under 35 U.S.C. § 101, Aug. 24, 2009; p. 2.). The examiner suggests amending the claim to exclude transitory propagating signals, by adding a modifier, such as non-transitory to the claimed medium.
Claim Objections
Claims 10 and 13 are objected to because of the following informalities: “an other artificial reality system” should be “another artificial reality system”. Appropriate correction is required.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2 and 7-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. PGPubs 2019/00432259 to Wang et al. in view U.S. Patent US 10832484 to Silverstein et al., further in view of U.S. PGPubs 2023/0196681 to Madden et al..
Regarding claim 1, Wang et al. teach a method for automatically generating a boundary for an artificial reality experience (abstract), the method comprising:
automatically detecting, by an artificial reality system, characteristics of a first portion of a real-world environment by at least partially scanning the depth of objects, away from the artificial reality system, in the real-world environment within a fixed radius of the artificial reality system (par 0041-0042, “ the electronic device 100 performs automatic estimation of bounded areas/volumes using depth information from the imaging cameras 114, 116 and depth sensor 118 to generate a two-dimensional, virtual bounded floor plan within which the user 110 may move freely without colliding into objects within bedroom 500, such as the walls 122, 124, the bed 126, the desk 504, and/or the ceiling fan 506 ….the electronic device 100 uses depth information to estimate the location of the bedroom floor and ceiling height to locate obstruction-free areas suitable for VR/AR use. The automatic estimation of bounded areas/volume may be performed prior to immersing the user 110 in a VR environment. Such automatic estimation of bounded areas/volumes may be accomplished by providing feedback on the display 108 of the electronic device 100 instructing the user 110 to change the pose of the electronic device 100 (e.g., directing the user 110 to stand in the middle of bedroom 500 and turn 360 degrees such that the entire room is scanned) ….the electronic device 100 may present the VR environment for display without having scanned any portion of the bedroom 500 a priori. In such embodiments, the user 110 initiates a navigation session by picking up the electronic device 100 (i.e., wearing the HMD as illustrated) and the electronic device 100 dynamically scans the bedroom 500 as the user 110 navigates the VR environment. Additionally, the electronic device 100 may attempt to define a bounded area/volume according to a type of pose in space (e.g., standing, sitting at table, room-scale, roaming) or a size of space (e.g., dimensions for a minimum width, height, radius) required for the user 110 to navigate around in the VR environment”);
generating the boundary, for the artificial reality experience, based on the detected characteristics of the first portion of the real-world environment (Fig 6, par 0044, “the electronic device 100 also detects the presence of overhanging structures, such as ceiling fan 506, that may hinder collision free navigation within the virtual bounded volume. As illustrated in FIG. 6, the electronic device 100 vertically clears the bounded area by generating a second set of initial boundary points on the ceiling (e.g., a first point 602, a second point 604, a third point 606, a fourth point 608, etc.) of the bedroom 500 in addition to the first set of initial boundary points on the floor of the bedroom 500. The points on the floor and the ceiling of the bedroom 500 are used by the electronic device 100 to define a three-dimensional (3D), virtual bounded volume (e.g., illustrated in FIG. 6 as a bounded cage 610) within which the user 110 may move without colliding into objects. The bounded cage 610 defines an area free of physical obstructions and/or overhanging structures (e.g., no ceiling fans that the user 110 may accidentally collide into with outstretched arms)”);
determining, based on the scanned depth of objects within the updated boundary, that one or more objects within the updated boundary present a hazard (par 0066-0067, “the depth sensor 118 of the electronic device 100 periodically scans the local environment 112 surrounding the user 110 to detect objects within the user's collision range. This periodic scanning is performed even while the relative pose of device 100 indicates user 110 to be positioned within a virtual bounded floor plan such as to detect new objects or obstructions that may have been introduced into the physical space aligned to the virtual bounded floor plan after initial obstruction clearance. FIG. 11 is a diagram illustrating a perspective view of a collision warning presented to users in accordance with at least one embodiment of the present disclosure. A depth sensor 118 of the electronic device 100 periodically scans the local environment and generates warnings to the user after detecting physical objects which obstruct at least a portion of the area within the virtual bounded floor plan 800. After detecting the presence of an unmapped object within the virtual bounded floor plan 800 (e.g., the dog 1102), the electronic device 100 displays a collision warning 1104 overlaid the VR environment rendering”); and
rendering the artificial reality experience based, at least partially, on the determining that the one or more objects within the updated boundary present the hazard (par 0067, “FIG. 11 is a diagram illustrating a perspective view of a collision warning presented to users in accordance with at least one embodiment of the present disclosure. A depth sensor 118 of the electronic device 100 periodically scans the local environment and generates warnings to the user after detecting physical objects which obstruct at least a portion of the area within the virtual bounded floor plan 800. After detecting the presence of an unmapped object within the virtual bounded floor plan 800 (e.g., the dog 1102), the electronic device 100 displays a collision warning 1104 overlaid the VR environment rendering”).
