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 .
Specification
The disclosure is objected to because of the following informalities:
In [0076] line 4, “FIG. 4B” should read “FIG. 4C”.
Appropriate correction is required.
Drawings
The drawings are objected to under 37 CFR 1.83(a) because “ROL” in Fig. 4D should be “ROI”. Any structural detail that is essential for a proper understanding of the disclosed invention should be shown in the drawing. MPEP § 608.02(d). Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
In regarding claims 1 and 11
Step 1:
Claims 1 and 11 are directed towards a process, machine, manufacture or composition of matter which is/are statutory subject matter.
Step 2A:
Claims 1 and 11 are directed to a method/system/manufacture executed by one or more processor for a lane data construction apparatus. The apparatus comprises a processor configured to generate a lane image based on semantic segmentation data including semantic information for a lane, generate a plurality of polylines using a plurality of feature points extracted from the lane image, and generate instance segmentation data including instance information related to each lane based on the plurality of polylines; and a memory operatively connected to the processor and storing data and an algorithm run by the processor.
Prong 1:The limitations listed below covers performance of the limitation that could be carried out in mental processes.
generate a lane image based on semantic segmentation data including semantic information for a lane:
This limitation could be performed mentally because a person could look at a lane image and generate a lane image using semantic information for a lane. Hence, this operation could be performed mentally, implying that the claim is directed to a mental process.generate a plurality of polylines using a plurality of feature points extracted from the lane image:
This limitation could be performed mentally because a person could look at a lane image and generate polyline predictions using feature points extracted from the lane image. Hence, this operation could be performed mentally, implying that the claim is directed to a mental process.generate instance segmentation data including instance information related to each lane based on the plurality of polylines:
This limitation could be performed mentally because a person could look at a lane image and assign instance IDs to lanes. Hence, this operation could be performed mentally, implying that the claim is directed to a mental process.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation by a mental process, then it falls within the “Mental process” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Prong 2:
This judicial exception is not integrated into a practical application. In particular, the claims only recite additional elements – an apparatus (claim 1) and computer implemented method (claim 11) are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computing component / software application.
Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim(s) is directed to an abstract idea.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception such as improvements to another technology or technical field, or other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
For a human, he/she will look at a lane image and generate a lane image based on semantic information for a lane, generate polyline predictions using feature points extracted from the lane image and generate instance IDs to each lane. The recitation of use of memory and processor to execute instruction doesn’t disclose any inventive concept since it merely invokes the use of generic computer to perform tasks that could otherwise be performed mentally.
Thus, the recited generic additional hardware/software (e.g., processor, machine-readable medium) perform no more than their basic computer function. In the court of Alice Corp. v. CLS Bank Intl, the court cites a “data processing system” with a “communications controller” and “data storage unit,” for example, —is purely functional and generic (page 16). In the specification of instant application, processor, machine-readable medium are general computer components ([0023] in publication). Generic computer-implementation of a method is not a meaningful limitation that alone can amount to significantly more than an abstract idea. Moreover, when viewed as a whole with such additional element considered as an ordered combination, claims modified by adding a generic computer are nothing more than a purely conventional computerized implementation of an idea in the general field of computer processing and do not provide significantly more than an abstract idea.
Consequently, the identified additional elements taken into consideration individually or in combination fails to amount of significantly more than the abstract idea above.
Regarding claims 2-10 and 12-20, these are dependent claims that recite limitations that extend the mental processes of their respective base claim and therefore also fall under mental steps as explained in their base claim.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(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.
Claims 1 and 11 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Xie (US Patent Pub. No.: US 11,275,955 B2).
