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 .
Claim Status
This action is in response to the application filed on 07/30/2025. Claims 1-20 are pending and examined below.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 20230105428 A1 (“Brown”) in view of US 20220365592 A1 (“Hol”).
Regarding claim 1, Brown discloses generating, by a device, modified video data based on video data that includes a plurality of video frames and corresponding sensor data associated with a vehicle;
selecting, by the device, image regions of video frames of the modified video data;, a;
generating, by the device, based on determining a speed and a turn angle of the vehicle, and based on the features, a trained neural network model for the vehicle; and performing, by the device, one or more actions based on the trained neural network model
Brown is not explicit on masking, by the device, the selected image regions to identify features of the video frames of the modified video data, however,
Hol discloses masking, by the device, the selected image regions to identify features of the video frames of the modified video data (see at least [0080]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 2, Brown discloses the sensor data includes location data (see at least [0134]).
Regarding claim 3, Brown discloses the sensor data includes inertial measurement unit (IMU) data (see at least [0127]).
Regarding claim 4, Brown is not explicit on generating the modified video data comprises: removing video frames from the video data, however,
Hol discloses on generating the modified video data comprises: removing video frames from the video data (see at least [0052]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 5, brown is not explicit on masking objects of the video frames of the modified video data to identify additional features of the video frames of the modified video data ,however,
Hol discloses masking objects of the video frames of the modified video data to identify additional features of the video frames of the modified video data (see at least [0080]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 6, Brown discloses the speed and the turn angle are determined based on the sensor data and the modified video data (see at least [0127]).
Regarding claim 7, Brown discloses the speed is a current speed and the turn angle is a current angle (see at least [0089]).
Regarding claim 8, one or more instructions that, when executed by one or more processors of a device, cause the device to (see at least [0040]);
generate modified video data based on video data that includes a plurality of video frames and corresponding sensor data associated with a vehicle; select objects of video frames of the modified video data (see at least [0127]);
generate, based on determining a speed and a turn angle of the vehicle, and based on the features, a trained neural network model for the vehicle; perform one or more actions based on the trained neural network model (see at least 0058]).
Brown is not explicit on mask the selected objects to identify features of the video frames of the modified video data, however,
Hol discloses mask the selected objects to identify features of the video frames of the modified video data (see at least [0080]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 9, Brown discloses the sensor data includes location data (see at least [0134]).
Regarding claim 10, the sensor data includes inertial measurement unit (IMU) data (see at least [0127]).
Regarding claim 11, Brown is not explicit on generating the modified video data comprises: removing video frames from the video data, however,
Hol discloses on generating the modified video data comprises: removing video frames from the video data (see at least [0052]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 12, Brown is not explicit on masking objects of the video frames of the modified video data to identify additional features of the video frames of the modified video data ,however,
Hol discloses masking objects of the video frames of the modified video data to identify additional features of the video frames of the modified video data (see at least [0080]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 13, Brown discloses the speed and the turn angle are determined based on the sensor data and the modified video data (see at least [0127]).
Regarding claim 14, Brown discloses the speed is a current speed and the turn angle is a current angle (see at least [0089]).
Regarding claim 15, Brown discloses one or more processors generate modified video data based on video data that includes a plurality of video frames and corresponding sensor data associated with a vehicle (see at least [0058]);
select one or more portions of video frames of the modified video data (see at least [0058])
generate based on determining a speed and a turn angle of the vehicle, and based on the features, a trained neural network model for the vehicle (see at least [0127]); and
perform one or more actions based on the trained neural network model (see at least [0134]).
Brown is not explicit on mask the selected one or more portions to identify features of the video frames of the modified video data, however,
Hol discloses mask the selected one or more portions to identify features of the video frames of the modified video data (see at least [0080]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 16, Brown discloses the sensor data includes location data (see at least [0134]).
Regarding claim 17, Brown discloses the sensor data includes inertial measurement unit (IMU) data (see at least [0127]).
Regarding claim 18, Brown is not explicit on generate the modified video data, are configured to: remove video frames from the video data, however,
Hol discloses generate the modified video data, are configured to: remove video frames from the video data S generate the modified video data, are configured to: remove video frames from the video data (see at least [0052]).
One of ordinary skill in the art would have been motivated to combine the system disclosed by Brown with the visual tracking system disclosed by Hol to allow users observe a scene while simultaneously seeing relevant virtual content that may be aligned to items, images, objects, or environments in the field of view (Hol, [0003]).
Regarding claim 19, Brown discloses the one or more portions are associated with one or more objects or one or more image regions of the video frames of the modified video data (see at least [0134]).
Regarding claim 20, Brown discloses the speed and the turn angle are determined based on the sensor data and the modified video data (see at least [0127]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATHEW FRANKLIN GORDON whose telephone number is (408)918-7612. The examiner can normally be reached Monday - Friday, 7:00 - 5:00 PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Christian Chace can be reached at (571) 272-4190. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MATHEW FRANKLIN GORDON/Primary Examiner, Art Unit 3665
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