But Wang et al. keep silent for teaching determining, based on the scanned depth of objects within the boundary, that the objects within the boundary do not present a hazard.
In related endeavor, Silverstein et al. teach determining, based on the scanned depth of objects within the boundary, that the objects within the boundary do not present a hazard (col 7:33-59, “ IoT device 225A may be an IoT camera that captures image data of thumbtack 210. This image data may be sent to VR device 202 where it is analyzed for risk through image recognition analysis. Based on previous risk tolerance data generated for the user, the system may determine the thumbtack 210 is a potential injury risk because it is detected within the action area 212 relative to the user 204 ….a second user may always wear shoes when playing a VR game. The system may analyze this event data (e.g., image recognition of the second user wearing shoes), such that no alert is sent to the user because the thumbtack 210 does not pose an injury risk. In this way, the system does not interrupt the second user's VR experience by sending them an unnecessary alert”).
It would have been obvious to a person of ordinary skill in the art at the time before the effective filing data of the claimed invention to modified Wang et al. to include determining, based on the scanned depth of objects within the boundary, that the objects within the boundary do not present a hazard as taught by Silverstein et al. to accurately determine risk through analyze certain objects and/or events occurring externally to the VR simulation may not be considered risks to the user when wearing a VR headset.
But Wang et al. as modified by Silverstein et al. keep silent for teaching detected movement of the artificial reality system; based on the detecting movement of the artificial reality system, automatically detecting, by the artificial reality system, characteristics of a second portion of the real-world environment by scanning the depth of objects, away from the artificial reality system, in the real-world environment within the fixed radius of the artificial reality system; updating the generated boundary, for the artificial reality experience, based on the detected characteristics of the second portion of the real-world environment.
