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. Claims 16-27 and 29-37 are pending. Bolded claim language below regards newly amended subject matter with a corresponding new rejection citation. Newly amended subject matter that is not bolded does not comprise a new rejection citation (utilizes previous interpretation that is unchanged in view of the new language) or is a newly added claim.
Claim Rejections - 35 USC § 102
3. 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)(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.
Claim(s) 36 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Jiang et al. (US Patent Application Publication 2024/0087491), herein after referred to as Jiang.
Regarding independent claim 36, Jiang discloses a computer-implemented method for an end-user to perform in-situ calibration of the imagery of the head-up display in a vehicle, the method comprising performing, by a processor of the head-up display system (Figure 4 and paragraph [0074] describes a flowchart of the calibration method for a HUD performed by a processor.):
receiving an instruction to enter a head-up display calibration mode (Paragraphs [0020] and [0085] describes sending an alignment request and alignment start prompt message to the user. Paragraphs [0074] and [0086] describes the calibration application process may be implemented in a starting up and static state of a vehicle, or may be implemented in a running process of the vehicle (each examples of receiving an instruction).); then, in response to receiving the instruction:
providing to the processor image information (image and position) on a real-world scene within a field of view of the head-up display from a vehicle sensor system (Figure 4 S401 described in paragraphs [0075]-[0076] to obtain and position information of a calibration object via a camera (vehicle sensor). The calibration object may be a static/dynamic object outside the vehicle such as a vehicle, tree, a geometric shape, running vehicle, or walking pedestrian. The exampled calibration objects describe real-world objects. Paragraph [0078] describes the calibration objects to be in regard of the field of view FOV of the HUD.);
identifying from the image information, using the processor (Paragraphs [0074]-[0076] describes a processor to perform the flowchart of figure 4.), one or more calibration-suitable features (Paragraphs [0076]-[0078] generalizes to acquire image and position information of the calibration object exampled to be an image captured by a camera, point cloud data collected by a radar, resolution, size, dimension, or a color. Said examples within the scope of calibration-suitable features since said features are described in reference to an object labeled as a calibration object.), assessing whether or not each of the at least one feature identified from the image information satisfies that satisfy a suitability criterion (overlap) for use in an alignment operations of the head-up display mode (F4 S403 determines an overlap ratio between the calibration object and projection plane such that if the object is less than a threshold it adjust a parameter of the imaging model, [0080].), each of the one or more calibration-suitable features being an identified feature that satisfies the respective suitability criterion (Paragraphs [0074]-[0078] describes a processor to perform the flowchart of figure 4 including obtaining, by a capture apparatus, an image of the calibration object including image and position information. Paragraph [0069] describes the capture apparatus to be a camera that can detect and collect image information and position information of an environment.);
projecting an image using the head-up display, wherein the image comprises an image element (calibration image) corresponding to each feature of the one or more calibration-suitable features (Figure 4 S402 and paragraphs [0077]-[0078] describes projecting a generated calibration image corresponding to the calibration object. Paragraph [0090] describes the calibration image generated may be (corresponds to) a virtual box of a quadrilateral (the geometric shape feature) comprising features that are automatically aligned (paragraphs [0085]-[0086] to the real world).); and
receiving at least one first user-input (paragraph [0085] human eye by camera) and changing the image (imaging model) in response to each first user-input, the first user input being provided to align each of the one or more image elements with a corresponding one of the one or more calibration-suitable features (Paragraphs [0085]-[0086] describes an automatic alignment process start prompt to a user for the human-eye position to be obtained by a camera in the vehicle.).
Claim Rejections - 35 USC § 103
4. 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 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) 16-22, 26, 29-32, 34-35, and 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jiang, in view of Maruyama et al. (US Patent Application 2024/0166229), herein after referred to as Maruyama.