Regarding claim 1, Xie teaches a lane data construction apparatus, comprising: a processor configured to generate a lane image based on semantic segmentation data including semantic information for a lane (a binarization module 71, configured to perform a binarization processing on a first image to obtain a binary image, the first image including lane line points and non-lane line points. Column 7 line 62), generate a plurality of polylines (A polynomial fitting is performed on coordinates of the selected plurality of lane line points in the second image, to obtain a polynomial curve of the lane line corresponding to the group. Column 6 line 58) using a plurality of feature points extracted from the lane image (a connected domain module, configured to perform a connected domain analysis on the binary image to obtain at least one connected domain in the binary image, the connected domain including a plurality of adjacent lane line points. Column 2 line 56), and generate instance segmentation data including instance information related to each lane based on the plurality of polylines (a start and end point sub-module, configured to determine a start point coordinate and/or an end point coordinate of the lane line from the polynomial curve of the lane line. Column 3 line 32); and a memory operatively connected to the processor and storing data and an algorithm run by the processor (In a possible design, the device includes a processor and a memory for storing a program which supports the device in executing the lane line processing method described above, and the processor is configured to execute the program stored in the memory. Column 3 line 41).
Method claim 11 is drawn to the method of using the corresponding apparatus claimed in claim 1. Therefore method claim 11 corresponds to apparatus claim 1 and is rejected for the same reasons of anticipation as used above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2-6 and 12-16 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US Patent Pub. No.: US 11,275,955 B2) hereinafter Xie, in view of Sakai (PCT Patent Pub. No.: WO 2026022924 A1), hereinafter Sakai.
Regarding claim 2, Xie teaches all of the elements of the claimed invention as stated in claim 1 except for the following limitations as further recited. However, Sakai teaches wherein the processor is further configured to: detect an edge portion of each lane region from the lane image (For example, the detection unit 23 estimates the shape of the lane boundary line of the portion Jx of the solid line L3 shown in Figure 2 that extends in the width direction of the road ahead of the branch point J, from an equation representing the connecting line X5. Page 10 2nd paragraph.
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) and extract intermediate points in a width direction of the lane as the feature points based on the edge portion (The connecting line X5 corresponds to feature points C8 to C11 that are not included in the point sequence, and connects line segment X3a and line segment X4c. Page 10 1st paragraph.
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); and sequentially extract the feature points every predetermined interval for a longitudinal direction of the lane (The connecting line X5 corresponds to feature points C8 to C11 that are not included in the point sequence, and connects line segment X3a and line segment X4c. Page 10 1st paragraph.
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).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Xie to incorporate the teachings of Sakai to detect an edge portion of each lane region from the lane image and extract intermediate points in a width direction of the lane as the feature points based on the edge portion and sequentially extract the feature points every predetermined interval for a longitudinal direction of the lane in order to improve lane identification accuracy.
Regarding claim 3, Xie in the combination teaches the lane data construction apparatus of claim 1, wherein the processor is further configured to: determine whether a first condition in which a distance between adjacent feature points among the plurality of feature points is less than a predetermined distance reference value are met (The adjacent points may include pixel points next to each other in their coordinate positions, and may also include pixel points having a small distance therebetween, e.g., a distance not exceeding a set value. Then, the lane line points in the first image are grouped by using the connected domains. Column 5 line 12); and classify feature points meeting the first condition among the plurality of feature points into a same feature point group (Then, the lane line points in the first image are grouped by using the connected domains. Column 5 line 12).
Sakai in the combination further teaches a second condition in which an angle between segments connecting the adjacent feature points is less than a predetermined angle reference value are met (The extraction unit 21 extracts a sequence of feature points (hereinafter simply referred to as a "sequence of points") where an approximation line generated by linear approximation forms a minor angle with the link line that is less than a predetermined angle, based on the position information of the extracted feature points relative to the link line. Page 6 last paragraph); and classify feature points meeting the second condition among the plurality of feature points into a same feature point group (In the present invention, when detecting lane boundary lines of a road by using map information including a link line (K) representing a road, point sequences of feature points (A 1 to A 16, B 1 to B 16, C1 to C16, D1 to D7) of an object indicating the lane boundary lines of a road on which a vehicle is traveling, each of the point sequences (which reads on “a same feature point group”) being where an approximate line generated by linear approximation forms an angle not more than a prescribed angle with respect to the link line (K), are extracted from position information, based on the link line (K), about the feature points (A1 to A16, 81 to 816, C1 to C16, D1 to D7). Abstract).