In related endeavor, Madden et al. teach detecting movement of the artificial reality system (par 0072, “the system can map the 3D space 101 over time by tracking the user 110 in camera images generated by the camera 111, and storing data indicating the extent of the user's movements. In some examples, the system can infer an assumed 3D space 101 based on the geometry of the room where the 3D space 101 is located. For example, the system can fit a rectangular shaped 3D space into an unobstructed area of the room. In some examples, the system can prompt the user 110, e.g., through a communication to the XR device 140, to directly define the 3D space within the camera field of view, e.g., by walking around an outline of the 3D space 101 in view of the camera 111”, par 0142, “the XR application 306 can present an environment to the user 310 that appears to change locations without the user 310 needing to physically move to a new location. In some examples, the XR application 306 can pause the XR experience while the resident 336 passes through the foyer 331. The XR application 306 can then resume the XR experience when the resident 336 enters the kitchen 333, and guide the user 310 to the redefined 3D space 302”);
based on the detecting movement of the artificial reality system, automatically detecting, by the artificial reality system, characteristics of a second portion of the real-world environment by scanning the depth of objects, away from the artificial reality system, in the real-world environment within the fixed radius of the artificial reality system (par 0136-0141, “the system 320 can analyze the sensor data and determine, based on the sensor data, that the resident 336 is arriving at the property 303. The system 320 may determine that the resident 336 is likely to enter the foyer 331 and therefore is likely to interfere with the defined 3D space 301. ….. The XR application 306 can adjust the XR environment narrative based on the redefined 3D space 302. The XR application 306 can re-evaluate the mapping of the XR environment to the redefined 3D space 302, and guide the user 310 to the redefined 3D space 302. In the example of FIG. 3, the XR application 306 adjusts the narrative of the XR experience to guide the user 310 from the kitchen 333 to the office 334. In this way, the XR application 306 adjusts the XR environment in a way that causes the user 310 to avoid the unavailable areas that are occupied or predicted to be occupied by the resident 336”);
updating the generated boundary, for the artificial reality experience, based on the detected characteristics of the second portion of the real-world environment (par 0149-0151, “The process 400 includes, based on sensor data generated from one or more sensors at the property 303, predicting that the first portion of the available 3D space will be interfered with (408). For example, based on sensor data generated from the camera 311, the system 320 can predict that the defined 3D space 301 will be interfered with by the resident 336 arriving at the property 303. The system 320 can determine a probability, or likelihood, that the 3D space 301 will be interfered with and can compare the probability of disruption to a threshold probability, e.g., a threshold probability of fifty percent ….. The process 400 includes, based on predicting that the selected portion of the available 3D space will be interfered with, selecting, from the available 3D space, a second portion of the available 3D space for representing the XR environment (410). For example, based on predicting that the defined 3D space 301 will be interfered with, the system 320 can select, from the available 3D space at the property 303, a redefined 3D space 302. The process 400 includes providing the XR environment represented by the second portion of the available 3D space for presentation by the user device (412). For example, the system 320 can provide the XR environment represented by the redefined 3D space 302 for presentation by the XR device 340”);
determining, based on the scanned depth of objects within the updated boundary, that one or more objects within the updated boundary present a hazard (par 0082, “ the system 120 can store a model of the property 102 and/or portions of the property 102. The model can include data indicating a position of sensors and devices at the property 102. Information of the property layout and of the positions of sensors can enable the system to provide advance warning of a potential 3D space encroachment “, par 0085-0093, “the system 120 may detect that a person, object, or animal is in or near the 3D space 101 when the user 110 first dons the XR device 140. Based on the user 110 donning the XR device 140, the system 120 can perform an action to mitigate or prevent interference by the person, object, or animal. For example, system 120 can transmit a notification to the XR device 140 that the person, object, or animal is in the 3D space 101. This can enable the user 110 to take an action to remove the person, object, or animal from the 3D space 101 before beginning an XR experience …the system 120 provides a notification 114 to a user device, e.g., mobile device 115. For example, based on determining that the person 130 is approaching the 3D space 101, the system 120 can transmit the notification 114 to the mobile device 115 associated with the person 130. The notification 114 can include, for example, a text message that says “Warning: approaching XR 3D space.” In some examples, the notification 114 can include an audible of visual alert, e.g., an alert sound or flashing light”, par 0108, “Examples include hazards inferred from imagery or 3D reconstruction that might warrant shrinking the 3D space out of caution such as a nearby staircase or window, and/or an overhanging lamp or furniture”).
