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 .
Priority
Acknowledgment is made of applicant's claim for domestic priority based on 371 of PCT/US2023/067708 application filed on 5/31/2023.
Information Disclosure Statement
The Information Disclosure Statement has been considered and placed in the record on file and is in compliance with USPTO requirements.
Drawings
The Drawings have been considered and placed in the record on file and are in compliance with USPTO requirements.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 2, 8, 9, 15, 16, 22, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Morrison et al. (US 2023/0400958 hereinafter Morrison) in view of Evans (US 2019/0213796 hereinafter Evans).
In regards to claim 1, Morrison discloses a method, comprising: inputting, into a machine learning engine at a refresh rate of a virtual environment, ultra-wideband (UWB) data, and inertial measurement unit (IMU) data (see paragraph 0035, sensor data is received from wrist-wearable device and/or the head-wearable device to determine that an augmented display criterion is satisfied)
the UWB data including samples of a UWB signal acquired at a first rate (see paragraph 0035, Ultra-wideband (UWB) sensor),
the IMU data representing samples of a IMU signal acquired at a second rate, the first rate being different from the second rate (see paragraph 0035, IMU sensor of the wrist-wearable device);
the machine learning engine being configured to output a position value and an orientation value indicative of a position and an orientation of a mobile device within the virtual environment (see paragraph 0221, the sensor data is used to determine position and orientation data).
However, Morrison fails to particularly disclose rendering a virtual object representing the mobile device in the virtual environment according to the position and orientation.
Evans teaches rendering a virtual object representing the mobile device in the virtual environment according to the position and orientation (see claim 38, render a virtual object representing the mobile phone).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and render a virtual object representing a mobile phone at a location and orientation based on the UWB and IMU data as taught by Evans, thereby using known techniques to yield predictable results.
In regards to claim 2, as recited in claim 1, Morrison further discloses further comprising: acquiring streaming content from the mobile device; and displaying the streaming content from the mobile device at the position and orientation within the virtual environment (see figure 1F and paragraph 0043, content related to music application is rendered over the watch).
In regards to claim 8., Morrison discloses a method, comprising: inputting depth image data, ultra-wideband (UWB) data, and inertial measurement unit (IMU) data into a machine learning engine at a refresh rate of a virtual environment (see paragraph 0035, sensor data is received from wrist-wearable device and/or the head-wearable device to determine that an augmented display criterion is satisfied), the depth image data including a depth image acquired at a first rate (see paragraph 0164, depth camera);
the UWB data including samples of a UWB signal acquired at a second rate (see paragraph 0035, Ultra-wideband (UWB) sensor),
the IMU data representing samples of a IMU signal acquired at a third rate, the first rate being different from at least one of the second rate or the third rate (see paragraph 0035, IMU sensor of the wrist-wearable device);
the machine learning engine being configured to output a position value and an orientation value indicative of a position and an orientation of a mobile device within the virtual environment (see paragraph 0221, the sensor data is used to determine position and orientation data).
However, Morrison fails to particularly disclose rendering a virtual object representing the mobile device in the virtual environment according to the position and orientation.
Evans teaches rendering a virtual object representing the mobile device in the virtual environment according to the position and orientation (see claim 38, render a virtual object representing the mobile phone).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and render a virtual object representing a mobile phone at a location and orientation based on the UWB and IMU data as taught by Evans, thereby using known techniques to yield predictable results.
In regards to claim 9, Morrison further discloses further comprising: acquiring streaming content from the mobile device; and displaying the streaming content from the mobile device at the position and orientation within the virtual environment (see figure 1F and paragraph 0043, content related to music application is rendered over the watch).
In regards to claim 15, Morrison discloses a computer program product comprising a nontransitory storage medium, the computer program product including code that, when executed by at least one processor, causes the at least one processor to perform a method, the method comprising: acquiring, at a first rate, depth image data in a real-world environment (see paragraph 0164, depth camera);
acquiring, at a second rate, a sample of an ultra-wideband (UWB) signal (see paragraph 0035, Ultra-wideband (UWB) sensor);
acquiring, at a third rate, a sample of an inertial measurement unit (IMU) signal, the first rate being different from at least one of the second rate or the third rate (see paragraph 0035, IMU sensor of the wrist-wearable device);
inputting the depth image data, the sample of the UWB signal, and the sample of the IMU signal into a machine learning engine at a refresh rate of a virtual environment (see paragraph 0035, sensor data is received from wrist-wearable device and/or the head-wearable device to determine that an augmented display criterion is satisfied), the machine learning engine being configured to output a position value and an orientation value indicative of a position and an orientation of a mobile device within the virtual environment (see paragraph 0221, the sensor data is used to determine position and orientation data).
