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 .
Status of Claims
This is in response to applicant’s filing date of May 30, 2025. Preliminary amendment filed on May 30, 2025, cancelled claims 1-30 and added new claims 31-50. Claims 31-50 are currently pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on May 30, 2025, is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 120, Application 16/781,350 which is now Patent 11,697,427 and Application 18/204,146 which is now Patent 12,330,679, is acknowledged.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 31-50 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-30 of U.S. Patent No. 11, 697, 427. Although the claims at issue are not identical, they are not patentably distinct from each other because they both recite the same limitations except for negligible wording/phrasing differences.
Claim Rejections - 35 U.S.C. § 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 31-35 and 38-49 are rejected under 35 U.S.C. 103 as being unpatentable over Viente et al (US-20190272389-A1) (“Viente”),Kazuyuki Sakurai (US-20100284569-A1) (“Sakurai”), further in view of He et al (US-20150131924-A1)(“He”).
31. A navigation system for a vehicle, the system comprising:
at least one processor comprising circuitry and a memory (Viente at Figure 1, plural processor processing unit 110.),
wherein the memory includes instructions that when executed by the circuitry cause the at least one processor (Viente at Figure 1 and Para. [0005] discloses “navigation system may include at least one processor.”) to:
receive at least one captured image representative of features in an environment of the vehicle, the at least one captured image being captured by a camera of the vehicle (Viente at Figure 1, image capture device 120, and Para. [0005] which discloses “processor may be programmed to receive at least one image representative of an environment of the host vehicle. The at least one image may be received from a camera and may include a representation of the environment along the road section.”);
;
identify at least one road feature represented in the warped image (Viente at Para. [0163] which discloses “processing unit 110 may analyze the first, second, and third plurality of images to detect features within the images, such as lane markings, vehicles, pedestrians, road signs, highway exit ramps, traffic lights, road hazards, and the like.”), , and
wherein identifying the at least one road feature includes identifying at least one first point representing a leading edge of the representation of the at least one road feature in the warped image and at least one second point representing a trailing edge of the representation of the at least one road feature in the warped image (Viente at Figure 1, image capture device 120, and Para. [0005] discloses analyzing road segments to derive motion information which using broadest reasonable interpretation is a leading and trailing edge of a road segment :“processor may be programmed to receive at least one image representative of an environment of the host vehicle. The at least one image may be received from a camera and may include a representation of the environment along the road section.”);
determine a navigational action for the vehicle based on real-world coordinates associated with the identified at least one road feature represented in the warped image (Viente at Para. [0165] which discloses “processing unit 110 may cause one or more navigational responses in vehicle 200 based on information derived from two of the first, second, and third plurality of images.”); and
cause at least one actuator system of the vehicle to implement the determined navigational action (Viente at Para. [0167] which discloses that “[n]avigational responses may include, for example, a turn, a lane shift, a change in acceleration, and the like. Processing unit 110 may cause the one or more navigational responses based on the analysis performed at step 720”.).
Viente does not disclose but Sakurai discloses a process to generate a warped image based on the received at least one captured image (Sakuri at Para. [0038] discloses warping an image into a bird’s eye view: “FIG. 2C shows a bird's-eye image that is created from the original image of FIG. 2A at the point of time T-1. FIG. 2D is an image obtained by shifting the pixels of the bird's-eye image of FIG. 2C towards the vertical direction for the amount of the distance the own car has traveled from time T-1 to time T. “), wherein the warped image simulates a view of one or more of the features in the environment of the vehicle from a simulated viewpoint elevated relative to an actual position of the camera (Sakurai at Para. [0005] which discloses “bird's-eye image creation module 1820 to which the original image 1910 is inputted from the original image 1910.” Further, Sakurai at Para. [0047] which discloses “images can be offset to suppress influences of those noises, so that the lane line can be recognized with high precision.”),
Sakurai in the same field of endeavor discloses a method and system to control a driving operation of an autonomous vehicle based on the elevated view of a warped image. See Abstract and Figure 7.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the autonomous vehicle navigation of Viente to include the converting a viewpoint of the input image into a bird's eye view of Sakurai, since transforming road surface image to an elevated viewpoint, such as a bird's eye view, improves road feature accuracy by suppressing the noises present in the captured images. Those in the art would be motivated to combine the bird’s eye view image conversion of Sakurai with the autonomous vehicle navigation controller of Viente because an elevated vantage point view, such as a Bird’s eye view, would enhance an analysis of “the at least one image to determine at least one road characteristic associated with the road section.” Viente at Para. [0005].
