DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This action is responsive to the amendments and remarks received 13 April 2026. Claims 1, 2 and 6 - 14 are currently pending.
The amendment to the claims filed on 13 April 2026 does not comply with the requirements of 37 CFR 1.121(c) because each claim has not been provided with the proper status identifier, for example, claim 12 does not include the proper status identifier. Amendments to the claims filed on or after July 30, 2003 must comply with 37 CFR 1.121(c) which states:
(c) Claims. Amendments to a claim must be made by rewriting the entire claim with all changes (e.g., additions and deletions) as indicated in this subsection, except when the claim is being canceled. Each amendment document that includes a change to an existing claim, cancellation of an existing claim or addition of a new claim, must include a complete listing of all claims ever presented, including the text of all pending and withdrawn claims, in the application. The claim listing, including the text of the claims, in the amendment document will serve to replace all prior versions of the claims, in the application. In the claim listing, the status of every claim must be indicated after its claim number by using one of the following identifiers in a parenthetical expression: (Original), (Currently amended), (Canceled), (Withdrawn), (Previously presented), (New), and (Not entered).
(1) Claim listing. All of the claims presented in a claim listing shall be presented in ascending numerical order. Consecutive claims having the same status of “canceled” or “not entered” may be aggregated into one statement (e.g., Claims 1–5 (canceled)). The claim listing shall commence on a separate sheet of the amendment document and the sheet(s) that contain the text of any part of the claims shall not contain any other part of the amendment.
(2) When claim text with markings is required. All claims being currently amended in an amendment paper shall be presented in the claim listing, indicate a status of “currently amended,” and be submitted with markings to indicate the changes that have been made relative to the immediate prior version of the claims. The text of any added subject matter must be shown by underlining the added text. The text of any deleted matter must be shown by strike-through except that double brackets placed before and after the deleted characters may be used to show deletion of five or fewer consecutive characters. The text of any deleted subject matter must be shown by being placed within double brackets if strike-through cannot be easily perceived. Only claims having the status of “currently amended,” or “withdrawn” if also being amended, shall include markings. If a withdrawn claim is currently amended, its status in the claim listing may be identified as “withdrawn—currently amended.”
(3) When claim text in clean version is required. The text of all pending claims not being currently amended shall be presented in the claim listing in clean version, i.e., without any markings in the presentation of text. The presentation of a clean version of any claim having the status of “original,” “withdrawn” or “previously presented” will constitute an assertion that it has not been changed relative to the immediate prior version, except to omit markings that may have been present in the immediate prior version of the claims of the status of “withdrawn” or “previously presented.” Any claim added by amendment must be indicated with the status of “new” and presented in clean version, i.e., without any underlining.
(4) When claim text shall not be presented; canceling a claim.
(i) No claim text shall be presented for any claim in the claim listing with the status of “canceled” or “not entered.”
(ii) Cancellation of a claim shall be effected by an instruction to cancel a particular claim number. Identifying the status of a claim in the claim listing as “canceled” will constitute an instruction to cancel the claim.
(5) Reinstatement of previously canceled claim. A claim which was previously canceled may be reinstated only by adding the claim as a “new” claim with a new claim number.
Claim Objections
The objections to claims 1 and 12, due to minor informalities, are hereby withdrawn in view of the amendments and remarks received 13 April 2026.
Response to Arguments
Applicant's arguments filed 13 April 2026 have been fully considered but they are not persuasive.
On page 7 of the remarks the Applicant’s Representative argues that Diessner et al. fail “to disclose, teach, or suggest calculating a trailer angle without using a location of the towball of the vehicle.” The Applicant’s Representative argues that Diessner et al. teach “that it is necessary to first identify the position of the hitch ball in the images, because ‘[t]he trailer angle detection system rotates the field of view around the tip of hitch.’” Therefore, the Applicant’s Representative argues that Diessner et al. is “different from claim 1, which requires calculating first and second angle estimations without using a location of the towball of the vehicle.”
The Examiner respectfully disagrees.