It would have been obvious to a person of ordinary skill in the art at the time before the effective filing data of the claimed invention to modified Wang et al. as modified by Silverstein et al. to include movement of the artificial reality system; based on the detecting movement of the artificial reality system, automatically detecting, by the artificial reality system, characteristics of a second portion of the real-world environment by scanning the depth of objects, away from the artificial reality system, in the real-world environment within the fixed radius of the artificial reality system; updating the generated boundary, for the artificial reality experience, based on the detected characteristics of the second portion of the real-world environment as taught by Madden et al. to reconfigure its virtual spaces to fit the constraints of the real-world adjusted 3D space to provide techniques used for XR 3D space monitoring, dynamic 3D space management, and coordination of multiple 3D spaces to prevent the multiple users from colliding with each other while minimizing disruption to the XR experience of each user through tracking all users in the play space and negotiating 3D space between the various independent XR applications to increase use of the full 3D space while maintaining users at a safe distance from each other.
Regarding claim 2, Wang et al. as modified by Silverstein et al. and Madden et al. teach all the limitation of claim 1, and further teach wherein the determining that the one or more objects presents the hazard includes determining that the one or more objects, within the updated boundary, are within a threshold distance of the artificial reality system (Silverstein et al.: col 3:6-22, “through image recognition analysis of the event data from an IoT camera, the system may determine there is a thumbtack within a user's active area. If the event data meets a risk tolerance threshold (e.g., the thumbtack is within the active area based on proximity and weighted alerts), the system sends a notification to the user's VR headset”, col 3:31-43, “the indicator may include different warning levels (e.g., red, yellow, etc.) to notify the user that they are within a certain distance of an object”, col 3:57-67 and col 4:1-4, “The system may analyze the biometric and image data using machine learning and generate a risk tolerance threshold for altering a user when a coffee table is in proximity to the user at a certain distance”, Madden et al.: par 0034-0035, par 0084, “the system 120 predicts 3D space interference. For example, the system 120 can analyze the sensor data to determine that the person 130 is approaching the 3D space 101 and is about to interfere with the 3D space 101. In some examples, the system 120 can predict interference based on the person 130 approaching within a threshold distance to a boundary of the 3D space 101. The system 120 can also predict interference based on the layout of the property 102 as indicated by the stored model”, par 0086, “the system 120 can predict interference by an animal. The system 120 can predict interference by objects similarly to predicting interference by a person, e.g., by determining that the object is within a threshold distance to a boundary of the 3D space 101 or by determining, based on the property layout and the current location of the object, that the object is likely to pass through the 3D space 101”).
Regarding claim 7, Wang et al. as modified by Silverstein et al. and Madden et al. teach all the limitation of claim 1, and further teach wherein the determining that the one or more objects presents the hazard includes determining that the artificial reality system is moving toward the one or more objects within the updated boundary (Wang et al.: par 0067, “A depth sensor 118 of the electronic device 100 periodically scans the local environment and generates warnings to the user after detecting physical objects which obstruct at least a portion of the area within the virtual bounded floor plan 800. After detecting the presence of an unmapped object within the virtual bounded floor plan 800 (e.g., the dog 1102), the electronic device 100 displays a collision warning 1104 overlaid the VR environment rendering”, Silverstein et al.: col 8:24-33, “based on historical risk tolerance data, if the dog 218 is determined to be moving and/or chewing on the couch 206, the system may alert the user of the risk”).
Regarding claim 8, Wang et al. as modified by Silverstein et al. and Madden et al. teach all the limitation of claim 1, and Wang et al. further teach when automatically detecting by the artificial reality system characteristics of the first portion of a real-world environment, the artificial reality system does not analyze data for depths outside the fixed radius of the artificial reality system (par 0042, “a warning may be displayed if the user 110 navigates into proximity of an unscanned or underscanned portion of bedroom 500. In other embodiments, the electronic device 100 may present the VR environment for display without having scanned any portion of the bedroom 500 a priori. In such embodiments, the user 110 initiates a navigation session by picking up the electronic device 100 (i.e., wearing the HMD as illustrated) and the electronic device 100 dynamically scans the bedroom 500 as the user 110 navigates the VR environment”).
