Prosecution Insights
Last updated: August 15, 2026
Application No. 18/670,933

ELECTRONIC DEVICE FOR IDENTIFYING DISTANCE BETWEEN ELECTRONIC DEVICE AND EXTERNAL OBJECT USING NEURAL NETWORK AND METHOD THEREOF

Non-Final OA §103
Filed
May 22, 2024
Priority
May 23, 2023 — RE 10-2023-0066610
Examiner
BALI, VIKKRAM
Art Unit
2663
Tech Center
2600 — Communications
Assignee
THINKWARE Corporation
OA Round
1 (Non-Final)
82%
Grant Probability
Favorable
1-2
OA Rounds
7m
Est. Remaining
93%
With Interview

Examiner Intelligence

Grants 82% — above average
82%
Career Allowance Rate
523 granted / 642 resolved
+19.5% vs TC avg
Moderate +12% lift
Without
With
+11.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
29 currently pending
Career history
675
Total Applications
across all art units

Statute-Specific Performance

§101
17.0%
-23.0% vs TC avg
§103
52.1%
+12.1% vs TC avg
§102
6.4%
-33.6% vs TC avg
§112
18.7%
-21.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 642 resolved cases

Office Action

§103
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 . Election/Restrictions Applicant's election with traverse of species I in the reply filed on 5/15/26 is acknowledged. The traversal is on the ground(s) that species I and II share a common technical relationship directed to coordinate corrections and improvement of distance identification accuracy for rotated objects. This is not found persuasive because species II recites identify first information indicating a combination of a first image and a first area of a visual object within the first image, within the memory; obtain, by rotating first coordinates of first vertices of the first area within the first image according to a preset angle, second coordinates; obtain a second image by segmenting the rotated first image according to the preset angle; and store, within the memory, second information indicating a combination of a second area indicated by the third coordinates and the second image, which are different from the species I. The requirement is still deemed proper and is therefore made FINAL. 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 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 1-9 and 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Ko et al (US Pub. 2022/0114815) in view of King et al (US 12,271,790). With respect to claim 1, Ko discloses An electronic device comprising: a camera; a sensor; and a processor, wherein the processor is configured to (see figure 12, 110, 150 and 190): [obtain an angle rotated about an optical axis of the camera, through the sensor; identify, in an image obtained through the camera, first coordinates with respect to first vertices of an area in which a visual object corresponding to an external object is included; obtain second coordinates by rotating the first coordinates about a middle point of the area, according to the angle]; based on a category of the external object, which is identified by a neural network to which the image is inputted, identify third coordinates having a size corresponding to the category, from the second coordinates; and identify a distance between the electronic device and the external object based on the third coordinates, (see paragraph 0009, wherein …a collision avoidance method of a moving body collision avoidance device includes: acquiring a driving image of the moving body; recognizing an object in the acquired driving image using a neural network model; calculating a relative distance between the moving body and the object based on the recognized object…), as claimed. However, Ko fails to explicitly disclose obtain an angle rotated about an optical axis of the camera, through the sensor; identify, in an image obtained through the camera, first coordinates with respect to first vertices of an area in which a visual object corresponding to an external object is included; obtain second coordinates by rotating the first coordinates about a middle point of the area, according to the angle, as claimed. King teaches obtain an angle rotated about an optical axis of the camera, through the sensor; identify, in an image obtained through the camera, first coordinates with respect to first vertices of an area in which a visual object corresponding to an external object is included; obtain second coordinates by rotating the first coordinates about a middle point of the area, according to the angle, (see figure 8, the input 810 is the image obtained and the 820 is the predicted image or track, also, see col. 16, lines 21-25, wherein …a camera tracker 518 which converts image captured by a camera (e.g. the camera 140…) to points or a surface in a 3D…; col. 19, lines 12-35 for explanation of the input “first coordinates” and predicted parameters “second coordinates” using the center of the input track), as claimed. It would have been obvious to one ordinary skilled in the art at the effective date of invention to combine the two references as they are analogous because they are solving similar problem of vehicle distance from an object using image analysis. Teaching of