Regarding claim 4, Sakai in the combination teaches the lane data construction apparatus of claim 3, wherein the processor is further configured to: assign sequence numbers depending on an order of the feature points included in the same feature point group and define a starting point and an end point of the same feature point group depending on the sequence numbers of the feature points (In the example shown in FIG. 4, the extraction unit 21 extracts the sequence of points consisting of feature points A 1 to A 16 if the approximation line generated by linear approximation from the sequence of points consisting of feature points A 1 to A 16 forms a minor angle with the link line K that is less than a predetermined angle. Page 7 2nd paragraph.
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Regarding claim 5, Xie in the combination teaches the lane data construction apparatus of claim 3, wherein the processor is further configured to: apply an outline approximation algorithm for each feature point group to generate each of the polylines (A polynomial fitting is performed on coordinates of the selected plurality of lane line points in the second image, to obtain a polynomial curve of the lane line corresponding to the group. Column 6 line 58).
Regarding claim 6, Sakai in the combination teaches the lane data construction apparatus of claim 1, wherein the processor is further configured to: define each lane depending on a similarity between the polylines (In the example shown in FIG. 4, the extraction unit 21 extracts the sequence of points consisting of feature points A 1 to A 16 if the approximation line generated by linear approximation from the sequence of points consisting of feature points A 1 to A 16 forms a minor angle with the link line K that is less than a predetermined angle. For the sequence of points consisting of feature points B1 to B16, the sequence of points consisting of feature points C1 to C7, the sequence of points consisting of feature points D1 to D7, and the sequence of points consisting of feature points C12 to C16, each of these sequences is also extracted if the approximation line generated from the sequence of points by linear approximation forms a minor angle with the link line K that is less than a predetermined angle. Page 7 2nd paragraph.
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) and assign an instance identification (ID) for each lane to generate the instance segmentation data including the instance ID (Lane W1 is defined by solid line L1 and dashed line L2, and lane W2 is defined by dashed line L2 and solid line L3. Furthermore, lane W2 branches at branch point J into lane W2a, defined by dashed lines L2 and L4, and lane W2b, defined by solid line L3 and dashed line L4. Page 4 last paragraph.
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Method claims 12-16 are drawn to the method of using the corresponding apparatus claimed in claims 2-6. Therefore method claims 12-16 correspond to apparatus claims 2-6 and are rejected for the same reasons of obviousness as used above.
Claims 7-10 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US Patent Pub. No.: US 11,275,955 B2) hereinafter Xie, in view of Sakai (PCT Patent Pub. No.: WO 2026022924 A1), hereinafter Sakai, further in view of Meng (Chinese Patent Pub. No.: CN 111860113 A), hereinafter Meng.