The Examiner asserts that, at least, Diessner et al. disclose “calculating first and second angle estimations without using a location of the towball of the vehicle”, see at least the abstract, figures 1, 2 and 6, page 1 paragraphs 0005 and 0015, page 2 paragraphs 0023 - 0024, page 3 paragraphs 0035 - 0037, 0040 and 0045, page 4 paragraphs 0047 and 0049 - 0051 and page 5 claims 1, 5 and 6 of Diessner et al. wherein they disclose that the “field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data” [0024], that once “a trailer has been recognized or newly calibrated, the trailer angle detection system is ready to begin normal operation, referred to herein as steady state running. In steady state running, the trailer angle detection system starts producing an estimated trailer angle and angular rate of change, along with the system status, for each input video frame of captured image data” [0035], that two “different approaches are used in concert to calculate the trailer angle. A kinematic model… and an analysis of the movement of visual features from the video frame, relative to a reference frame, is used” [0036], that in “order to track the movement of the trailer in video stream, the trailer angle detection system uses several algorithms developed for computer vision to calculate how much angular difference there is between the current video frame and the reference frame” [0040], that for “features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame. The absolute measured angle of the trailer is the consensus angle computed above, plus the offset angle for the current reference image” [0047] and a “trailer angle detection system for a vehicle towing a trailer, said trailer angle detection system comprising: a camera disposed at a rear portion of a vehicle so as to have a field of view exterior and rearward of the vehicle; an image processor operable to process frames of image data captured by said camera… wherein said trailer angle detection system determines feature vectors of the determined trailer by determining, via processing by said image processor of frames of captured image data, features that have similar angular changes between a current frame of image data captured by said camera and a previous frame of image data captured by said camera… wherein, responsive to movement of the trailer relative to the vehicle, and via processing by said image processor of frames of captured image data, said trailer angle detection system tracks determined feature vectors over multiple frames of captured image data for different positions of the determined trailer relative to the vehicle; and wherein said trailer angle detection system determines angle of the determined trailer relative to the vehicle responsive to tracking of determined feature vectors of the determined trailer present in the field of view of said camera over multiple frames of captured image data” [claim 1].
The Examiner asserts that, as shown herein above and in the cited portions, Diessner et al. disclose that the trailer angle is determined based on calculating the angular differences between features in a current video frame and matching features in a reference/previous frame. The Examiner asserts that the angular differences between matching features in the current and reference/previous video frames calculated by Diessner et al., corresponding to calculated angle estimations, depend only on the movement of the matching features from the current video frame relative to the reference/previous video frame. Furthermore, the Examiner asserts that Diessner et al. disclose that the angular differences between matching features in the current and reference/previous video frames indicate how much angular difference there is between the current and reference/previous video frames. Nowhere in Diessner et al. is it disclosed, suggested, or implied that their calculations of angular differences between matching features in current and reference/previous video frames, corresponding to the claimed first and second angle estimations, uses or requires a location of a towball of the vehicle.
Therefore, the Examiner asserts that, at least, Diessner et al. disclose “calculating first and second angle estimations without using a location of the towball of the vehicle.”
On page 8 of the remarks the Applicant’s Representative argues that the previously “applied references fail to disclose, teach, or suggest the features of ‘calculating a first angle estimation, the first angle estimation characterizing a pivot angle in a horizontal plane between the first feature on the first image and the first feature on the second image with respect to a fix point of the towing vehicle, the fix point being a position of the camera... calculating a second angle estimation, the second angle estimation characterizing a pivot angle in a horizontal plane between the second feature on the first image and the second feature on the second image with respect to the fix point of the towing vehicle; and... calculating the yaw angle based on the first and second angle estimations... wherein the method does not use a location of a towball of the towing vehicle,’”. Initially, the Applicant’s Representative asserts that, during an interview with the Examiner, the Examiner indicated that Diessner et al. disclose “two processes: a ‘kinetic model’ and an ‘analysis of movement of visual features’” and “argued that, while the kinetic model approach required the location of the towball, the separate analysis does not.” The Applicant’s Representative argues that Diessner et al. teach “that these two approaches are ‘used in concert to calculate the trailer angle.’” The Applicant’s Representative thus argues that “one skilled in the art would understand that both approaches are required to calculate trailer angle” and that Diessner et al. therefore do “not disclose a method of determining yaw angle that excludes the steps of the kinetic model, which requires the location of the towball.” Furthermore, the Applicant’s Representative argues that Diessner et al. teach “that a trailer must be calibrated before either approach can be used” and “that the location of the towball is required to perform calibration.” The Applicant’s Representative thus argues that “under either approach disclosed by Diessner for steady state operation, the location of the towball would be required, since the trailer must first be calibrated prior to steady state operation” and that Diessner et al. “is therefore different from claim 1, which does not use the location of the towball in determining yaw angle.”
The Examiner respectfully disagrees.
