DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This Office Action is in response to the application filed on 10/21/2024.
3. The IDSs filed on 07/16/25, 04/19/26, 06/23/26, and 09/2/26 are considered and entered into the application file.
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
4. Claims 1-4, 8-11, and 15-18, are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Shi et al (US 20240169498 A1).
Shi et al (“Shi”) is directed to Joint Video Stabilization And Motion Deblurring.
As per claim 1, Shi discloses a computer-implemented method (see flowchart of Figs. 6-10) for motion stabilization in a digital platform, the computer-implemented method comprising:
receiving, from one or more sensor devices, motion data associated with a user device;
processing the motion data to generate processed motion data that reflects motion of a screen of the user device [0010] The operations can include processing the image data and the motion data with an image correction model to generate augmented image data. In some implementations, the augmented image data can include an augmented image) and comprises one or more of intensity of the motion of the screen or direction of the motion of the screen ([0058] For example, motion blur masking can involve adjusting frame motion to follow the specific direction of the motion blur. Alternatively and/or additionally, motion blur masking can include limiting image stabilization and/or adding motion to the image).
generating, using a motion stabilization model and based on the processed motion data, stabilization adjustment data by applying the motion data to the motion stabilization model; ([0007] The one or more sensors can include one or more optical image stabilization sensors. The sensor data can include optical image stabilization data, and determining an estimated motion blur can include generating a two-dimensional pixel offset based at least in part on the optical image stabilization data); and
adjusting one or more user interface elements associated with a user interface of the user device based on the stabilization adjustment data ([0010] The operations can include processing the image data and the motion data with an image correction model to generate augmented image data. In some implementations, the augmented image data can include an augmented image. The image correction model can be trained to: generate an estimated motion blur masking based on a stabilized virtual camera pose: generate an estimated frame deblur based on a motion blur kernel to generate a sharpening kernel using one or more polynomial filters: and correct an image based at least in part on the estimated motion blur masking and the sharpening kernel. The operations can include providing the augmented images to a user. Also see [0029]
As per claim 2, Shi further discloses that the computer-implemented method of claim 1, wherein adjusting the one or more user interface elements comprises transmitting computer-executable instructions configured to change a position of the one or more user interface elements relative to the user interface ([0124] FIG. 4 depicts three example results for three different stabilization implementations. The first result 402 depicts a corrected image generated using partial-strength electronic image stabilization masking only. The second result 404 depicts a corrected image generated using full-strength electronic image stabilization masking. The third result 406 depicts a corrected image generated using deblur and tuned electronic image stabilization. Examiner’s note: Fig. 4 illustrates adjusting or sharpening one or more user interface elements as shown in Fig. 4. [0125] in particular, as shown in 404, full-strength masking can make sharpness issues more evident while also causing shaping issues 408. The systems and methods disclosed herein can rely on sensor data and polynomial filters to generate a sharpening kernel that can be used to deblur and sharpen the image to provide for better shape consistency 410 with better image sharpness and deblur. The use of sensor data and polynomial filters can allow for a lessened need for electronic image stabilization masking).
As per claim 3 , Shi further discloses that the computer-implemented method of claim 1, further comprising adjusting, using the motion stabilization model, a position and orientation of a display content on the screen of the user device ([0133] At 612, the computing system can generate an augmented image by applying the sharpening kernel to the image. The augmented image may be a corrected image that has been deblurred and stabilized. Alternatively and/or additionally, the augmented image can be generated by applying the motion blur kernel and the motion blur masking to the image. The augmented image may be provided to a user. For example, the augmented image may be output for display to a user or transmitted to a computing device of the user.
As per claim 4, Shi further discloses that the computer-implemented method of claim 3, wherein adjusting the position and the orientation of the display content comprises interpolating one or more frames and applying spatial transformations to reduce motion blur ([0047] The systems and methods for image data augmentation can include motion blur masking. For example, an electronic image stabilization system can be used that can mask the image to provide a more stabilized appearance to videos and image capture. In some implementations, the systems and methods can reduce motion blur masking strength based on the estimated motion blur. Also see [0053-0054 and [0058]).
As per apparatus claims 8-11, these claims are also rejected under similar citations given to the method claims 1-4, respectively.
As per storage-medium claims 15-18, these claims are also rejected under similar citations given to the method claims 1-4, respectively.
Claim Rejections - 35 USC § 102
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.
5. Claims 1-3, 5-10, 12-17, 19 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang (US 20210263586 A1).
Wang is directed to a display apparatus and a mobile phone for content adjustment based on motion of a vehicle and an eye gaze of an occupant.