Regarding claim 9, Wang et al. as modified by Silverstein et al. and Madden et al. teach all the limitation of claim 1, and further teach further comprising: determining that the artificial reality system has less than a threshold amount of movement in the real-world environment and/or determining a posture of the user as a non-standing posture; and based on the determining that the artificial reality system has less than the threshold amount of movement in the real-world environment and/or determining a posture of the user as a non-standing posture, switching to a stationary mode in which the real-world environment is not further scanned and/or the generated boundary is not further updated (Wang et al.: par 0045, “subsequent to generating the first set of initial boundary points, the electronic device 100 allows for user modification of the initial points to refine or adjust boundaries of the virtual bounded volume. Referring now back to FIG. 5, the initial third point 512 generated by the electronic device 100 is positioned too close to the desk 504 such that the user 110 is likely to collide with the desk 504 if the user 110 walks close to or past the boundary of the virtual bounded area/volume” …. Refine boundary only user to close to boundary, Silverstein et al.: col 7:11-31, “These risks are shown within the active area 212 of the user 204. The active area 212 is the area surrounding user 204 where the user may move about when interacting with a VR simulation” ….disclose stationary area for AR without update).
Regarding claim 10, Wang et al. as modified by Silverstein et al. and Madden et al. teach all the limitation of claim 1, and further teach further comprising: obtaining additional characteristics of the first portion of the real-world environment, within the fixed radius of the artificial reality system, detected by an other artificial reality system at least partially scanning the first portion of the real-world environment, wherein the updating the generated boundary is further based on the additional characteristics of the first portion of the real-world environment (Wang et al.: par 0029, “certain non-image sensor data, such as gyroscopic data or accelerometer data, can be used to correlate spatial features observed in one image frame with spatial features observed in a subsequent image frame. Moreover, the relative pose information obtained by the electronic device 100 can be combined with any of the camera image data 128, non-image sensor data 130, depth data 132, head tracking data 134, and/or supplemental information 136 to present a VR environment or an AR view of the local environment 112 to the user 110 via the display 108 of the electronic device 100”, par 0045, “subsequent to generating the first set of initial boundary points, the electronic device 100 allows for user modification of the initial points to refine or adjust boundaries of the virtual bounded volume”, Madden et al.: par 0080-0081, “he system 120 obtains sensor data 122. The sensor data 122 can include, for example, camera image data, motion sensor data, geofence data, GPS data, and/or other types of sensor data. For example, the sensor data can include camera image data generated by the camera 111 that is external from the XR device 140. The sensor data 122 can include camera image data showing a person 130 approaching the 3D space 101. The sensor data 122 can also include motion sensor data, microphone data, and/or other data indicating that the person 130 is approaching the 3D space 101. The sensor data 122 can also include geofence data indicating that a mobile device 115 associated with the person 130 has entered within a geofence of the property 102 where the 3D space 101 is located”, par 0141, “The XR application 306 can adjust the XR environment narrative based on the redefined 3D space 302. The XR application 306 can re-evaluate the mapping of the XR environment to the redefined 3D space 302, and guide the user 310 to the redefined 3D space 302”).
Regarding claim 11, Wang et al. as modified by Silverstein et al. and Madden et al. teach all the limitation of claim 10, and further teach wherein the additional characteristics correspond to an area, of the second portion of the real-world environment, not scanned by the artificial reality system (Wang et al.: par 0029, “certain non-image sensor data, such as gyroscopic data or accelerometer data, can be used to correlate spatial features observed in one image frame with spatial features observed in a subsequent image frame. Moreover, the relative pose information obtained by the electronic device 100 can be combined with any of the camera image data 128, non-image sensor data 130, depth data 132, head tracking data 134, and/or supplemental information 136 to present a VR environment or an AR view of the local environment 112 to the user 110 via the display 108 of the electronic device 100”, par 0042, “the electronic device 100 may present the VR environment for display without having scanned any portion of the bedroom 500 a priori”, Madden et al.: par 0080-0081, “he system 120 obtains sensor data 122. The sensor data 122 can include, for example, camera image data, motion sensor data, geofence data, GPS data, and/or other types of sensor data. For example, the sensor data can include camera image data generated by the camera 111 that is external from the XR device 140. The sensor data 122 can include camera image data showing a person 130 approaching the 3D space 101. The sensor data 122 can also include motion sensor data, microphone data, and/or other data indicating that the person 130 is approaching the 3D space 101. The sensor data 122 can also include geofence data indicating that a mobile device 115 associated with the person 130 has entered within a geofence of the property 102 where the 3D space 101 is located”, par 0141, “The XR application 306 can adjust the XR environment narrative based on the redefined 3D space 302. The XR application 306 can re-evaluate the mapping of the XR environment to the redefined 3D space 302, and guide the user 310 to the redefined 3D space 302”).