Initially, the Examiner asserts that they did not argue that “the kinetic model approach required the location of the towball” during the interview. Furthermore, the Examiner asserts that nowhere in Diessner et al. is it disclosed that their kinematic model uses the location of the towball to calculate the trailer angle, see at least page 3 paragraph 0036 - 0037 of Diessner et al. wherein they disclose that “ to calculate the trailer angle. A kinematic model of the movement of a car and trailer is used, and an analysis of the movement of visual features from the video frame, relative to a reference frame, is used” [0036] and that the “kinematic model provides an estimate based on the geometries of the towing vehicle and trailer, the steering angle, and the velocity” [0037].
Moreover, the Examiner asserts that the instant claims merely require that the claimed method does not use a location of a towball of the towing vehicle, i.e., the instant claims merely require that none of the claimed steps of the method use a location of a towball of the towing vehicle.
In addition, the Examiner asserts that, at least, Diessner et al. disclose the aforementioned disputed claim limitations, see at least the abstract, figures 1, 2 and 6, page 1 paragraphs 0005 and 0015 - 0016, page 2 paragraphs 0023 - 0024, page 3 paragraphs 0035 - 0037, 0040, 0042 and 0045, page 4 paragraphs 0047 and 0049 - 0051 and page 5 claims 1, 5 and 6 of Diessner et al. wherein they disclose that the “field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data” [0024], that once “a trailer has been recognized or newly calibrated, the trailer angle detection system is ready to begin normal operation, referred to herein as steady state running. In steady state running, the trailer angle detection system starts producing an estimated trailer angle and angular rate of change, along with the system status, for each input video frame of captured image data” [0035], that two “different approaches are used in concert to calculate the trailer angle. A kinematic model… and an analysis of the movement of visual features from the video frame, relative to a reference frame, is used” [0036], that in “order to track the movement of the trailer in video stream, the trailer angle detection system uses several algorithms developed for computer vision to calculate how much angular difference there is between the current video frame and the reference frame” [0040], that the “algorithm takes the set of features separately detected in the current frame and the reference frame, and finds the correspondence” [0042], that for “features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame. The absolute measured angle of the trailer is the consensus angle computed above, plus the offset angle for the current reference image” [0047] and a “trailer angle detection system for a vehicle towing a trailer, said trailer angle detection system comprising: a camera disposed at a rear portion of a vehicle so as to have a field of view exterior and rearward of the vehicle; an image processor operable to process frames of image data captured by said camera… wherein said trailer angle detection system determines, via processing by said image processor of frames of captured image data, feature vectors of the determined trailer; wherein said trailer angle detection system determines feature vectors of the determined trailer by determining, via processing by said image processor of frames of captured image data, features that have similar angular changes between a current frame of image data captured by said camera and a previous frame of image data captured by said camera… wherein, responsive to movement of the trailer relative to the vehicle, and via processing by said image processor of frames of captured image data, said trailer angle detection system tracks determined feature vectors over multiple frames of captured image data for different positions of the determined trailer relative to the vehicle; and wherein said trailer angle detection system determines angle of the determined trailer relative to the vehicle responsive to tracking of determined feature vectors of the determined trailer present in the field of view of said camera over multiple frames of captured image data” [claim 1].
The Examiner asserts that, as shown herein above and in the cited portions, Diessner et al. disclose a process for determining a yaw angle of a trailer in relation to a vehicle by capturing video frames, determining features in a current video frame and a reference/previous frame, calculating the angular differences between the features in the current video frame and matching features in the reference/previous frame and calculating the trailer angle based on the calculated angular differences. The Examiner asserts that none of the steps of the aforementioned process disclosed by Diessner et al. use a location of a towball of the vehicle. Additionally, the Examiner asserts that, at least, the angle determination process based on the analysis of the movement of visual features disclosed by Diessner et al. does not use a location of a towball of the vehicle when determining a yaw angle of a trailer with respect to the vehicle and corresponds to the aforementioned disputed claim limitations. In addition, the Examiner asserts that, for example, claims 1, 5 and 6 on page 5 of Diessner et al. also describe and disclose a system for determining an angle of trailer relative to a vehicle that does not use a location of a towball of the vehicle nor use of a kinematic model.
Therefore, the Examiner asserts that, at least, Diessner et al. disclose the aforementioned disputed claim limitations.
Claim Rejections - 35 USC § 103
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 2, 6 and 8 - 13 are rejected under 35 U.S.C. 103 as being unpatentable over Diessner et al. U.S. Publication No. 2018/0276839 A1 in view of Haja et al. German Publication No. DE 102011113197 A1. The Examiner notes that citations to Haja et al. correspond the machine translation previously provided.