Regarding independent claim 16, Jiang discloses a computer-implemented method for an end-user to perform in-situ calibration of the imagery of a head- up display in a vehicle, the method comprising performing, by a processor of the head-up display system (Figure 4 and paragraph [0074] describes a flowchart of the calibration method for a HUD performed by a processor.):
receiving an instruction to enter a head-up display calibration mode (Paragraphs [0020] and [0085] describes sending an alignment request and alignment start prompt message to the user. Paragraphs [0074] and [0086] describes the calibration application process may be implemented in a starting up and static state of a vehicle, or may be implemented in a running process of the vehicle (each examples of receiving an instruction).); then, in response to receiving the instruction:
obtaining information (image and position) on a real-world scene within a field of view of the head-up display from a vehicle sensor system (camera) of the vehicle, the information including an image of the real-world scene (Figure 4 S401 described in paragraphs [0075]-[0076] to obtain and position information of a calibration object via a camera (vehicle sensor). The calibration object may be a static/dynamic object outside the vehicle such as a vehicle, tree, a geometric shape, running vehicle, or walking pedestrian. The exampled calibration objects describe real-world objects (of inherently a real-world scene). Paragraph [0078] describes the calibration objects to be in regard of the field of view FOV of the HUD.);
identifying one or more calibration-suitable features from the image (Paragraphs [0076]-[0078] generalizes to acquire image and position information of the calibration object exampled to be an image captured by a camera, point cloud data collected by a radar, resolution, size, dimension, or a color. Said examples within the scope of calibration-suitable features since said features are described in reference to an object labeled as a calibration object.), by:
using the processor ([0076] describes the processor to obtain image and position information of the calibration object), performing [ ] the image obtained from the vehicle sensor system to identify at least one feature (image and position information) in the field of view (Paragraphs [0074]-[0078] describes a processor to perform the flowchart of figure 4 including obtaining, by a capture apparatus, an image of the calibration object including image and position information. Paragraph [0069] describes the capture apparatus to be a camera that can detect and collect image information and position information of an environment. While it can detect objects there is not a description of recognizing or determining what the object is, only that an object exists. Said paragraphs examples what the objects may be.),
assessing, using the processor (Paragraphs [0074]-[0076] describes a processor to perform the flowchart of figure 4.), whether or not each of the at least one identified feature satisfies a suitability criterion (overlap) for use in an alignment operation of the head-up display calibration mode (F4 S403 determines an overlap ratio between the calibration object and projection plane such that if the object is less than a threshold it adjust a parameter of the imaging model, [0080].), and
identifying from the assessment, using the processor one or more calibration-suitable features, each of the one or more calibration-suitable features being an identified feature that satisfies the respective suitability criterion (Figure 5, described in paragraph [0086] to be figure 4 implemented in the running process of the vehicle, S502 and paragraph [0090] describes the selection process of the calibration object to have a regular geometric shape, exampled as a quadrilateral, within an observation range of the human eye and the virtual image plane of the HUD (FOV). Paragraphs [0080] and [0085]-[0086] describes adjusting the imaging model automatically to align (suitability criterion) a parameter/feature based on human-eye positions so that the image projected is always fused/aligned with environment information of the real world via the quadrilateral geometric shaped calibration object.);
projecting an image using the head-up display, wherein the image comprises an image element (calibration image) corresponding to each feature of the one or more calibration-suitable features (Figure 4 S402 and paragraphs [0077]-[0078] describes projecting a generated calibration image corresponding to the calibration object. Paragraph [0090] describes the calibration image generated may be (corresponds to) a virtual box of a quadrilateral (the geometric shape feature) comprising features that are automatically aligned (paragraphs [0080] [0085]-[0086] to the real world).); and
receiving at least one first user-input (paragraph [0085] human eye by camera) and changing the image (imaging model) in response to each first user-input, the first user input being provided to align each of the one or more image elements with a corresponding one of the one or more calibration-suitable features (Paragraphs [0085]-[0086] describes an automatic alignment process start prompt to a user for the human-eye position to be obtained by a camera in the vehicle.).
Jiang does not specifically disclose object recognition on the image obtained from the vehicle sensor system to determine at least one feature in the field of view.