Regarding claim 12, Wang et al. teach a computer-readable storage medium storing instructions, for automatically generating a boundary for an artificial reality experience, the instructions, when executed by a computing system, cause the computing system to (par 0037, claim 18). The remaining limitations of the claim is similar in scope to claim 1 (part of claim 1) and rejected under the same rationale.
Regarding claims 13-15, Wang et al. as modified by Silverstein et al. and Madden et al. teaches all the limitation of claim 12, the claims 13-15 are similar in scope to claims 10-11 and 8 and are rejected under the same rational.
Regarding claim 16, Wang et al. teach a computing system for automatically generating a boundary for an artificial reality experience, the computing system comprising: one or more processors; and one or more memories storing instructions that, when executed by the one or more processors, cause the computing system to (par 0083-0084). The remaining limitations of the claim is similar in scope to claim 1 (part of claim 1) and rejected under the same rationale.
Regarding claim 17, Wang et al. as modified by Silverstein et al. and Madden et al. teaches all the limitation of claim 16, the claim 17 is similar in scope to claim 2 and is rejected under the same rational.
Claim(s) 3-4, 6, and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. PGPubs 2019/00432259 to Wang et al. in view U.S. Patent US 10832484 to Silverstein et al., further in view of U.S. PGPubs 2023/0196681 to Madden et al., further in view of U.S. PGPubs 2019/0221035 to Clark et al..
Regarding claim 3, Wang et al. as modified by Silverstein et al. and Madden et al. teach all the limitation of claim 2, but keep silent for teaching wherein rendering the artificial reality experience includes rendering a representation of the one or more objects.
In related endeavor, Clark et al. teach wherein rendering the artificial reality experience includes rendering a representation of the one or more objects (par 0076-0077, “FIG. 7 depicts a view 700 of virtual objects 710, 720, 722, 730, 740 associated with the physical objects 130, 132, 134, 136 of FIG. 6. The virtual objects 710-740 need not look like the physical objects 130, 132, 134, 136, but instead can be selected or generated to match visual characteristics of a virtual reality (VR) environment (or AR environment), for example a theme of the VR environment …. Based on such determinations, the VR application 345 can select, from the virtual object library 430, virtual objects 710-740 that satisfy specific criteria. The specific criteria can correspond to the shape/spatial dimensions of the physical objects 130-150, the location of the physical objects 130-150 relative to the user 105 in the real world environment 100, and the VR environment being presented to the user 105”).
It would have been obvious to a person of ordinary skill in the art at the time before the effective filing data of the claimed invention to modified Wang et al. as modified by Silverstein et al. and Madden et al. to include wherein rendering the artificial reality experience includes rendering a representation of the one or more objects as taught by Clark et al. to presented virtual objects in a virtual reality environment at virtual coordinates, relative to a virtual representation of the user in the virtual reality environment, corresponding to the determined real world environment coordinates of where the physical object is located relative to the user in the real world environment to reduce a risk the user will bump into various physical objects, which can result in injury to the user becoming and/or damage to the physical objects.
