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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 22 July 2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-7 and 9 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "extracting point clouds of structures from point clouds" in the first limitation of the claim. It is unclear how point clouds are extracted from other point clouds. Claims 7 and 9 are rejected for similar reasons. Claims 2-6 are rejected because they are dependent on claim 1.
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 1-3, 6-7 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Zhan (US 20190206063) in view of Sakurahara (US 20250014271).
Regarding claim 1, Zhan teaches a device comprising one or more processors configured to execute instructions that cause the device to perform operations comprising:
Detecting a target facility from the structures using reflection intensities of the extracted point clouds of the structures (Paragraph 48, reflection intensity refers to the degree of reflection of the surface of the object to the laser emitted by the acquisition device 110. For example, the metal surface of vehicle 120 may reflect a significant portion of the laser (as indicated by the arrow 610B) upon receipt of the laser from the acquisition device; Paragraph 32, The first frame 320 and the second frame 330 may be acquired from the point cloud data 310. Then, a first candidate object 322 and a second candidate object 332 corresponding to the first candidate object 322 may be extracted from the first frame 320 and the second frame 330, respectively).
While Zhan fails to disclose the following, Sakurahara teaches:
Extracting point clouds of structures from point clouds by clustering a point cloud in which each point represents three-dimensional coordinates (Paragraph 82, a cable model is created by extracting a cluster that is linearly approximated as a cable possibility cluster from clusters generated from a three-dimensional point cloud).
Sakurahara and Zhan are both considered to be analogous to the claimed invention because they are in the same field of point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhan by using Sakurahara and extract point clouds of structures using clustering. Doing so would allow for using a known way of segmenting point clouds to determine existing objects.
Method claim 7 and CRM claim 9 correspond to apparatus claim 1. Therefore, claims 7 and 9 are rejected for the same reasons as used above.
Regarding claim 2, the combination of Zhan and Sakurahara teaches the device according to claim 1, wherein the target facility is detected from the structures by determining an artificial structure on the basis of the reflection intensities of the extracted point clouds of the structures (Zhan, Paragraph 48, the metal surface of vehicle 120 may reflect a significant portion of the laser).
Regarding claim 3, the combination of Zhan and Sakurahara teaches the device according to claim 2, wherein the operations further comprise:
Comparing the reflection intensities of the extracted point clouds of the structures between point clouds disposed on the same scan line (Zhan, Paragraph 48, degree of reflection of the surface of the object to the laser emitted… Since generally there are many gaps between the leaves of the tree 140, the reflection intensity is much lower than the reflection intensity of the vehicle 120).
In a case in which reflection intensities of the point clouds disposed on the same scan line have a predetermined rule, determining the point clouds to be an artificial structure (Zhan, Paragraph 48, degree of reflection of the surface of the object to the laser emitted… Since generally there are many gaps between the leaves of the tree 140, the reflection intensity is much lower than the reflection intensity of the vehicle 120).
Regarding claim 6, the combination of Zhan and Sakurahara teaches the device according to claim 1, wherein a three-dimensional model of the target facility is created using a point cloud of a structure corresponding to the target facility when the target facility is detected (Zhan, Paragraph 3, For stationary objects such as buildings, roads, and trees, it is now possible to construct a corresponding three-dimensional model based on the acquired point cloud data).
Claims 1-3, 6-7 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Zhan (US 20190206063) in view of Yoshizawa (US 20230306833).
Regarding claim 1, Zhan teaches a device comprising one or more processors configured to execute instructions that cause the device to perform operations comprising:
Detecting a target facility from the structures using reflection intensities of the extracted point clouds of the structures (Paragraph 48, reflection intensity refers to the degree of reflection of the surface of the object to the laser emitted by the acquisition device 110. For example, the metal surface of vehicle 120 may reflect a significant portion of the laser (as indicated by the arrow 610B) upon receipt of the laser from the acquisition device; Paragraph 32, The first frame 320 and the second frame 330 may be acquired from the point cloud data 310. Then, a first candidate object 322 and a second candidate object 332 corresponding to the first candidate object 322 may be extracted from the first frame 320 and the second frame 330, respectively).