King to calculate the transformation can be incorporated into the Ko system as suggested in figure 1, numerical 13 and 14 for position state and tracking determination, for suggestion, and modifying the system yields accurately tracking object using the adjusting track data (see King col. 1, lines 6-13), for motivation. With respect to claim 2, combination of Ko and King further discloses wherein the processor is configured to: obtain, based on identifying a roll motion with respect to the optical axis of the camera, the angle corresponding to the roll motion, (see Ko paragraph 0232, wherein …the sensor 2110 may include a posture sensor (e.g., a yaw sensor, a roll sensor, or a pitch sensor), a collision sensor, a wheel sensor…), as claimed. With respect to claim 3, combination of Ko and King further discloses wherein the processor is configured to: identify the third coordinates based on a position of the visual object within the image, (see Ko figure 4, the bounding box “third coordinates” are per the location or position of the object), as claimed. With respect to claim 4, combination of Ko and King further discloses wherein the processor is configured to: identify a bounding box corresponding to a rear side of the external object based on the third coordinates and the category of the external object, (see Ko the figure 4, where the bounding boxes are covering the objects front or the rear side or the external object), as claimed. With respect to claim 5, combination of Ko and King further discloses wherein the processor is configured to: identify a middle point of a bottom periphery of the bounding box, (see Ko figure 4, numerical 45a the middle point), as claimed. With respect to claim 6, combination of Ko and King further discloses wherein the processor is configured to: identify, based on a width of the bounding box corresponding to the rear side of the external object, a distance between the electronic device and the external object, (see Ko paragraph 0085, and equation 1), as claimed. With respect to claim 7, combination of Ko and King further discloses wherein the processor is configured to: form a three-dimensional virtual coordinate system based on the bounding box and an area formed by the third coordinates, (see Ko paragraph 0107, wherein … a moving body-based coordinate system as a 3D view, and (b) of FIG. 9 shows a moving-object-based coordinate system as a top view. In the coordinate system based on the moving body, a current position of the moving body is a reference point O.sub.PM, a movement direction (longitudinal direction) of the moving body is the X axis, and a lateral direction of the moving body is the Y axis), as claimed. With respect to claim 8, combination of Ko and King further discloses wherein the processor is configured to: identify a virtual object corresponding to the visual object in the three-dimensional virtual coordinate system; and identify a distance between the electronic device and the external object based on the virtual object, (see Ko paragraph 0106-018), as claimed. With respect to claim 9, combination of Ko and King further discloses wherein the processor is configured to: identify the visual object based on applying a filter with respect to the image, (see Ko paragraph 0081, wherein …the normalization processing unit 16 may normalize the driving image using a low pass filter. For example, the normalization processing unit 16 may normalize a driving image as shown in FIG. 5(a) into a driving image as shown in FIG. 5(b)…), as claimed. Claims 13-20 are rejected for the same reasons as set forth in the rejections of claims 1-9, because claims 13-20 are claiming subject matter of similar scope as claimed in claims 1-9. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to VIKKRAM BALI whose telephone number is (571)272-7415. The examiner can normally be reached Monday-Friday 7:00AM-3:00PM. 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, Gregory Morse can be reached at 571-272-3838. 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. /VIKKRAM BALI/Primary Examiner, Art Unit 2663
Read full office action

Prosecution Timeline

May 22, 2024
Application Filed
Jul 16, 2026
Non-Final Rejection mailed — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12700058
VIDEO PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM
2y 11m to grant Granted Aug 04, 2026
Patent 12685898
DETERMINATION OF SPIN RATE AND SPIN AXIS OF A BALL IN FLIGHT
2y 8m to grant Granted Jul 21, 2026
Patent 12682612
WEAK SUPERVISED TRAINING DATA FOR IMAGE TAGGING MODELS
3y 2m to grant Granted Jul 14, 2026
Patent 12675899
IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND NON-TRANSITORY STORAGE MEDIUM
2y 11m to grant Granted Jul 07, 2026
Patent 12675887
HIGH THROUGHPUT POINT CLOUD PROCESSING
2y 10m to grant Granted Jul 07, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

1-2
Expected OA Rounds
82%
Grant Probability
93%
With Interview (+11.9%)
2y 10m (~7m remaining)
Median Time to Grant
Low
PTA Risk
Based on 642 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month