Regarding claim 4, Wang et al. as modified by Silverstein et al., Madden et al., and Clark et al. teach all the limitation of claim 3, and Wang et al further teach wherein the representation of the one or more objects includes a mesh outlining the one or more objects (par 0067, “presented as a point cloud outline of the obstruction in FIG. 11 (i.e., point cloud outline of the dog 1102)).
Regarding claim 6, Wang et al. as modified by Silverstein et al., Madden et al., and Clark et al. teach all the limitation of claim 3, and further teach wherein the representation of the one or more objects includes a pass-through view of the one or more objects (Wang et al.: par 0066, “the electronic device 100 enters a free roam mode in which the electronic 100 maintains rendering of the VR environment but further overlays display showing, for example, point cloud representations of objects (or alternatively, live imagery of objects via pass through cameras) around the user 110”, Madden et al.: par 0086, “The system 120 can predict interference by objects similarly to predicting interference by a person, e.g., by determining that the object is within a threshold distance to a boundary of the 3D space 101 or by determining, based on the property layout and the current location of the object, that the object is likely to pass through the 3D space 101”, Clark et al.: par 0076, “FIG. 7 depicts a view 700 of virtual objects 710, 720, 722, 730, 740 associated with the physical objects 130, 132, 134, 136 of FIG. 6. The virtual objects 710-740 need not look like the physical objects 130, 132, 134, 136, but instead can be selected or generated to match visual characteristics of a virtual reality (VR) environment (or AR environment), for example a theme of the VR environment”).
Regarding claims 18-20, Wang et al. as modified by Silverstein et al. and Madden et al. teaches all the limitation of claim 17, the claims 18-20 are similar in scope to claims 3-4 and 6 and are rejected under the same rational.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. PGPubs 2019/00432259 to Wang et al. in view U.S. Patent US 10832484 to Silverstein et al., further in view of U.S. PGPubs 2023/0196681 to Madden et al., further in view of U.S. PGPubs 2019/0221035 to Clark et al., further in view of U.S. PGPubs 2021/0125407 to Pekelny et al..
Regarding claim 5, Wang et al. as modified by Silverstein et al., Madden et al., and Clark et al. teach all the limitation of claim 4, but keep silent for teaching wherein the mesh is a three-dimensional mesh of the one or more objects.
In related endeavor, Pekelny et al. teach wherein the mesh is a three-dimensional mesh of the one or more objects (par 0044, “As shown in FIG. 3, in some embodiments, the 3D representation 300 is comprised of any number of polygons 305 (e.g., 3D triangles). These polygons 305 are shaped and oriented in different configurations to symbolically, or rather digitally, represent an object. FIG. 3, for example, shows how the different polygons 305 are shaped and oriented in a manner to digitally reflect or represent a staircase, such as the staircase shown in FIG. 2. Each stair in the staircase is digitally represented by a number of different polygons”, par 0069, “Turning briefly to FIG. 6, this figure illustrates one example of a detailed SR mesh 600 that may be generated by method act 510. Detailed SR mesh 600 is shown as including different polygons, such as, for example, polygons 605, 610, 615, and 620. Polygons 605 are shown as corresponding to the stairs and further show a specific set of 3D triangles”
It would have been obvious to a person of ordinary skill in the art at the time before the effective filing data of the claimed invention to modified Wang et al. as modified by Silverstein et al. and Madden et al. to include wherein the mesh is a three-dimensional mesh of the one or more objects as taught by Pekelny et al. to identify a structure of the environment to generate a detailed three-dimensional (3D) representation of the environment based on depth data and pose data to render or update holograms in the MR scene.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jin Ge whose telephone number is (571)272-5556. The examiner can normally be reached 8:00 to 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason Chan can be reached at (571)272-3022. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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JIN . GE
Examiner
Art Unit 2619
/JIN GE/Primary Examiner, Art Unit 2619
Prosecution Insights