While Zhan fails to disclose the following, Yoshizawa teaches:
Extracting point clouds of structures from point clouds by clustering a point cloud in which each point represents three-dimensional coordinates (Paragraph 203, the clustering processing unit 16b of the moving body recognition analysis unit 16 of the safety monitoring device 10 extracts a cluster of point cloud data (moving bodies) from the foreground data on the basis of the distance data of the point cloud sensed using the three-dimensional data, and performs the clustering processing).
Yoshizawa and Zhan are both considered to be analogous to the claimed invention because they are in the same field of point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhan by using Yoshizawa and extract point clouds of structures using clustering. Doing so would allow for using a known way of segmenting point clouds to determine existing objects.
Method claim 7 and CRM claim 9 correspond to apparatus claim 1. Therefore, claims 7 and 9 are rejected for the same reasons as used above.
Regarding claim 2, the combination of Zhan and Yoshizawa teaches the device according to claim 1, wherein the target facility is detected from the structures by determining an artificial structure on the basis of the reflection intensities of the extracted point clouds of the structures (Zhan, Paragraph 48, the metal surface of vehicle 120 may reflect a significant portion of the laser).
Regarding claim 3, the combination of Zhan and Yoshizawa teaches the device according to claim 2, wherein the operations further comprise:
Comparing the reflection intensities of the extracted point clouds of the structures between point clouds disposed on the same scan line (Zhan, Paragraph 48, degree of reflection of the surface of the object to the laser emitted… Since generally there are many gaps between the leaves of the tree 140, the reflection intensity is much lower than the reflection intensity of the vehicle 120).
In a case in which reflection intensities of the point clouds disposed on the same scan line have a predetermined rule, determining the point clouds to be an artificial structure (Zhan, Paragraph 48, degree of reflection of the surface of the object to the laser emitted… Since generally there are many gaps between the leaves of the tree 140, the reflection intensity is much lower than the reflection intensity of the vehicle 120).
Regarding claim 6, the combination of Zhan and Yoshizawa teaches the device according to claim 1, wherein a three-dimensional model of the target facility is created using a point cloud of a structure corresponding to the target facility when the target facility is detected (Zhan, Paragraph 3, For stationary objects such as buildings, roads, and trees, it is now possible to construct a corresponding three-dimensional model based on the acquired point cloud data).
Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Zhan in view of Yoshizawa as applied to claims 1-3, 6-7 and 9 above and further in view of Li (CN 112740269).
Regarding claim 4, the combination of Zhan and Yoshizawa teaches the method of claim 3. While the combination fails to disclose the following, Li teaches:
For each point included in a scan line, calculating a difference or a ratio of reflection intensity between adjacent points (Page 22, Paragraph 5, three-dimensional point with difference value of the surrounding three-dimensional point reflection intensity greater than the preset threshold value or three-dimensional point with reflection intensity greater than the preset threshold value)
In case in which a difference or a ratio of reflection intensity between adjacent points on the same scan line is within a certain value, determining the scan line to be an artificial structure (Page 20, Paragraph 4, if the intersection of the two and the ratio of the parallel set is small (such as less than the preset threshold 0.4), it indicates that the second 2 D detection frame and the first 2 D detection frame described are the same object).
Li and the combination of Zhan and Yoshizawa are both considered to be analogous to the claimed invention because they are in the same field of point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Zhan and Yoshizawa by using Li and determining a difference or ratio between adjacent point clouds. Doing so would allow for using a known way of using point cloud values to determine the presence of an object.
Regarding claim 5, the combination of Zhan and Yoshizawa teaches the device according to claim 5. While the combination fails to disclose the following, Li teaches:
Wherein the same scan line is a scan line including a simultaneously measured point cloud (Page 14, Paragraph 3, the target detection device 100 can call the laser sensor 1061 at the second time, obtaining the three-dimensional point cloud of the target scene. wherein, the first time and the second time can be the same or different).
Li and the combination of Zhan and Yoshizawa are both considered to be analogous to the claimed invention because they are in the same field of point clouds. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Zhan and Yoshizawa by using Li and use simultaneously measured point clouds for the same scan line. Doing so would allow for ensuring point value accuracy by measuring two point values at the same time.
Conclusion
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/SNIGDHA SINHA/Examiner, Art Unit 2619
/JASON CHAN/Supervisory Patent Examiner, Art Unit 2619