As per claim 1, Wang discloses a computer-implemented method for motion stabilization in a digital platform, the computer-implemented method comprising (see Fig. 2, wherein a circuitry 202 may be further configured to adjust or stabilize the movement of the displayed content 404 on the display screen 402 based on the determined second degree of adjustment corresponding to the other motion signal (i.e. new value of capture motion or vibration);
receiving, from one or more sensor devices, motion data associated with a user device; ([0050] The circuitry 202 may be configured to determine the direction and the extent (length) of the motion/vibration from the received first motion signal captured from the first motion sensor 314);
processing the motion data to generate processed motion data that reflects motion of a screen of the user device and comprises one or more of intensity of the motion of the screen or direction of the motion of the screen ([0050] The circuitry 202 may be configured to determine the direction and the extent (length) of the motion/vibration from the received first motion signal captured from the first motion sensor 314. For example, as per FIG. 4B, there is shown a motion or movement of the display apparatus 306 in a right direction as indicated by the horizontal motion component 406);
generating, using a motion stabilization model and based on the processed motion data, stabilization adjustment data by applying the motion data to the motion stabilization model ([0013] FIG. 8 is a flowchart that illustrates exemplary operations for content adjustment based on the vehicle motion using the machine learning model. [0075] The circuitry 202 may be further configured to adjust or stabilize the movement of the displayed content 404 on the display screen 402 based on the determined second degree of adjustment corresponding to the other motion signal (i.e. new value of capture motion or vibration);
and
adjusting one or more user interface elements associated with a user interface of the user device based on the stabilization adjustment data ([0033] The circuitry 202 may include suitable logic, circuitry, interfaces, and/or code that may be configured to execute a set of operations, such as, but not limited to, control of the display screen 106 to display the content 120, control of the first motion sensor 108 to capture the first motion signal, control of the image capturing device 110 to capture the first image of the occupant 118, and/or, adjustment/stabilization of the movement of the content 120 on the display screen 106 based on the captured first motion signal). Also see claim 14, wherein the mobile phone according to claim 13, wherein the circuitry is further configured to stabilize a display position of the portion on the display screen to adjust the movement of the portion of the displayed content).
As per claim 2, Wang further discloses that the computer-implemented method of claim 1, wherein adjusting the one or more user interface elements comprises transmitting computer-executable instructions configured to change a position of the one or more user interface elements relative to the user interface ([0029] In an embodiment, the display apparatus 102 may be configured to stabilize a display position of the portion on the display screen 106 to adjust the movement of the portion of the displayed content 120).
As per claim 3, Wang further discloses that the computer-implemented method of claim 1, further comprising adjusting, using the motion stabilization model, a position and orientation of a display content on the screen of the user device ([0029] In an embodiment, the display apparatus 102 may be configured to stabilize a display position of the portion on the display screen 106 to adjust the movement of the portion of the displayed content 120. [0051] The circuitry 202 may be further configured to stabilize a display position of the portion 412 on the display screen 402 to adjust the movement or motion of the portion 412 of the displayed content 404. The display position may be an area (i.e. focus point or focus area where the occupant 302 may be looking) of the display screen 402 where the portion 412 of the content 404 is displayed. In some embodiments, the circuitry 202 may stabilize the movement or motion of the region 410 of the eye gaze of the occupant 302 on the display screen 402. For example, to adjust the movement of the portion 412, the circuitry 202 may be configured to shift the portion 412 of the displayed content 404 in left-right directions and/or in up-downward directions (as shown in FIGS. 4A and 4B) based on the horizontal motion component 406 and/or the vertical motion component 408 of the first component of the linear motion, indicated by the first motion signal. Also see [0070).
As per claim 5, Wang further discloses that the computer-implemented method of claim 1, further comprising: retrieving, from a database, user profile data associated with a user, the user profile data comprising accessibility data for the user ([0068] In an embodiment, the one or more first driving parameters associated with the occupant 302 may indicate a driving behavior of the occupant 302 (i.e. current driver) of the vehicle 304. The circuitry 202 may be configured to recognize the occupant 302 from the capture first image based on face recognition techniques, and identify or retrieve driver profile information associated with the recognized occupant 302, where the driver profile information may indicate the driving behavior (i.e. learning behavior, experienced driving behavior, soft driving behavior, or rough driving behavior). In some embodiments, the circuitry 202 may retrieve the driving behavior of the currently recognized occupant 302 from the server or from the memory 204. The driving behavior of the current occupant 302 (as the driver) may be one of the driving behaviors (i.e. driving pattern information) on which the neural network model 602 may be trained to determine the corresponding degree of adjustment for a particular driving behavior).