Maruyama discloses using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view (Paragraph [0089] describes object recognition unit 31 to recognize an object based on shape, color, and the like from the image captured by the camera.).
It would have been obvious to one skilled in the art before the effective filing date of the current application to enable Jiang’s calibration object exampled as an object with a geometric shape with the known technique of using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view yielding the predictable results of providing visual guidance as disclosed by Maruyama (paragraph [0095]).
Regarding claim 17, Jiang discloses the method as claimed in claim 16 wherein changing the image comprises at least one selected from the group comprising: a translating (Paragraph [0082] describes adjusting a relative position of the image on image on the imaging plane. An object that moves from a first position to a second position is a description of translating.), rotating, skewing or keystoning the image.
Regarding claim 18, Jiang discloses the method as claimed in claim 16 wherein the at least one identified feature comprises a plurality of calibration-suitable features (Figure 4 S401 described in paragraphs [0075]-[0076] to obtain and position information of a calibration object via a camera (vehicle sensor). The calibration object may be a static/dynamic object outside the vehicle such as a vehicle, tree, a geometric shape (quadrilateral paragraph [0090]), running vehicle, or walking pedestrian. For example, utilizing the geometric shape quadrilateral requires multiple features including: four sides, straight edges (non-curved), and four angles.).
Regarding claim 19, Jiang discloses the method as claimed in claim 18 wherein a first calibration-suitable feature of the plurality of calibration-suitable features satisfies a first suitability criterion and a second calibration-suitable feature of the plurality of calibration-suitable features satisfies a second suitability criterion different to the first suitability criterion (Geometric shape quadrilateral requires multiple features including: four sides (first criterion), straight edges (non-curved) (second criterion), and four angles (third criterion).).
Regarding claim 20, Jiang discloses the method as claimed in claim 16 wherein each suitability criterion relates to a physical property or parameter of the at least one identified feature (Geometric shape quadrilateral requires multiple features including: four sides, straight edges (non-curved), and four angles.).
Regarding claim 21, Jiang discloses the method as claimed in claim 16 wherein satisfying the suitability criterion comprises having a straight line or edge with a minimum length; or having at least two straight sides (Geometric shape quadrilateral requires multiple features including: four sides, straight edges (non-curved), and four angles.).
Regarding claim 22, Jiang discloses the method as claimed in claim 21 wherein satisfying the suitability criterion comprises a having a polygonal shape (Geometric shape quadrilateral), a circular shape or an elliptical shape.
Regarding claim 26, Jiang discloses the method as claimed in claim 16 further comprising receiving a second user- input (manual user input and/or automatic detection of human eye position via guidance of ta human machine interface/driver monitor system) and, in response to the second user-input, determining a calibration function, wherein the calibration function corresponds to the total change to the image made in response to the at least one first user-input (Figure 4 S403 described in paragraphs [0079]-[0080] to adjust the overlap between the [real world] calibration object and the projection of the calibration object/image (virtual) by feedback/input of the user. Paragraph [0067] examples adjustment by a driver including adjusting the driver seat to align the displayed/projected image to the real world. Paragraphs [0080]-[0081] example automatic adjustment by the imaging model itself based on detection of the human eye position or a simulated human eye position (camera disposed at the position of the human eye). Paragraph [0085] describes the user to send an adjustment instruction based on personal subjective experience, to adjust the parameter of the imaging model.).