- With regards to claim 1, Diessner et al. disclose a method for determining a yaw angle of a trailer with respect to a longitudinal axis of a towing vehicle, (Diessner et al., Abstract, Figs. 1 - 6, Pg. 1 ¶ 0005 and 0015 - 0017, Pg. 3 ¶ 0035 - 0040, Pg. 3 ¶ 0045 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6) the method comprising: - capturing at least a first image and a second image of the trailer using a camera, (Diessner et al., Abstract, Figs. 3 - 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037, 0040 and 0045, Pg. 4 ¶ 0053 - 0055, Pg. 5 Claims 1, 5 and 6) an orientation of the trailer with respect to the towing vehicle being different on the at least first and second images; (Diessner et al., Abstract, Fig. 8, Pg. 3 ¶ 0029 - 0037 and 0040, Pg. 3 ¶ 0045 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6) - determining at least a first feature and a second feature of the trailer which are visible on the first and second images, wherein the first and second features are arranged at different positions of the trailer; (Diessner et al., Abstract, Pg. 1 ¶ 0005, Pg. 2 ¶ and 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040 - 0042) - calculating a first angle estimation, the first angle estimation characterizing a pivot angle in a horizontal plane between the first feature on the first image and the first feature on the second image with respect to a fix point of the towing vehicle, (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6 [“The field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data”, “matched features that are on the trailer will have similar vector angles or low angular differences in position between the current and the reference frame, while matched features not on the trailer will have random angular changes or differences or dissimilar angular differences of vectors of features over multiple frames of captured image data. For example, features determined on a trailer, as the trailer moves relative to the vehicle (such as during a turning maneuver of the vehicle and trailer) will have similar angular feature vectors (and thus the differences between the vector angles will be low and similar or non-random) in that the features move together relative to the vehicle, while features that are not indicative of features on the trailer, such as features of an object on the ground, will have dissimilar or random angular differences or changes as they move over multiple frames of captured image data, due to the non-uniform movement of the vehicle relative to the object, with the field of view of the camera changing relative to the object” and “For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame”]) the fix point being a position of the camera; (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051 [“The field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data. The field of view is shown in FIG. 7, where features are detected only in the white regions, and not the black regions of the mask”, “In order to track the movement of the trailer in video stream, the trailer angle detection system uses several algorithms developed for computer vision to calculate how much angular difference there is between the current video frame and the reference frame” and “For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame. The absolute measured angle of the trailer is the consensus angle computed above, plus the offset angle for the current reference image”]) - calculating a second angle estimation, the second angle estimation characterizing a pivot angle in a horizontal plane between the second feature on the first image and the second feature on the second image with respect to the fix point of the towing vehicle; (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6 [“The field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data”, “matched features that are on the trailer will have similar vector angles or low angular differences in position between the current and the reference frame, while matched features not on the trailer will have random angular changes or differences or dissimilar angular differences of vectors of features over multiple frames of captured image data. For example, features determined on a trailer, as the trailer moves relative to the vehicle (such as during a turning maneuver of the vehicle and trailer) will have similar angular feature vectors (and thus the differences between the vector angles will be low and similar or non-random) in that the features move together relative to the vehicle, while features that are not indicative of features on the trailer, such as features of an object on the ground, will have dissimilar or random angular differences or changes as they move over multiple frames of captured image data, due to the non-uniform movement of the vehicle relative to the object, with the field of view of the camera changing relative to the object” and “For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame”]) and - calculating the yaw angle based on the first and second angle estimations, (Diessner et al., Abstract, Figs. 2 - 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 3 ¶ 0040 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6) wherein the calculating of the first and second angle estimations comprises determining vectors between the fix point and the first and second features in the first and second images, (Diessner et al., Abstract, Fig. 2, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6) and wherein the method does not use a location of a towball of the towing vehicle. (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037, 0040, 0042 and 0045, Pg. 4 ¶ 0047 and 0049 - 0051, Pg. 5 Claims 1, 5 and 6) Diessner et al. fail to disclose explicitly determining optical rays between the fix point and the features, and the