The combination of Viente and Sakurai fails to disclose wherein the representation of the at least one road feature in the warped image is transformed in one or more respects relative to a representation of the at least one road feature in the at least one captured image.
He discloses wherein the representation of the at least one road feature in the warped image is transformed in one or more respects relative to a representation of the at least one road feature in the at least one captured image (See Para. [0004], which discuss adding pixels to a warped image to preserve shapes and straight lines which would result in a transformation of the at least one road feature.).
He suggests that adding pixels to a warped image preserves the shapes and straight lines within the input images. See Para. [0050].
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the navigation system as taught by Viente as modified by Sakurai with the addition of pixels to a warped image as taught by He with a reasonable expectation of success in order for the one or more steps in a navigation system to better recognize lanes and shapes. The teaching suggestion/motivation to combine is that by adding pixels to a transformed/warped image shapes and straight lines can be preserved as taught by He in Para. [0050].
As per claim 32, Viente, Sakurai, and He disclose a navigation system of claim 31,
wherein determining the navigational action for the vehicle based on the real-world coordinates associated with the identified at least one road feature includes comparing a location of the at least one road feature determined based on the warped image with real-world coordinates associated with the identified at least one road feature included in a navigational map (Sakurai at Para. [0054] discloses “the road surface 710 forms a flat surface that is vertical to the Y-axis. Distance 730 from the origin of the real world coordinate system to the road surface 710 is defined as H”.).
As per claim 33, Viente, Sakurai, and He disclose a navigation system of claim 31,
wherein the representation of the at least one road feature in the at least one captured image includes at least a first pixel and a second pixel (He discloses at Para. [0058] placing the added pixels in between pixels: “by adding pixels towards the middle of the image that edge of the image is moved closer to target rectangle. One example of this is shown in FIG. 4 where the added sequences of pixels 402 are placed within the image 400.”), and
wherein generating the warped image includes adding at least one additional pixel between the first pixel and the second pixel (He at Para. [0004] & Para. [0050], which discuss adding pixels to a warped image to preserve shapes and straight lines).
As per claim 34, Viente, Sakurai, and He disclose a navigation system of claim 33,
wherein adding at least one additional pixel includes applying an upscaling algorithm (He at Para. [0045] discloses upscaling/upsampling to increase the number of pixels: “upsampling are performed, the warping performed is according to the upsampled output mesh from 820.”).
As per claim 35, Viente, Sakurai, and He disclose a navigation system of claim 34,
wherein the upscaling algorithm includes at least one of a nearest-neighbor interpolation, a bilinear interpolation, a bicubic interpolation, an edge-directed interpolation, or a Fourier-transform (He at Para.[0044] discloses at least bilinear interpolation:” upsampling may be performed by using a displacement map and bilinear interpolation to warp the full resolution input image.”)..
As per claim 38, Viente, Sakurai, and He disclose a navigation system of claim 31,
wherein generating the warped image further includes applying a noise reduction algorithm (Sakurai discloses in Para. [0047] applying noise reduction to enhance the warped image: “detect and verify the lane line candidate respectively from the original image 410 and the synthesized bird's-eye image 420. Thus, the noises appearing in each of the images can be offset to suppress influences of those noises, so that the lane line can be recognized with high precision.”).
As per claim 39, Viente, Sakurai, and He disclose a navigation system of claim 31,
wherein the simulated viewpoint is elevated by between ten meters and twenty meters relative to the actual position of the camera (Sakurai discloses that an elevation is mere scaling parameters at Para. [0073] where the Application discloses which under broadest reasonable interpretation is inclusive of a range between 10-20 meters: “bird's-eye image creation module 120 creates a bird's-eye image from an original image of current time in a real world range that is set in advance such as a range of”.).