Regarding independent claim 29, Jiang discloses a head-up display having a calibration mode for an end-user to perform in-situ calibration of the imagery of the head-up display in a vehicle (Figure 4 and paragraph [0074] describes a flowchart of the calibration method for a HUD performed by a processor.), wherein the head-up display comprises a processor arranged to:
receive an instruction to enter a head-up display calibration mode (Paragraphs [0020] and [0085] describes sending an alignment request and alignment start prompt message to the user. Paragraphs [0074] and [0086] describes the calibration application process may be implemented in a starting up and static state of a vehicle, or may be implemented in a running process of the vehicle (each examples of receiving an instruction).), and in response to receiving the instruction:
obtain information (image and position) on a real-world scene within a field of view of the head-up display from a vehicle sensor system (camera) of the vehicle, the information including image information of the real-world scene (Figure 4 S401 described in paragraphs [0075]-[0076] to obtain and position information of a calibration object via a camera (vehicle sensor). The calibration object may be a static/dynamic object outside the vehicle such as a vehicle, tree, a geometric shape, running vehicle, or walking pedestrian (of the real world). The exampled calibration objects describe real-world objects. Paragraph [0078] describes the calibration objects to be in regard of the field of view FOV of the HUD.);
identifying one or more calibration-suitable features from the image (Paragraphs [0076]-[0078] generalizes to acquire image and position information of the calibration object exampled to be an image captured by a camera, point cloud data collected by a radar, resolution, size, dimension, or a color. Said examples within the scope of calibration-suitable features since said features are described in reference to an object labeled as a calibration object.), by:
using the processor ([0076] describes the processor to obtain image and position information of the calibration object), performing [ ] the image information obtained from the vehicle sensor system to identify at least one feature (image and position information) in the field of view (Paragraphs [0074]-[0078] describes a processor to perform the flowchart of figure 4 including obtaining, by a capture apparatus, an image of the calibration object including image and position information. Paragraph [0069] describes the capture apparatus to be a camera that can detect and collect image information and position information of an environment. While it can detect objects there is not a description of recognizing or determining what the object is, only that an object exists. Said paragraphs examples what the objects may be.),
assessing, using the processor (Paragraphs [0074]-[0076] describes a processor to perform the flowchart of figure 4.), whether or not each of the at least one identified feature satisfies a suitability criterion (overlap) for use in an alignment operation of the head-up display calibration mode (F4 S403 determines an overlap ratio between the calibration object and projection plane such that if the object is less than a threshold it adjust a parameter of the imaging model, [0080].), and
identifying from the assessment, using the processor, one or more calibration-suitable features, each of the one or more calibration-suitable features being an identified feature that satisfies the respective suitability criterion (Figure 5, described in paragraph [0086] to be figure 4 implemented in the running process of the vehicle, S502 and paragraph [0090] describes the selection process of the calibration object to have a regular geometric shape, exampled as a quadrilateral, within an observation range of the human eye and the virtual image plane of the HUD (FOV). Paragraphs [0080] and [0085]-[0086] describes adjusting the imaging model automatically to align (suitability criterion) a parameter/feature based on human-eye positions so that the image projected is always fused/aligned with environment information of the real world via the quadrilateral geometric shaped calibration object.);
project an image, using the head-up display, wherein the image comprises an image element (calibration image) corresponding to each feature of the one or more calibration-suitable features (Figure 4 S402 and paragraphs [0077]-[0078] describes projecting a generated calibration image corresponding to the calibration object. Paragraph [0090] describes the calibration image generated may be (corresponds to) a virtual box of a quadrilateral (the geometric shape feature) comprising features that are automatically aligned (paragraphs [0080] [0085]-[0086] to the real world).); and
receive at least one first user-input (paragraph [0085] human eye by camera) and changing the image (imaging model) in response to each first user-input, the first user input being provided to align each of the one or more image elements with a corresponding one of the one or more calibration-suitable features (Paragraphs [0085]-[0086] describes an automatic alignment process start prompt to a user for the human-eye position to be obtained by a camera in the vehicle.).
Jiang does not specifically disclose object recognition on the image obtained from the vehicle sensor system to determine at least one feature in the field of view.
Maruyama discloses using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view (Paragraph [0089] describes object recognition unit 31 to recognize an object based on shape, color, and the like from the image captured by the camera.).
It would have been obvious to one skilled in the art before the effective filing date of the current application to enable Jiang’s calibration object exampled as an object with a geometric shape with the known technique of using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view yielding the predictable results of providing visual guidance as disclosed by Maruyama (paragraph [0095]).