determining comprising using camera calibration information of the camera to transform positions of the first and second features into the optical rays. Pertaining to analogous art, Haja et al. disclose wherein the calculating of the first and second angle estimations comprises determining optical rays between the fix point and the first and second features in the first and second images, (Haja et al., Fig. 3, Pg. 1 ¶ 0001 and 0006 - 0009, Pg. 1 ¶ 0013 - Pg. 2 ¶ 0015, Pg. 2 ¶ 0024 - 0027, Pg. 3 ¶ 0031 - 0033 and 0035 - 0037) the determining comprising using camera calibration information of the camera to transform positions of the first and second features into the optical rays. (Haja et al., Fig. 3, Pg. 1 ¶ 0006 - 0009, Pg. 2 ¶ 0015 and 0024 - 0027, Pg. 3 ¶ 0029 - 0031 and 0035 - 0037) Diessner et al. and Haja et al. are combinable because they are both directed towards image processing systems and methods for determining an angle between a tow vehicle and a trailer. 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 teachings of Diessner et al. with the teachings of Haja et al. This modification would have been prompted in order to enhance the base device of Diessner et al. with the well-known and applicable technique Haja et al. applied to a comparable device. Determining optical rays between the fix point and the features, as taught by Haja et al., would enhance the base device of Diessner et al. by enabling positions of the fix point and the features in images to be determined in three-dimensional real-world space so as to allow for their positions, and thus angles, to be more precisely determined and thereby improving the ability of the base device of Diessner et al. to accurately and reliably determine trailer angles between tow vehicles and trailers. Furthermore, this modification would have been prompted by the teachings and suggestions of Diessner et al. to calculate the trailer position in physical space and that camera and system parameters can be utilized to estimate real-world measurements, see at least page 2 paragraphs 0020 - 0022 and page 3 paragraphs 0031 - 0034 of Diessner et al. This combination could be completed according to well-known techniques in the art and would likely yield predictable results, in that optical rays between the fix point and the features would be determined in order to enable positions of the fix point and the features in images to be more precisely determined in three-dimensional real-world space so as to improve the ability of the base device of Diessner et al. to accurately and reliably determine trailer angles between tow vehicles and trailers. Therefore, it would have been obvious to combine Diessner et al. with Haja et al. to obtain the invention as specified in claim 1.
- With regards to claim 2, Diessner et al. in view of Haja et al. disclose the method according to claim 1, wherein on the first or second image, the yaw angle of the trailer with respect to the towing vehicle is zero or any known yaw angle which is usable as reference angle. (Diessner et al., Fig. 8, Pg. 3 ¶ 0029 - 0036, Pg. 4 ¶ 0047 - 0051, Pg. 5 Claims 1 - 6)
- With regards to claim 6, Diessner et al. in view of Haja et al. disclose the method according to claim 1, wherein in addition to the first and second features, at least one further feature of the trailer is used for calculating the yaw angle. (Diessner et al., Abstract, Figs. 4 & 6, Pg. 1 ¶ 0005, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037, Pg. 3 ¶ 0040 - Pg. 4 ¶ 0047, Pg. 4 ¶ 0051, Pg. 5 Claims 1 - 6 [“The algorithm takes the set of features separately detected in the current frame and the reference frame, and finds the correspondence. This produces a set of feature references that are deemed to have matched” and “For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame.” The Examiner asserts that one of ordinary skill in the art reading Diessner et al. would understand that Diessner et al. disclose that three or more features of the trailer may be used when calculating the trailer angle.])
- With regards to claim 8, Diessner et al. in view of Haja et al. disclose the method according to claim 1, wherein the yaw angle is calculated by establishing an average value of the first and second angle estimations or by using a statistical approach applied to the first and second angle estimations. (Diessner et al., Pg. 3 ¶ 0040 - Pg. 4 ¶ 0047, Pg. 5 Claims 1, 5 and 6)
- With regards to claim 9, Diessner et al. in view of Haja et al. disclose the method according to claim 1, further comprising determining an angle window, the angle window comprising an upper bound and a lower bound around a yaw angle, (Diessner et al., Figs. 7 & 8, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0040 - Pg. 4 ¶ 0051) determining a set of features which lead to angle estimations within the angle window, and (Diessner et al., Figs. 7 & 8, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0040 - Pg. 4 ¶ 0051) using the determined set of features for future yaw angle calculations. (Diessner et al., Figs. 7 & 8, Pg. 2 ¶ 0023 - 0027, Pg. 3 ¶ 0040 - Pg. 4 ¶ 0051)
- With regards to claim 10, Diessner et al. in view of Haja et al. disclose the method according to claim 1, wherein a value of a calculated yaw angle is increased by a certain portion or percentage in order to remedy underestimations. (Diessner et al., Pg. 3 ¶ 0040 - Pg. 4 ¶ 0051 [“For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame. The absolute measured angle of the trailer is the consensus angle computed above, plus the offset angle for the current reference image.” The Examiner asserts that “in order to remedy underestimations” is an intended use/intended result limitation and that intended use/intended result limitations are not given patentable weight, see at least MPEP § 2111.02 and § 2111.04.])
