Prosecution Insights
Last updated: April 19, 2026
Application No. 18/730,846

DEVICE, METHOD AND PROGRAM FOR DETECTING TARGET EQUIPMENT

Non-Final OA §103§112
Filed
Jul 22, 2024
Examiner
SINHA, SNIGDHA
Art Unit
2619
Tech Center
2600 — Communications
Assignee
NTT, Inc.
OA Round
1 (Non-Final)
50%
Grant Probability
Moderate
1-2
OA Rounds
2y 6m
To Grant
96%
With Interview

Examiner Intelligence

Grants 50% of resolved cases
50%
Career Allow Rate
3 granted / 6 resolved
-12.0% vs TC avg
Strong +46% interview lift
Without
With
+45.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
26 currently pending
Career history
32
Total Applications
across all art units

Statute-Specific Performance

§101
2.0%
-38.0% vs TC avg
§103
65.6%
+25.6% vs TC avg
§102
16.2%
-23.8% vs TC avg
§112
11.7%
-28.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 6 resolved cases

Office Action

§103 §112
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 Any inquiry concerning this communication or earlier communications from the examiner should be directed to SNIGDHA SINHA whose telephone number is (571)272-6618. The examiner can normally be reached Mon-Fri. 12pm-8pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason Chan can be reached at 571-272-3022. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /SNIGDHA SINHA/Examiner, Art Unit 2619 /JASON CHAN/Supervisory Patent Examiner, Art Unit 2619
Read full office action

Prosecution Timeline

Jul 22, 2024
Application Filed
Feb 19, 2026
Non-Final Rejection — §103, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12567216
AUGMENTED-REALITY-INTERFACE CONFLATION IDENTIFICATION
2y 5m to grant Granted Mar 03, 2026
Patent 12406339
MACHINE LEARNING DATA AUGMENTATION USING DIFFUSION-BASED GENERATIVE MODELS
2y 5m to grant Granted Sep 02, 2025
Study what changed to get past this examiner. Based on 2 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
50%
Grant Probability
96%
With Interview (+45.8%)
2y 6m
Median Time to Grant
Low
PTA Risk
Based on 6 resolved cases by this examiner. Grant probability derived from career allow rate.

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