As per claim 40, Viente, Sakurai, and He disclose a navigation system of claim 31,
wherein the warped image further simulates a view of the at least one road feature in the environment of the vehicle based on a simulated camera optical axis angled downward relative to an actual optical axis of the camera by an angle of between thirty-five degrees and fifty-five degrees (Sakurai at Para. [0060] discloses a range that is inclusive of 35 and 55 degrees: “the lane line angle range 830 is defined as +-.30 degrees, and the sum of the pixel values at the synthesized bird's-eye image lane line candidate position”.).
As per claim 41, Viente, Sakurai, and He disclose a navigation system of claim 31,
wherein the identified at least one road feature includes at least one of a lane mark, a roundabout, or a curve in the road (Viente at Para. [0331] discloses that “an instruction may dictate that if a tunnel, a bridge, a roundabout, a merge-lane, a highway exit ramp, or other unique road characteristic is detected, the information should be preserved such that information related to the unique characteristic is not lost by segmentation.”).
As per claim 42, Viente, Sakurai, and He disclose a navigation system of claim 31,
wherein the determined navigational action includes at least one of braking or a change in heading direction (Viente at Para. [0406] discloses that based “on the desired navigational response, the processor (e.g., processing unit 110) may transmit electronic signals to … braking system 230”.).
As per claim 43, Viente discloses a method for navigating a vehicle (Figure 5A), the method comprising:
receiving at least one captured image including a representation of at least one road feature in an environment of the vehicle, the at least one captured image being captured by a camera of the host vehicle (Viente at Figure 1, image capture device 120, and at Para. [0005] which discloses “processor may be programmed to receive at least one image representative of an environment of the host vehicle. The at least one image may be received from a camera and may include a representation of the environment along the road section.”);
,
;
identifying a representation of the at least one road feature in the warped image (Viente at Para. [0163] which discloses “processing unit 110 may analyze the first, second, and third plurality of images to detect features within the images, such as lane markings, vehicles, pedestrians, road signs, highway exit ramps, traffic lights, road hazards, and the like.”),
wherein the representation of the at least one road feature in the warped image is transformed in one or more respects relative to the representation of the at least one road feature in the at least one captured image (Viente at Figure 1, image capture device 120, and Para. [0005] discloses analyzing road segments to derive motion information which using broadest reasonable interpretation is a leading and trailing edge of a road segment :“processor may be programmed to receive at least one image representative of an environment of the host vehicle. The at least one image may be received from a camera and may include a representation of the environment along the road section.”);
determining a navigational action for the vehicle based on the identified at least one road feature represented in the warped image (Viente at Para. [0165] which discloses “processing unit 110 may cause one or more navigational responses in vehicle 200 based on information derived from two of the first, second, and third plurality of images.”); and
causing at least one actuator system of the vehicle to implement the determined navigational action (Viente at Para. [0167] which discloses that “[n]avigational responses may include, for example, a turn, a lane shift, a change in acceleration, and the like. Processing unit 110 may cause the one or more navigational responses based on the analysis performed at step 720”.).
Viente does not disclose but Sakurai discloses a process to generating a warped image based on the received at least one captured image (Sakuri at Para. [0038] discloses warping an image into a bird’s eye view: “FIG. 2C shows a bird's-eye image that is created from the original image of FIG. 2A at the point of time T-1. FIG. 2D is an image obtained by shifting the pixels of the bird's-eye image of FIG. 2C towards the vertical direction for the amount of the distance the own car has traveled from time T-1 to time T. “), wherein the warped image simulates a view of the at least one road feature in the environment of the vehicle from a simulated viewpoint elevated relative to an actual position of the camera (Sakurai at Para. [0005] which discloses “bird's-eye image creation module 1820 to which the original image 1910 is inputted from the original image 1910.” Further, Sakurai at Para. [0047] which discloses “images can be offset to suppress influences of those noises, so that the lane line can be recognized with high precision.”),
Sakurai in the same field of endeavor discloses a method and system to control a driving operation of an autonomous vehicle based on the elevated view of a warped image. See Abstract and Figure 7.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the autonomous vehicle navigation of Viente to include the converting a viewpoint of the input image into a bird's eye view of Sakurai, since transforming road surface image to an elevated viewpoint, such as a bird's eye view, improves road feature accuracy by suppressing the noises present in the captured images. Those in the art would be motivated to combine the bird’s eye view image conversion of Sakurai with the autonomous vehicle navigation controller of Viente because an elevated vantage point view, such as a Bird’s eye view, would enhance an analysis of “the at least one image to determine at least one road characteristic associated with the road section.” Viente at Para. [0005].