- With regards to claim 11, Diessner et al. in view of Haja et al. disclose the method according to claim 1, wherein the camera is a rear view camera of the towing vehicle. (Diessner et al., Abstract, Figs. 1, 3 - 5 & 7, Pg. 1 ¶ 0005 and 0015 - 0017, Pg. 2 ¶ 0022 - 0024, Pg. 5 Claim 1)
- With regards to claim 12, Diessner et al. disclose a system for determining a yaw angle of a trailer with respect to a longitudinal axis of a towing vehicle, (Diessner et al., Abstract, Figs. 1 - 6, Pg. 1 ¶ 0005 and 0015 - 0017, Pg. 3 ¶ 0035 - 0040, Pg. 3 ¶ 0045 - Pg. 4 ¶ 0051, Pg. 4 ¶ 0053 - 0054, Pg. 5 Claims 1, 5 and 6) the system comprising a camera for capturing images of the trailer (Diessner et al., Abstract, Figs. 3 - 5, Pg. 1 ¶ 0005 and 0015, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0029 - 0037, Pg. 4 ¶ 0053 - 0055, Pg. 5 Claim 1) and a processing entity, (Diessner et al., Abstract, Figs. 3 - 5, Pg. 1 ¶ 0015 - 0017, Pg. 2 ¶ 0023 - 0024, Pg. 4 ¶ 0053 - 0056, Pg. 5 Claim 1, Pg. 6 Claims 14 and 18) the system further being configured to execute a method comprising: - capturing at least a first image and a second image of the trailer using the camera, (Diessner et al., Abstract, Figs. 3 - 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037, 0040 and 0045, Pg. 4 ¶ 0053 - 0055, Pg. 5 Claims 1, 5 and 6) an orientation of the trailer with respect to the towing vehicle being different on the at least first and second images; (Diessner et al., Abstract, Fig. 8, Pg. 3 ¶ 0029 - 0037 and 0040, Pg. 3 ¶ 0045 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6) - determining at least a first feature and a second feature of the trailer which are visible on the first and second images, wherein the first and second features are arranged at different positions of the trailer; (Diessner et al., Abstract, Pg. 1 ¶ 0005, Pg. 2 ¶ and 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040 - 0042) - calculating a first angle estimation, the first angle estimation characterizing a pivot angle in a horizontal plane between the first feature on the first image and the first feature on the second image with respect to a fix point of the towing vehicle, (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6 [“The field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data”, “matched features that are on the trailer will have similar vector angles or low angular differences in position between the current and the reference frame, while matched features not on the trailer will have random angular changes or differences or dissimilar angular differences of vectors of features over multiple frames of captured image data. For example, features determined on a trailer, as the trailer moves relative to the vehicle (such as during a turning maneuver of the vehicle and trailer) will have similar angular feature vectors (and thus the differences between the vector angles will be low and similar or non-random) in that the features move together relative to the vehicle, while features that are not indicative of features on the trailer, such as features of an object on the ground, will have dissimilar or random angular differences or changes as they move over multiple frames of captured image data, due to the non-uniform movement of the vehicle relative to the object, with the field of view of the camera changing relative to the object” and “For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame”]) the fix point being a position of the camera; (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051 [“The field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data. The field of view is shown in FIG. 7, where features are detected only in the white regions, and not the black regions of the mask”, “In order to track the movement of the trailer in video stream, the trailer angle detection system uses several algorithms developed for computer vision to calculate how much angular difference there is between the current video frame and the reference frame” and “For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame. The absolute measured angle of the trailer is the consensus angle computed above, plus the offset angle for the current reference image”]) - calculating a second angle estimation, the second angle estimation characterizing a pivot angle in a horizontal plane between the second feature on the first image and the second feature on the second image with respect to the fix point of the towing vehicle; (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6 [“The field of view of the rear camera is centered around the tip of the hitch. This allows the system to measure trailer angle by analyzing the movement of visual features from the video frames of captured image data”, “matched features that are on the trailer will have similar vector angles or low angular differences in position between the current and the reference frame, while matched features not on the trailer will have random angular changes or differences or dissimilar angular differences of vectors of features over multiple frames of captured image data. For example, features determined on a trailer, as the trailer moves relative to the vehicle (such as during a turning maneuver of the vehicle and trailer) will have similar