As per claim 6, Wang further discloses that the computer-implemented method of claim 5, wherein adjusting the one or more user interface elements further comprises adjusting the one or more user interface elements based on the user profile data ([0068]The circuitry 202 may be configured to recognize the occupant 302 from the capture first image based on face recognition techniques, and identify or retrieve driver profile information associated with the recognized occupant 302, where the driver profile information may indicate the driving behavior (i.e. learning behavior, experienced driving behavior, soft driving behavior, or rough driving behavior)).
As per claim 7, Wang further discloses that the computer-implemented method of claim 1, wherein the motion data is received from the one or more sensor devices comprising one or more accelerometers ([0022] Examples of the first motion sensor 108 may include, but are not limited to, an accelerometer, a gyroscope, a tilt sensor, and/or other motion detection sensors).
As per apparatus claims 8-10, and 12-14, these claims are also rejected under similar citations given to the method claims 1-3, and 5-7, respectively.
As per storage-medium claims 15-17 and 19-20, these claims are also rejected under similar citations given to the method claims 1-3, and 5-7, respectively.
Conclusion
6. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20230336873 A1 discloses methods, systems, and apparatus, including computer programs stored on a computer-readable storage medium, for video stabilization. In some implementations, a computer system obtains frames of a video captured by a recording device using an optical image stabilization (OIS) system. The computing system receives (i) OIS position data indicating positions of the OIS system during capture of the frames, and (ii) device position data indicating positions of the recording device during capture of the frames. The computing system determines a first transformation for a particular frame based on the OIS position data for the particular frame and device position data for the particular frame. The computing system determines a second transformation for the particular frame based on the first transformation and positions of the recording device occurring after capture of the particular frame. The computing system generates a stabilized version of the particular frame using the second transformation (Abstract).
US 20200267320 A1 discloses an electronic device includes a camera; a motion sensor; a memory; and at least one processor. The at least one processor may be configured to acquire motion information of the electronic device from the motion sensor according to executing an image acquisition mode; determine an image stabilization scheme based on at least one part of the motion information; and perform a stabilization operation on at least one image acquired through the camera, based on the determined image stabilization scheme. The image stabilization scheme may include a first stabilization scheme for correcting shaking of the at least one image based on a first margin region; and a second stabilization scheme for correcting shaking of the at least one image based on a second margin region larger than the first margin region (Abstract).
US 20180220073 A1 -discloses in a method of electronic image stabilization, a processor buffers image data into a memory buffer, the image data being obtained by the processor from an image sensor disposed in an electronic device. The processor obtains motion data from a motion sensor disposed in the electronic device, wherein the motion data corresponds with a time of capture of the image data. The processor analyzes the motion data to determine a stabilization correction to apply to the image data. The processor applies the determined stabilization correction to the image data to achieve stabilized image data. The determined stabilization correction is applied, and the stabilized image data is achieved, by the processor without requiring a transfer of the image data from the memory buffer to a graphics processing unit. The stabilized image data is output (Abstract).
US 10447926 B1 discloses a video capture device may include multiple cameras that simultaneously capture video data. The video capture device may include one or more motion sensors that track the motion of the video capture device during video capture. Using the motion data, motion vectors can be calculated and used by an encoder to compress and encode a stream of video data. The motion vectors calculated for one stream of video data can then be used to compress and encode a second stream of video data due to the symmetry of a first camera that captured the first video stream and a second camera that captured the second video stream. The video capture device and/or remote computing resources may stitch together the first and second video streams to generate a panoramic video (Abstract).
US 20110234825 A1 discloses embodiments of the present invention provide a control system for video processes that selectively control the operation of motion stabilization processes. According to the present invention, motion sensor data indicative of motion of a mobile device may be received and processed. A determination may be made by comparing processed motion sensor data to a threshold. Based on the determination, motion stabilization may be suspended on select portions of a captured video sequence (Abstract).
7. Any inquiry concerning this communication or earlier communications from the examiner should be directed to TADESSE HAILU whose telephone number is (571)272-4051; and the email address is Tadesse.hailu@USPTO.GOV. The examiner can normally be reached Monday- Friday 9:30-5:30 (Eastern time).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bashore, William L. can be reached (571) 272-4088. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TADESSE HAILU/Primary Examiner, Art Unit 2174
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