Regarding claim 30, Jiang discloses the head-up display as claimed in claim 29 wherein changing the image comprises at least one selected from the group comprising: a translation (Paragraph [0082] describes adjusting a relative position of the image on image on the imaging plane. An object that moves from a first position to a second position is a description of translating.), rotation, skew or keystone of the image.
Regarding claim 31, Jiang discloses the head-up display as claimed in claim 29 wherein the head-up display is arranged to receive a second user-input (manual user input and/or automatic detection of human eye position) and, in response to the second user-input, determine a calibration function, wherein the calibration function represents the total change to the image made in response to the at least one first user-input (Figure 4 S403 described in paragraphs [0079]-[0080] to adjust the overlap between the [real world] calibration object and the projection of the calibration object/image (virtual) by feedback/input of the user. Paragraph [0067] examples adjustment by a driver including adjusting the driver seat to align the displayed/projected image to the real world. Paragraphs [0080]-[0081] example automatic adjustment by the imaging model itself based on detection of the human eye position or a simulated human eye position (camera disposed at the position of the human eye). Paragraph [0085] describes the user to send an adjustment instruction based on personal subjective experience, to adjust the parameter of the imaging model.).
Regarding claim 32, Jiang discloses the head-up display as claimed in claim 31 wherein the head-up display is arranged, during normal display operation, to apply the calibration function to each source image before projection (Paragraph [0106] describes applying the calibration to the display module 6032 for projection.).
Regarding claim 34, Jiang discloses the head-up display as claimed in claim 29 wherein each suitability criterion relates to a physical property or parameter of the at least one identified feature (Geometric shape quadrilateral requires multiple features including: four sides, straight edges (non-curved), and four angles.).
Regarding claim 35, Jiang discloses the head-up display as claimed in claim 29 wherein satisfying each suitability criterion comprises having at least one selected from the group comprising: a straight line or edge with a minimum length; at least two straight sides each with a minimum length; a polygonal shape with a minimum area (Geometric shape quadrilateral requires multiple features including: four sides, straight edges (non-curved), and four angles. Without a definition or claimed acceptable range for a minimum area, this is interpreted to regard the inherent threshold of a sensor to perform the function of detecting the quadrilateral. For example, if the area were of such a small size that the resolution of the camera is unable to determine the quadrilateral shape is a description of a minimum area.); or a circular or elliptical shape with an minimum dimension or area.
Jiang does not specifically disclose object recognition on the image obtained from the vehicle sensor system to determine at least one feature in the field of view.
Maruyama discloses using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view (Paragraph [0089] describes object recognition unit 31 to recognize an object based on shape, color, and the like from the image captured by the camera.).
It would have been obvious to one skilled in the art before the effective filing date of the current application to enable Jiang’s calibration object exampled as an object with a geometric shape with the known technique of using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view yielding the predictable results of providing visual guidance as disclosed by Maruyama (paragraph [0095]).
Regarding claim 37, Jiang discloses the method of claim 36, wherein the processor [ ] identify features from the image information obtained from the vehicle sensor system (Figure 5, described in paragraph [0086] to be figure 4 implemented in the running process of the vehicle, S502 and paragraph [0090] describes the selection process of the calibration object to have a regular geometric shape, exampled as a quadrilateral, within an observation range of the human eye and the virtual image plane of the HUD (FOV). Paragraphs [0085]-[0086] describes adjusting the imaging model automatically to align (suitability criterion) a parameter/feature based on human-eye positions so that the image projected is always fused/aligned with environment information of the real world via the quadrilateral geometric shaped calibration object.).
Jiang does not specifically disclose object recognition on the image obtained from the vehicle sensor system to determine at least one feature.
Maruyama discloses using object recognition on the image obtained from a vehicle sensor system to determine at least one feature (Paragraph [0089] describes object recognition unit 31 to recognize an object based on shape, color, and the like from the image captured by the camera.).
It would have been obvious to one skilled in the art before the effective filing date of the current application to enable Jiang’s calibration object exampled as an object with a geometric shape with the known technique of using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view yielding the predictable results of providing visual guidance as disclosed by Maruyama (paragraph [0095]).
5. Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jiang-Maruyama in view of Chou et al. (US Patent Application Publication 2023/0182766), herein after referred to as Chou.
Regarding claim 23, Jiang discloses the method as claimed in claim 21.
Jiang does not disclose wherein the polygonal shape is a triangular shape.
Chou discloses wherein the polygonal shape is a triangular shape (Paragraph [0070] describes calibration target to have triangle shape.).
It would have been obvious to one skilled in the art before the effective filing date of the current application to enable Jiang’s geometrical shape with the known technique of being triangular shaped yielding the predictable results of performing calibration as disclosed by Chou (paragraph [0070]) and increasing the amount of acceptable calibration objects (i.e. trees, pedestrians, quadrilateral, and now also triangular).
6. Claim(s) 27 and 33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jiang-Maruyama in view of Wan et al. (US Patent 11,953,697), herein after referred to as Wan.
Regarding claim 27, Jiang discloses the method as claimed in claim 16 wherein the step of projecting an image using the head-up display comprises:
determining an input image from the obtained information on the real-world scene (Figure 4 S401 described in paragraphs [0075]-[0076] to obtain and position information of a calibration object via a camera (vehicle sensor). The calibration object may be a static/dynamic object outside the vehicle such as a vehicle, tree, a geometric shape, running vehicle, or walking pedestrian. The exampled calibration objects describe real-world objects. Paragraph [0078] describes the calibration objects to be in regard of the field of view FOV of the HUD.);
determining a virtual image of the input image (Figure 4 S402 and paragraphs [0077]-[0078] describes generating calibration image corresponding to the calibration object.); and
illuminating the hologram to form the image (Figure 4 S402 and paragraphs [0077]-[0078] describes projecting the generated calibration image corresponding to the calibration object.).
Jiang does not disclose the virtual image to be a hologram.
Wan discloses a virtual image to be a hologram (Figure 2b reference projected images via figure 3 projector 205 including semi-transparent lens 125 described in column 6 lines 56-61.).
It would have been obvious to one skilled in the art before the effective filing date of the current application to enable Jiang’s virtual image with the known technique of a hologram yielding the predictable results of enabling the viewer to view the real image and graphical/virtual images with additional information as disclosed by Wan (column 6 lines 56-61).
Regarding claim 33, Jiang discloses the head-up display as claimed in claim 31 wherein the head-up display is further arranged to:
determine an input image from the obtained information on the real-world scene (Figure 4 S401 described in paragraphs [0075]-[0076] to obtain and position information of a calibration object via a camera (vehicle sensor). The calibration object may be a static/dynamic object outside the vehicle such as a vehicle, tree, a geometric shape, running vehicle, or walking pedestrian. The exampled calibration objects describe real-world objects. Paragraph [0078] describes the calibration objects to be in regard of the field of view FOV of the HUD.);
determine a virtual image of the input image (Figure 4 S402 and paragraphs [0077]-[0078] describes generating calibration image corresponding to the calibration object.); and
illuminate the hologram in order to project the image (Figure 4 S402 and paragraphs [0077]-[0078] describes projecting the generated calibration image corresponding to the calibration object.).
Jiang does not disclose the virtual image to be a hologram.
Wan discloses a virtual image to be a hologram (Figure 2b reference projected images via figure 3 projector 205 including semi-transparent lens 125 described in column 6 lines 56-61.).
It would have been obvious to one skilled in the art before the effective filing date of the current application to enable Jiang’s virtual image with the known technique of a hologram yielding the predictable results of enabling the viewer to view the real image and graphical/virtual images with additional information as disclosed by Wan (column 6 lines 56-61).
Allowable Subject Matter
7. Claims 24-25 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.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 24, Jiang discloses the method as claimed in claim 16. However, the cited art does not specifically disclose identifying at least one calibration-suitable feature outside of the field of view, the calibration-suitable feature outside the field of view satisfying a third suitability criterion, and providing an output for the end-user.