The combination of Viente and Sakurai fails to disclose wherein generating the warped image includes adding at least one additional pixel to the warped image.
He discloses wherein generating the warped image includes adding at least one additional pixel to the warped image (See Para. [0004], which discuss adding pixels to a warped image to preserve shapes and straight lines).
He suggests that adding pixels to a warped image preserves the shapes and straight lines within the input images. See Para. [0050].
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the navigation system as taught by Viente as modified by Sakurai with the addition of pixels to a warped image as taught by He with a reasonable expectation of success in order for the one or more steps in a navigation system to better recognize lanes and shapes. The teaching suggestion/motivation to combine is that by adding pixels to a transformed/warped image shapes and straight lines can be preserved as taught by He in Para. [0050].
As per claim 44, Viente, Sakurai, and He disclose a method of claim 43,
wherein determining the navigational action for the vehicle based on the real-world coordinates associated with the identified at least one road feature includes comparing a location of the at least one road feature determined based on the warped image with real-world coordinates associated with the identified at least one road feature included in a navigational map (Sakurai at Para. [0054] discloses “the road surface 710 forms a flat surface that is vertical to the Y-axis. Distance 730 from the origin of the real world coordinate system to the road surface 710 is defined as H”.).
As per claim 45, Viente, Sakurai, and He disclose a method of claim 43,
wherein the simulated viewpoint is elevated by between ten meters and twenty meters relative to the actual position of the camera (Sakurai discloses that an elevation is mere scaling parameters at Para. [0073] where the Application discloses which under broadest reasonable interpretation is inclusive of a range between 10-20 meters: “bird's-eye image creation module 120 creates a bird's-eye image from an original image of current time in a real world range that is set in advance such as a range of”.).
As per claim 46, Viente, Sakurai, and He disclose a method of claim 43,
wherein the warped image further simulates a view of the at least one road feature in the environment of the vehicle based on a simulated camera optical axis angled downward relative to an actual optical axis of the camera by an angle of between thirty-five degrees and fifty-five degrees (Sakurai at Para. [0060] discloses a range that is inclusive of 35 and 55 degrees: “the lane line angle range 830 is defined as +-.30 degrees, and the sum of the pixel values at the synthesized bird's-eye image lane line candidate position”.).
As per claim 47, Viente discloses a non-transitory computer readable medium containing instructions that when executed by at least one processor, cause the at least one processor to perform a method for navigating a vehicle (Viente at Figure 1, Figure 5A, Para. [0007], and Para. [0005] discloses “navigation system may include at least one processor.”), the method comprising:
receiving at least one captured image including a representation of at least one road feature in an environment of the vehicle, the at least one captured image being captured by a camera of the host vehicle (Viente at Figure 1, image capture device 120, and at Para. [0005] which discloses “processor may be programmed to receive at least one image representative of an environment of the host vehicle. The at least one image may be received from a camera and may include a representation of the environment along the road section.”);
,
;
identifying a representation of the at least one road feature in the warped image (Viente at Para. [0163] which discloses “processing unit 110 may analyze the first, second, and third plurality of images to detect features within the images, such as lane markings, vehicles, pedestrians, road signs, highway exit ramps, traffic lights, road hazards, and the like.”),
wherein the representation of the at least one road feature in the warped image is transformed in one or more respects relative to the representation of the at least one road feature in the at least one captured image (Viente at Figure 1, image capture device 120, and Para. [0005] discloses analyzing road segments to derive motion information which using broadest reasonable interpretation is a leading and trailing edge of a road segment :“processor may be programmed to receive at least one image representative of an environment of the host vehicle. The at least one image may be received from a camera and may include a representation of the environment along the road section.”);
determining a navigational action for the vehicle based on the identified at least one road feature represented in the warped image (Viente at Para. [0165] which discloses “processing unit 110 may cause one or more navigational responses in vehicle 200 based on information derived from two of the first, second, and third plurality of images.”); and
causing at least one actuator system of the vehicle to implement the determined navigational action (Viente at Para. [0167] which discloses that “[n]avigational responses may include, for example, a turn, a lane shift, a change in acceleration, and the like. Processing unit 110 may cause the one or more navigational responses based on the analysis performed at step 720”.).