However, Morrison fails to particularly disclose rendering a virtual object representing the mobile device in the virtual environment according to the position and orientation.
Evans teaches rendering a virtual object representing the mobile device in the virtual environment according to the position and orientation (see claim 38, render a virtual object representing the mobile phone).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and render a virtual object representing a mobile phone at a location and orientation based on the UWB and IMU data as taught by Evans, thereby using known techniques to yield predictable results.
In regards to claim 16, as recited in claim 15, Morrison further discloses further comprising: acquiring streaming content from the mobile device; and displaying the streaming content from the mobile device at the position and orientation within the virtual environment (see figure 1F and paragraph 0043, content related to music application is rendered over the watch).
In regards to claim 22, Morrison discloses an apparatus, comprising: memory (see paragraph 0072, computer memory); and
processing circuitry coupled to the memory (see paragraph 0072, processor), the processing circuitry being configured to:
input depth image data, ultra-wideband (UWB) data, and inertial measurement unit (IMU) data into a machine learning engine at a refresh rate of a virtual environment (see paragraph 0035, sensor data is received from wrist-wearable device and/or the head-wearable device to determine that an augmented display criterion is satisfied),
the depth image data including a depth image acquired at a first rate (see paragraph 0164, depth camera);
the UWB data including samples of a UWB signal acquired at a second rate (see paragraph 0035, Ultra-wideband (UWB) sensor);
the IMU data representing samples of a IMU signal acquired at a third rate, the first rate being different from at least one of the second rate or the third rate (see paragraph 0035, IMU sensor of the wrist-wearable device);
the machine learning engine being configured to output a position value and an orientation value indicative of a position and an orientation of a mobile device within the virtual environment (see paragraph 0221, the sensor data is used to determine position and orientation data).
However, Morrison fails to particularly disclose render a virtual object representing the mobile device in the virtual environment according to the position and orientation.
Evans teaches render a virtual object representing the mobile device in the virtual environment according to the position and orientation (see claim 38, render a virtual object representing the mobile phone).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and render a virtual object representing a mobile phone at a location and orientation based on the UWB and IMU data as taught by Evans, thereby using known techniques to yield predictable results.
In regards to claim 23, as recited in claim 22, Morrison further discloses wherein the processing circuitry is further configured to: acquire streaming content from the mobile device; and display the streaming content from the mobile device at the position and orientation within the virtual environment (see figure 1F and paragraph 0043, content related to music application is rendered over the watch).
Claims 3, 10, 17, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Morrison and Evans in view of Fajt et al. (US 2019/0329129 hereinafter Fatj).
In regards to claim 3, as recited in claim 1, the combination of Morrison and Evans fails to disclose wherein the machine learning engine outputs a quarternion representing the orientation.
Fajt teaches wherein the machine learning engine outputs a quarternion representing the orientation (see paragraph 0028, orientation is in a quarternion representation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include orientation as a quarternion representation as taught by Fatj, thereby using known techniques to yield predictable results.
In regards to claim 10, as recited in claim 8, the combination of Morrison and Evans fails to disclose wherein the machine learning engine outputs a quarternion representing the orientation.
Fajt teaches wherein the machine learning engine outputs a quarternion representing the orientation (see paragraph 0028, orientation is in a quarternion representation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include orientation as a quarternion representation as taught by Fatj, thereby using known techniques to yield predictable results.
In regards to claim 17, as recited in claim 15, the combination of Morrison and Evans fails to disclose wherein the machine learning engine outputs a quarternion representing the orientation.
Fajt teaches wherein the machine learning engine outputs a quarternion representing the orientation (see paragraph 0028, orientation is in a quarternion representation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include orientation as a quarternion representation as taught by Fatj, thereby using known techniques to yield predictable results.
In regards to claim 24, as recited in claim 22, the combination of Morrison and Evans fails to disclose wherein the machine learning engine outputs a quarternion representing the orientation.
Fajt teaches wherein the machine learning engine outputs a quarternion representing the orientation (see paragraph 0028, orientation is in a quarternion representation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include orientation as a quarternion representation as taught by Fatj, thereby using known techniques to yield predictable results.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Morrison and Evans in view of Lehment et al. (US 2024/0310937 hereinafter Lehment) and Hong (US 2022/0362631 hereinafter Hong).
In regards to claim 6, as recited in claim 1, the combination of Morrison and Evans fails to particularly disclose wherein the first rate is about 10 Hz and the second rate is about 100 Hz.
Lehment teaches wherein the first rate is about 10 Hz (see paragraph 0066, UWB at 10 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include UWB at 10 hertz as taught by Lehment, thereby using known techniques to yield predictable results.
