DETAILED ACTION
This action is in response to communications filed 11/1/2024:
Claims 1-12 are pending
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.
Claim(s) 1, 3-4, and 8-12 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lawrence et al (NPL: “Project Starline: A high-fidelity telepresence system”, hereinafter “Lawrence”).
Regarding claim 1, Lawrence teaches a method (pg. 2, rendering method) comprising:
receiving sensor data corresponding with at least one physical characteristic of a user (pg. 4, Fig. 5 shows a plurality of cameras for capturing at least one physical characteristic of a user);
updating a three-dimensional mesh of the user based on the sensor data (pg. 7, Fig. 9 shows a 3D mesh of the user based on the captured images);
determining an impulse response for the user based on the three-dimensional mesh (pg. 9, HRTFs are used to create binaural signals as output wherein the binaural signals are updated in real-time); and
generating an audio stream based on the impulse response (pg. 9, HRTFs are used to create binaural signals as output).
Regarding claim 3, Lawrence teaches wherein the sensor data includes a snapshot of the user, the method further comprising:
updating the three-dimensional mesh by mapping the user via non-rigid fusion using the snapshot (pg. 7, Fig. 9 shows at least one snapshot of the user and wherein the 3D mesh is created by a fusion technique (of a plurality of snapshots of the user)).
Regarding claim 4, Lawrence teaches wherein the three-dimensional mesh of the user includes information related to a most recent number of snapshots of the user, wherein the number of snapshots is set based on threshold value (pg. 4, real-time 3D localization of the user’s head and various features implies capturing and rendering the most recently-captured images; setting a threshold can be seen as a parameter based on an end-user’s equipment/processing limitation).
Regarding claim 8, Lawrence teaches wherein the at least one physical characteristic of the user includes a first ear and a second ear (pg. 6, features such as the user’s ears are tracked for spatialized audio rendering), and
wherein the impulse response is a first impulse response associated with the first ear,
the method further comprising:
determining a second impulse response associated with the second ear (pg. 4, user’s ears are tracked and used to apply HRTFs);
generating the audio stream based on the first impulse response and the second impulse response, wherein the audio stream provides a binaural sound of an audio source (pg. 4, providing binaural audio output using HRTFs).
Regarding claim 9, Lawrence teaches further comprising:
providing the audio stream, via an electroacoustic transducer, as binaural audio (pg. 4, Fig. 5 shows a plurality of loudspeakers for rendering audio output).
Regarding claim 10, Lawrence teaches further comprising:
determining a transfer function based on an integral transform of the impulse response for the user (pg. 4, HRTFs are integral transforms of HRIRs); and
generating the audio stream by multiplying frequency spectra of an audio source and the transfer function (pg. 4, binaural audio is generated using HRTFs which includes performing convolution of a sound signal with the HRTF to produce said binaural audio output).
Regarding claim 11, Lawrence teaches wherein the transfer function is a Fourier transform of the impulse response (pg. 4, HRTFs are Fourier transforms of HRIRs).
Regarding claim 12, Lawrence teaches wherein the sensor data includes images captured by an imaging device (pg. 4, Fig. 5 shows the cameras using to generate the sensor data and images).
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) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawrence et al (NPL: “Project Starline: A high-fidelity telepresence system”, hereinafter “Lawrence”) in view of Meshram (US20170034641).
Regarding claim 2, Lawrence fails to explicitly teach further comprising:
updating the three-dimensional mesh based on the sensor data according to a sparse inference frequency.
Meshram teaches further comprising:
updating the three-dimensional mesh based on the sensor data according to a sparse inference frequency (¶40, generating a 3D mesh model using sparse point cloud technique (i.e. using sparse data points to create a surface of the image)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the sparse cloud technique (as taught by Meshram) on an audiovisual system (as taught by Lawrence). The rationale to do so is to use a known technique on a similar device to yield the predictable result of improved processing when processing speed is of a greater priority than processing quality (Meshram, ¶35).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawrence et al (NPL: “Project Starline: A high-fidelity telepresence system”, hereinafter “Lawrence”) in view of Stengel et al (US20220191638, hereinafter “Stengel”).
Regarding claim 5, Lawrence fails to explicitly teach further comprising:
determining the impulse response for the user by processing the three-dimensional mesh through a generative model.
Stengel teaches further comprising:
determining the impulse response for the user by processing the three-dimensional mesh through a generative model (¶67, determining head pose of the user (¶70, which is used to produce the binaural/spatialized audio) can be used in combination with generative modeling).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the generative modeling (as taught by Stengel) on an audiovisual system (as taught by Lawrence). The rationale to do so is to use a known technique on a similar device to yield the predictable result of using one or more well-known algorithms to estimate a user’s head position to provide improved spatialized audio output (Stengel, ¶67).
Allowable Subject Matter
Claims 6-7 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Refer to PTO-892, Notice of References Cited for a listing of analogous art.
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/QIN ZHU/Primary Examiner, Art Unit 2691
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