angular feature vectors (and thus the differences between the vector angles will be low and similar or non-random) in that the features move together relative to the vehicle, while features that are not indicative of features on the trailer, such as features of an object on the ground, will have dissimilar or random angular differences or changes as they move over multiple frames of captured image data, due to the non-uniform movement of the vehicle relative to the object, with the field of view of the camera changing relative to the object” and “For features that survive the filtering, the mean angular difference is calculated, resulting in a consensus angle that the frame differs from the reference frame”]) and - calculating the yaw angle based on the first and second angle estimations, (Diessner et al., Abstract, Figs. 2 - 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 3 ¶ 0040 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6) wherein the calculating of the first and second angle estimations comprises determining vectors between the fix point and the first and second features in the first and second images, (Diessner et al., Abstract, Fig. 2, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037 and 0040, Pg. 3 ¶ 0044 - Pg. 4 ¶ 0051, Pg. 5 Claims 1, 5 and 6) and wherein the method does not use a location of a towball of the towing vehicle. (Diessner et al., Abstract, Figs. 1, 2 & 6, Pg. 1 ¶ 0005 and 0015 - 0016, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0035 - 0037, 0040, 0042 and 0045, Pg. 4 ¶ 0047 and 0049 - 0051, Pg. 5 Claims 1, 5 and 6) Diessner et al. fail to disclose explicitly determining optical rays between the fix point and the features, and the determining comprising using camera calibration information of the camera to transform positions of the first and second features into the optical rays. Pertaining to analogous art, Haja et al. disclose wherein the calculating of the first and second angle estimations comprises determining optical rays between the fix point and the first and second features in the first and second images, (Haja et al., Fig. 3, Pg. 1 ¶ 0001 and 0006 - 0009, Pg. 1 ¶ 0013 - Pg. 2 ¶ 0015, Pg. 2 ¶ 0024 - 0027, Pg. 3 ¶ 0031 - 0033 and 0035 - 0037) the determining comprising using camera calibration information of the camera to transform positions of the first and second features into the optical rays. (Haja et al., Fig. 3, Pg. 1 ¶ 0006 - 0009, Pg. 2 ¶ 0015 and 0024 - 0027, Pg. 3 ¶ 0029 - 0031 and 0035 - 0037) Diessner et al. and Haja et al. are combinable because they are both directed towards image processing systems and methods for determining an angle between a tow vehicle and a trailer. 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 teachings of Diessner et al. with the teachings of Haja et al. This modification would have been prompted in order to enhance the base device of Diessner et al. with the well-known and applicable technique Haja et al. applied to a comparable device. Determining optical rays between the fix point and the features, as taught by Haja et al., would enhance the base device of Diessner et al. by enabling positions of the fix point and the features in images to be determined in three-dimensional real-world space so as to allow for their positions, and thus angles, to be more precisely determined and thereby improving the ability of the base device of Diessner et al. to accurately and reliably determine trailer angles between tow vehicles and trailers. Furthermore, this modification would have been prompted by the teachings and suggestions of Diessner et al. to calculate the trailer position in physical space and that camera and system parameters can be utilized to estimate real-world measurements, see at least page 2 paragraphs 0020 - 0022 and page 3 paragraphs 0031 - 0034 of Diessner et al. This combination could be completed according to well-known techniques in the art and would likely yield predictable results, in that optical rays between the fix point and the features would be determined in order to enable positions of the fix point and the features in images to be more precisely determined in three-dimensional real-world space so as to improve the ability of the base device of Diessner et al. to accurately and reliably determine trailer angles between tow vehicles and trailers. Therefore, it would have been obvious to combine Diessner et al. with Haja et al. to obtain the invention as specified in claim 12.
- With regards to claim 13, Diessner et al. in view of Haja et al. disclose a system according to claim 12, and a vehicle comprising a system (Diessner et al., Abstract, Figs. 1 - 5, Pg. 1 ¶ 0005 and 0015 - 0017, Pg. 2 ¶ 0021 - 0025, Pg. 4 ¶ 0051 - 0056) according to claim 12. ([Diessner et al. in view of Haja et al. disclose a system according to claim 12, see the analysis of claim 12 provided herein above.])
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Diessner et al. U.S. Publication No. 2018/0276839 A1 in view of Haja et al. German Publication No. DE 102011113197 A1 as applied to claim 1 above, and further in view of Singh U.S. Publication No. 2021/0064046 A1. The Examiner notes that citations to Haja et al. correspond the machine translation previously provided.