Hong teaches wherein the second rate is about 100 Hz (see paragraph 0114, IMU at sample rate of 100 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include IMU sample rates at 100 hertz as taught by Hong, thereby using known techniques to yield predictable results.
Claims 13, 20, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Morrison and Evans in view of Lehment, Hong, and Chizeck et al. (US 2014/0168073 hereinafter Chizeck).
In regards to claim 13, as recited in claim 8, the combination of Morrison and Evans fails to particularly disclose wherein the first rate is about 30 Hz, the second rate is about 10 Hz, the third rate is about 100 Hz.
Chizeck teaches wherein the first rate is about 30 Hz (see paragraph 008, depth sensor at 30 Hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include a depth sensor at 30 hertz as taught by Chizeck, thereby using known techniques to yield predictable results.
Lehment teaches wherein the first rate is about 10 Hz (see paragraph 0066, UWB at 10 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include UWB at 10 hertz as taught by Lehment, thereby using known techniques to yield predictable results.
Hong teaches wherein the second rate is about 100 Hz (see paragraph 0114, IMU at sample rate of 100 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include IMU sample rates at 100 hertz as taught by Hong, thereby using known techniques to yield predictable results.
In regards to claim 20, as recited in claim 15, the combination of Morrison and Evans fails to particularly disclose wherein the first rate is about 30 Hz, the second rate is about 10 Hz, the third rate is about 100 Hz.
Chizeck teaches wherein the first rate is about 30 Hz (see paragraph 008, depth sensor at 30 Hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include a depth sensor at 30 hertz as taught by Chizeck, thereby using known techniques to yield predictable results.
Lehment teaches wherein the first rate is about 10 Hz (see paragraph 0066, UWB at 10 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include UWB at 10 hertz as taught by Lehment, thereby using known techniques to yield predictable results.
Hong teaches wherein the second rate is about 100 Hz (see paragraph 0114, IMU at sample rate of 100 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include IMU sample rates at 100 hertz as taught by Hong, thereby using known techniques to yield predictable results.
In regards to claim 27, as recited in claim 22, the combination of Morrison and Evans fails to disclose wherein the first rate is about 30 Hz, the second rate is about 10 Hz, the third rate is about 100 Hz.
Chizeck teaches wherein the first rate is about 30 Hz (see paragraph 008, depth sensor at 30 Hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include a depth sensor at 30 hertz as taught by Chizeck, thereby using known techniques to yield predictable results.
Lehment teaches wherein the first rate is about 10 Hz (see paragraph 0066, UWB at 10 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include UWB at 10 hertz as taught by Lehment, thereby using known techniques to yield predictable results.
Hong teaches wherein the second rate is about 100 Hz (see paragraph 0114, IMU at sample rate of 100 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include IMU sample rates at 100 hertz as taught by Hong, thereby using known techniques to yield predictable results.
Claims 7, 14, 21, and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Morrison and Evans in view of Leu et al. (US 2006/0139317 hereinafter Leu).
In regards to claim 7, as recited in claim 1, the combination of Morrison and Evans fails to disclose wherein the refresh rate of the virtual environment is about 60 Hz.
Leu teaches wherein the refresh rate of the virtual environment is about 60 Hz (see paragraph 0044, graphics update rate is 60 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include graphics update rate at 60 hertz as taught by Leu, thereby using known techniques to yield predictable results.
In regards to claim 14, as recited in claim 8, the combination of Morrison and Evans fails to disclose wherein the refresh rate of the virtual environment is about 60 Hz.
Leu teaches wherein the refresh rate of the virtual environment is about 60 Hz (see paragraph 0044, graphics update rate is 60 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include graphics update rate at 60 hertz as taught by Leu, thereby using known techniques to yield predictable results.
In regards to claim 21, as recited in claim 15, the combination of Morrison and Evans fails to disclose wherein the refresh rate of the virtual environment is about 60 Hz.
Leu teaches wherein the refresh rate of the virtual environment is about 60 Hz (see paragraph 0044, graphics update rate is 60 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include graphics update rate at 60 hertz as taught by Leu, thereby using known techniques to yield predictable results.
In regards to claim 28, as recited in claim 22, the combination of Morrison and Evans fails to disclose wherein the refresh rate of the virtual environment is about 60 Hz.
Leu teaches wherein the refresh rate of the virtual environment is about 60 Hz (see paragraph 0044, graphics update rate is 60 hertz).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Morrison and Evans and include graphics update rate at 60 hertz as taught by Leu, thereby using known techniques to yield predictable results.
Allowable Subject Matter
Claims 4, 5, 11, 12, 18, 19, 25, and 26 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER J KOHLMAN whose telephone number is (571)270-5503. The examiner can normally be reached 9-5:30.
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/CHRISTOPHER J KOHLMAN/ Primary Examiner, Art Unit 2628