Response to Arguments
8. Applicant's arguments filed 6/25/2026 have been fully considered and relate towards newly amended subject matter.
In regards to argument a the following limitations are not particularly defined: suitability criterion or calibration-suitable feature. While not considered indefinite the scope of interpretation is extremely broad. In so far as the independent claims, the claims define a processor to perform identification of said criterion and features what the processor is identifying is not defined. Therefore, prior art Jiang’s discloser of detecting overlap, position, radar (inherently implying depth), dimension, and color. Each one of the disclosed features is a description of identification of that feature. For example, detecting a position of an object is a description of identifying the feature of position. Without a specific discloser of what features are being identified, any identified feature may read on the claims.
In regards to argument b, the claims state to identify calibration-suitable features that satisfy an undefined suitability criterion. First, the ability to detect said feature (exampled above) describe a satisfaction of being within the sensor range (an inherent suitability criterion). Second, as also described above, the suitability criterion itself is not defined. Therefore, any criteria, including predetermined criteria, may be utilized to disclose the subject matter.
In regards to argument bi, similar to above, Jiang is not required to disclose how the calibration object is selected (how is not claimed) but rather that it satisfies a criteria. One specific example disclose by Jiang is the overlap of figure 4 S03 that is determined between the calibration object and projection plane before the calibration object is utilized for calibration (a criteria). The object is not identified as a calibration object until it satisfies the overlap criteria. At which point the object is then considered a calibration object and can be used for calibration purposes.
The above interpretations may be overcome by specifically claimed or providing a range of acceptable values for the criteria and features.
In regards to argument bii, Maruyama is utilized to disclose using object recognition on the image obtained from a vehicle sensor system to determine at least one feature in the field of view. Jiang utilizes a camera that detects objects in its field of view. Therefore, Maruyama and Jiang are found to be in the same field of application. Maruyama is not required to disclose the entirety of the claim language (piecemeal analysis).
In regards to argument biii, Jiang is utilized to disclose the features.
In regards to argument biv, Jiang discloses in figure 4 S401 and paragraphs [0075]-[0076] to obtain and position information of a calibration object via a camera (vehicle sensor). The calibration object may be a static/dynamic object outside the vehicle such as a vehicle, tree, a geometric shape, running vehicle, or walking pedestrian. The exampled calibration objects describe real-world objects (of inherently a real-world scene).
The rest of applicant’s arguments are found to be rebutted in view of above.
This action is final necessitated by amendment.
Conclusion
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Engstle et al. (US Patent Application Publication 2023/0281873) discloses repositioning a vehicle to image a sensor outside of the FOV of the sensor system, the vehicle comprising an imaging system (Figure 1 reference vehicle 2 comprising sensor system 1. Figure 2 and paragraphs [0085]-[0087] describes calibrating the system 1 rotational and/or translational movement of the sensor system 1 for the step of calibrating the optical sensors 3 (of system 1) with calibration objects 9 comprising patterns 10. Paragraph [0086] emphasizes that movement of the system is required so that calibration objects 9 can be detected (describing the system 1 is outside of the field of view of some of the calibration objects). Further, the movement of the system 1 is suggested to be removed from the vehicle to a table 17 for easier movement, describing that system may still be mounted on the vehicle and the vehicle causing the movement of the system to image the calibration objects.).
Erdei et al. (US Patent Application Publication) discloses moving the calibration object outside relative to a vehicle (figure 1 and paragraphs [0017], [0021], and [0037]).
Wells et al. (US Patent 11,482,141) HUD calibration (Figures 7A-7B).
Wells et al. (US Patent 10,996,481) HUD calibration with robotic calibration (figure 2).
Chang et al. (US Patent Application Publication 2021/0109355) HUD calibration (Figure 3 and paragraph [0040]).
Lee et al. (US Patent Application Publication 2020/0125862) discloses using lane lines for calibration of a HUD (Figure 1B and 2).
Neilhouse (US Patent Application Publication 2010/0198506) HUD calibrating a virtual image to a real object (Figure 1).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/CHRISTOPHER E LEIBY/Primary Examiner, Art Unit 2621
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