- With regards to claim 7, Diessner et al. in view of Haja et al. disclose the method according to claim 1, wherein the yaw angle is calculated by establishing a mean value based on the first and second angle estimations. (Diessner et al., Pg. 3 ¶ 0040 - Pg. 4 ¶ 0047) Diessner et al. fail to disclose explicitly establishing a median value. Pertaining to analogous art, Singh discloses wherein the yaw angle is calculated by establishing a median value based on the first and second angle estimations. (Singh, Figs. 3 & 4, Pg. 2 ¶ 0027 - 0028, Pg. 4 ¶ 0051 - 0053, Pg. 5 ¶ 0058) Diessner et al. in view of Haja et al. and Singh are combinable because they are all directed towards image processing systems and methods that determine an angle of trailer with respect to a vehicle. 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 combined teachings of Diessner et al. in view of Haja et al. with the teachings of Singh. This modification would have been prompted in order to substitute the mean value of Diessner et al. for the median value of Singh. The median value of Singh could be substituted in place of the mean value of Diessner et al. utilizing well-known techniques in the art and would likely yield predictable results, in that in the combination a median value of the trailer angles that survive the filtering of Diessner et al. would be utilized as the consensus trailer angle. This combination could be completed according to well-known techniques in the art and would likely yield predictable results, in that a median value of the trailer angles that survive the filtering of the combined base device would be utilized as the consensus angle of the trailer angle detected. Therefore, it would have been obvious to combine Diessner et al. in view of Haja et al. with Singh to obtain the invention as specified in claim 7.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Diessner et al. U.S. Publication No. 2018/0276839 A1 in view of Haja et al. German Publication No. DE 102011113197 A1 as applied to claim 1 above, and further in view of Turner U.S. Publication No. 2022/0222850 A1. The Examiner notes that citations to Haja et al. correspond the machine translation previously provided.
- With regards to claim 14, Diessner et al. in view of Haja et al. disclose the method according to claim 1, wherein determining the first and second features in the first and second images comprises a feature matching process, (Diessner et al., Abstract, Pg. 1 ¶ 0005, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0039 - 0042, Pg. 3 ¶ 0045 - Pg. 4 ¶ 0047, Pg. 5 Claims 1 - 6) the feature matching process comprising one or more algorithms. (Diessner et al., Abstract, Pg. 1 ¶ 0005, Pg. 2 ¶ 0023 - 0024, Pg. 3 ¶ 0039 - 0045) Diessner et al. fail to disclose explicitly one or more algorithms selected from the group consisting of Harris Corner Detector algorithm, Scale-Invariant Feature Transform algorithm, Speeded Up Robust Features algorithm, Binary Robust Invariant Scalable Keypoints algorithm, Binary Robust Independent Elementary Features (BRIEF) algorithm, and Oriented Features from Accelerated Segment Test (FAST) and rotated BRIEF algorithm. Pertaining to analogous art, Turner discloses wherein determining the first and second features in the first and second images comprises a feature matching process, the feature matching process comprising one or more algorithms selected from the group consisting of Harris Corner Detector algorithm, Scale-Invariant Feature Transform algorithm, Speeded Up Robust Features algorithm, Binary Robust Invariant Scalable Keypoints algorithm, Binary Robust Independent Elementary Features (BRIEF) algorithm, and Oriented Features from Accelerated Segment Test (FAST) and rotated BRIEF algorithm. (Turner, Pg. 2 ¶ 0014, Pg. 3 ¶ 0040, Pg. 5 ¶ 0051) Diessner et al. in view of Haja et al. and Turner are combinable because they are all directed image processing systems and methods that determine an angle of trailer with respect to a vehicle. 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 combined teachings of Diessner et al. in view of Haja et al. with the teachings of Turner. This modification would have been prompted in order to substitute the undisclosed feature matching algorithm(s) of Diessner et al. for the BRIEF algorithm of Turner. The BRIEF algorithm of Turner could be substituted in place of the undisclosed feature matching algorithm(s) of Diessner et al. utilizing well-known techniques in the art and would likely yield predictable results, in that in the combination the BRIEF algorithm would be utilized as the feature matching algorithm that determines the first and second features in the first and second images. This combination could be completed according to well-known techniques in the art and would likely yield predictable results, in that the BRIEF algorithm would be utilized as the feature matching algorithm of the combined base device that determines the first and second features in the first and second images. Therefore, it would have been obvious to combine Diessner et al. in view of Haja et al. with Turner to obtain the invention as specified in claim 14.
Conclusion
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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/ERIC RUSH/Primary Examiner, Art Unit 2677
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