Viente does not disclose but Sakurai discloses a process to generating a warped image based on the received at least one captured image (Sakuri at Para. [0038] discloses warping an image into a bird’s eye view: “FIG. 2C shows a bird's-eye image that is created from the original image of FIG. 2A at the point of time T-1. FIG. 2D is an image obtained by shifting the pixels of the bird's-eye image of FIG. 2C towards the vertical direction for the amount of the distance the own car has traveled from time T-1 to time T. “), wherein the warped image simulates a view of the at least one road feature in the environment of the vehicle from a simulated viewpoint elevated relative to an actual position of the camera (Sakurai at Para. [0005] which discloses “bird's-eye image creation module 1820 to which the original image 1910 is inputted from the original image 1910.” Further, Sakurai at Para. [0047] which discloses “images can be offset to suppress influences of those noises, so that the lane line can be recognized with high precision.”),
Sakurai in the same field of endeavor discloses a method and system to control a driving operation of an autonomous vehicle based on the elevated view of a warped image. See Abstract and Figure 7.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the autonomous vehicle navigation of Viente to include the converting a viewpoint of the input image into a bird's eye view of Sakurai, since transforming road surface image to an elevated viewpoint, such as a bird's eye view, improves road feature accuracy by suppressing the noises present in the captured images. Those in the art would be motivated to combine the bird’s eye view image conversion of Sakurai with the autonomous vehicle navigation controller of Viente because an elevated vantage point view, such as a Bird’s eye view, would enhance an analysis of “the at least one image to determine at least one road characteristic associated with the road section.” Viente at Para. [0005].
The combination of Viente and Sakurai fails to disclose wherein generating the warped image includes adding at least one additional pixel to the warped image.
He discloses wherein generating the warped image includes adding at least one additional pixel to the warped image (See Para. [0004], which discuss adding pixels to a warped image to preserve shapes and straight lines).
He suggests that adding pixels to a warped image preserves the shapes and straight lines within the input images. See Para. [0050].
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the navigation system as taught by Viente as modified by Sakurai with the addition of pixels to a warped image as taught by He with a reasonable expectation of success in order for the one or more steps in a navigation system to better recognize lanes and shapes. The teaching suggestion/motivation to combine is that by adding pixels to a transformed/warped image shapes and straight lines can be preserved as taught by He in Para. [0050].
As per claim 48, Viente, Sakurai, and He disclose a non-transitory computer readable medium of claim 47,
wherein the representation of the at least one road feature in the at least one captured image includes at least a first pixel and a second pixel (He discloses at Para. [0058] placing the added pixels in between pixels: “by adding pixels towards the middle of the image that edge of the image is moved closer to target rectangle. One example of this is shown in FIG. 4 where the added sequences of pixels 402 are placed within the image 400.”), and
wherein generating the warped image includes adding at least one additional pixel between the first pixel and the second pixel (He at Para. [0004] & Para. [0050], which discuss adding pixels to a warped image to preserve shapes and straight lines).
As per claim 49, Viente, Sakurai, and He disclose a non-transitory computer readable medium of claim 48,
wherein adding at least one additional pixel includes applying an upscaling algorithm (He at Para. [0045] discloses upscaling/upsampling to increase the number of pixels: “upsampling are performed, the warping performed is according to the upsampled output mesh from 820.”).