Regarding claim 7, Xie and Sakai teach all of the elements of the claimed invention as stated in claim 6 except for the following limitations as further recited. However, Meng teaches wherein the processor is further configured to: determine whether a third condition in which a distance between adjacent polylines among the polylines is less than a predetermined distance reference value (the upper and lower positions of the two lines are close, and the miny difference of the two lines is smaller than a certain threshold (10 in the embodiment); the two lines have similar attitude positions, that is, the difference between topX and topY of the two lines is smaller than a certain threshold (in the embodiment, the two thresholds are set to 10 collectively). Page 12 last paragraph) and a fourth condition in which an angle between segments connecting starting points and end points of the adjacent polylines among the polylines is less than a predetermined angle reference value (And comparing each line with the rest lines in sequence, and merging the two lines when the following conditions are met: the difference between the two line angles is smaller than a certain threshold (6 degrees in the embodiment. Page 12 last paragraph) are met (Optionally, the aggregating process includes: comparing each line segment of the line segments with the rest line segments in sequence, and merging the two line segments meeting the following conditions; the difference between the angles of the two line segments is smaller than a set angle threshold; the positions of the two line segments are similar; the attitude positions of the two line segments are similar. Page 7 18th paragraph); and classify polylines meeting the third condition and the fourth condition into a same polyline group (aggregating a plurality of line segments belonging to the same straight line. Abstract).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Xie and Sakai to incorporate the teachings of Meng to classify polylines into a same polyline group if a distance between adjacent polylines is less than a predetermined distance reference value and if an angle between segments connecting starting points and end points of the adjacent polylines is less than a predetermined angle reference value in order to reduce calculation complexity, guarantee the real-time performance and achieve lane identification accuracy.
Regarding claim 8, Meng in the combination teaches the lane data construction apparatus of claim 7, wherein the processor is further configured to: recognize the respective polylines included in the same polyline group as a same lane (aggregating a plurality of line segments belonging to the same straight line. Abstract).
Regarding claim 9, Meng in the combination teaches the lane data construction apparatus of claim 6, wherein the processor is further configured to: set a region of interest (ROI) based on a starting point and an end point of each polyline (an ROI area acquisition module: the method comprises the steps of selecting an ROI (region of interest) in an acquired image, wherein the ROI comprises a lane line. Page 3 6th paragraph).
Xie in the combination further teaches assign an instance ID of a lane to which the ROI belongs to a lane pixel in the ROI (For example, as shown in FIG. 4, the region surrounded by the broken lines is the ROI. The lane lines meeting at a distal end are separate in the ROI, in which only lane lines that do not intersect are included. In this way, the connected domain analysis is only performed on the pixel points in the ROI, and the lane lines converging at the distal end are separate in the ROI, which can prevent the pixel points located in different lane lines from being grouped into the same group (in other words, a lane pixel in the ROI is associated with an instance ID of a lane), so that the grouping is more accurate. Column 6 line 19.
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Regarding claim 10, Xie in the combination teaches the lane data construction apparatus of claim 9, wherein the processor is further configured to: set the ROI to a rectangle (For example, as shown in FIG. 4, the region surrounded by the broken lines is the ROI. Column 6 line 19
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); determine vertex coordinates of a top left for the ROI based on a smaller value between an x-coordinate of the starting point of each polyline and an x-coordinate of the end point of each polyline and a minimum margin value between a y-coordinate of the starting point of each polyline and a y-coordinate of the end point of each polyline (For example, as shown in FIG. 5, a curve L1 is obtained by fitting a certain group, wherein the start point coordinate A of L1 is determined using the minimum value of y ( and/or x) in the group, and the end point coordinate B of L1 is determined using the maximum value of y (and/or x). Column 7 line 31.
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); and determine vertex coordinates of a bottom right for the ROI based on a larger value between the x-coordinate of the starting point of each polyline and the x-coordinate of the end point of each polyline and a maximum margin value between the y-coordinate of the starting point of each polyline and the y-coordinate of the end point of each polyline (A curve L2 is obtained by fitting a certain group, wherein the start point coordinate C of L2 is determined using the maximum value of x (the minimum value of y) in the group, and the end point coordinate D of L2 is determined using the minimum value of x (the maximum value of y) in the group. Column 7 line 31.
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Method claims 17-20 are drawn to the method of using the corresponding apparatus claimed in claims 7-10. Therefore method claims 17-20 correspond to apparatus claims 7-10 and are rejected for the same reasons of obviousness as used above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEI ZHAO whose telephone number is (703)756-1922. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, VU LE can be reached at (571)272-7332. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/LEI ZHAO/Examiner, Art Unit 2668
/VU LE/Supervisory Patent Examiner, Art Unit 2668
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