Claims 36-37 are rejected under 35 U.S.C. 103 as being unpatentable over Viente, Sakurai, and He as applied to claim 31 above, and further in view of Zhaowen Wang (US-20190114742-A1)(“Wang.”).
As per claim 36, Viente, Sakurai, and He disclose a navigation system of claim 33,
Viente, Sakurai, and He do not disclose but Wang discloses wherein adding at least one additional pixel to the warped image includes applying a machine learning model (Wang discloses in Para. [0030] and upscaling process that adds pixels to an image: “an image that is 100 pixels×100 pixels will be scaled to a size of 200 pixels×200 pixels.”; further in Para. [0031] Wang discloses that the upscaling algorithm uses a machine learning model such as a neural network:” upscale tool 119 may include a selector to select the portion of the image for upscaling by the neural network 112. In this application, image is used to refer to both an entire image and a portion of an image because when input into the neural network 112 for upscaling and de-noising.”).
Wang suggest that an upscaling such as by adding pixels to an image is beneficial for removing noise or artifacts from an image. See Para. [0032]
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the navigation system as taught by Viente as modified by Sakurai and He with the addition of pixels to an image as taught by Wang with a reasonable expectation of success in order for the one or more steps in a navigation system to better recognize lanes and shapes. The teaching suggestion/motivation to combine is that by adding pixels to an image by upscaling, noise reduction can be improved as taught by Wang at Para. [0032].
As per claim 37, Viente, Sakurai, He, and wang disclose a navigation system of claim 36,
wherein the machine learning model includes at least a neural network (Wang at Para. [0004] discloses that a neural network is a machine learning model.)..
Claim 50 is rejected under 35 U.S.C. 103 as being unpatentable over Viente, Sakurai, and He as applied to claim 47 above, and further in view of Zhaowen Wang (US-20190114742-A1)(“Wang.”).
As per claim 50, Viente, Sakurai, and He disclose a non-transitory computer readable medium of claim 48,
Viente, Sakurai, and He do not disclose but Wang discloses wherein adding at least one additional pixel to the warped image includes applying a machine learning model (Wang discloses in Para. [0030] and upscaling process that adds pixels to an image: “an image that is 100 pixels×100 pixels will be scaled to a size of 200 pixels×200 pixels.”; further in Para. [0031] Wang discloses that the upscaling algorithm uses a machine learning model such as a neural network:” upscale tool 119 may include a selector to select the portion of the image for upscaling by the neural network 112. In this application, image is used to refer to both an entire image and a portion of an image because when input into the neural network 112 for upscaling and de-noising.”).
Wang suggest that an upscaling such as by adding pixels to an image is beneficial for removing noise or artifacts from an image. See Para. [0032]
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the navigation system as taught by Viente as modified by Sakurai and He with the addition of pixels to an image as taught by Wang with a reasonable expectation of success in order for the one or more steps in a navigation system to better recognize lanes and shapes. The teaching suggestion/motivation to combine is that by adding pixels to an image by upscaling, noise reduction can be improved as taught by Wang at Para. [0032].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Robani et al (US-20190025854-A1) discloses a vehicle localization using images from a set camera and then a top view image (also known as a bird's eye view) of the vehicle 105 in the environment is generated by the processor 120 using at least the four images captured by the cameras 112. Top view image generation techniques are known in the art and will not be described in detailed herein. Generally, top view image generation comprises transforming (e.g., rotating and scaling) the images using the angle of the image plane of the cameras 112 relative to a horizontal plane of the vehicle 105 (e.g., vehicle frame), projecting the transformed image onto a 2D plane, analysing the images to identify common features using image and/or object recognition techniques, and stitching (e.g., combining) the images to form a composite image. Overlapping FOVs captured by different cameras 112 may assist in the stitching operation by looking for common features in different images with overlapping FOVs for aligning images when stitching. See Abstract and Figures 4-5.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELLIS B. RAMIREZ whose telephone number is (571)272-8920. The examiner can normally be reached 7:30 am to 5:00pm.
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ELLIS B. RAMIREZ
Primary Examiner
Art Unit 3658
/ELLIS B. RAMIREZ/Examiner, Art Unit 3658
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