CTNF 18/652,122 CTNF 99213 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Specification 06-11 AIA The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-12-aia AIA (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. 07-15-aia AIA Claim(s) 1-7, 9-10, 12-19 is/are rejected under 35 U.S.C. 102 (a) as being taught by Yun et al. (U.S. Patent Publication No. 2023/0410489 -A1, hereinafter “Yun”) . Regarding claim 1 , Yun teaches: An object recognition apparatus, the apparatus comprising: a LIDAR; a camera; a radar; one or more processors; and a storage device storing a program to be executed by the one or more processors, the program including instructions for: (Fig. 1; [0090], " For example, in order to generate and update the sensor fusion track, the processor 250 may be configured to utilize data illustrated in FIG. 4, that is, sensor fusion track data 41, front-side LiDAR data 43 received from the front-side LiDAR 21, surrounding vehicle detection data 45 acquired using the surround view monitoring camera, and/or rear side view camera data 47 received from the rear side view camera 27. ") identifying at least one fusion track corresponding to at least one external object acquired through the camera and the radar; ([0090], " For example, in order to generate and update the sensor fusion track, the processor 250 may be configured to utilize data illustrated in FIG. 4, that is, sensor fusion track data 41, front-side LiDAR data 43 received from the front-side LiDAR 21, surrounding vehicle detection data 45 acquired using the surround view monitoring camera, and/or rear side view camera data 47 received from the rear side view camera 27. ") identifying a target fusion track among the at least one fusion track based on a category into which the at least one fusion track is classified, a longitudinal component of a distance from a point corresponding to a host vehicle to the at least one fusion track, or any combination thereof; ([0090], " For example, in order to generate and update the sensor fusion track, the processor 250 may be configured to utilize data illustrated in FIG. 4, that is, sensor fusion track data 41, front-side LiDAR data 43 received from the front-side LiDAR 21, surrounding vehicle detection data 45 acquired using the surround view monitoring camera, and/or rear side view camera data 47 received from the rear side view camera 27. "; Examiner's Note - The claim language could apply to any track fusion track based on the fact that a single fusion track would by its nature be chosen for being a fusion track. Longitudinal component is also optional due to claim language making it part of an incomplete enumeration of classifications that the fusion track could be classified under.) identifying at least one LIDAR track corresponding to an external object represented by the target fusion track among the at least one external object acquired through the LIDAR; ([0118], " For example, the sensor fusion system 200 may be configured to detect the target vehicle located around the vehicle 2 based on sensor data of the sensing device 20 and predict a plurality of sensor tracks of the detected target vehicle. In addition, the sensor fusion system 200 may be configured to identify whether the sensor tracks are the same object by varying weights using an overlapping range and distances between the plurality of predicted sensor tracks, and fuse the sensor tracks identified as the same object to generate a sensor fusion track. ") identifying at least one target LIDAR track among the at least one LIDAR track based on a distance to the at least one LIDAR track from a half line from the point corresponding to the host vehicle to a point corresponding to the target fusion track, wherein the point corresponding to the target fusion track represents a point corresponding to a camera track identified through the camera, represents the at least one external object, and identifies the target fusion track; ([0118], " For example, the sensor fusion system 200 may be configured to detect the target vehicle located around the vehicle 2 based on sensor data of the sensing device 20 and predict a plurality of sensor tracks of the detected target vehicle. In addition, the sensor fusion system 200 may be configured to identify whether the sensor tracks are the same object by varying weights using an overlapping range and distances between the plurality of predicted sensor tracks, and fuse the sensor tracks identified as the same object to generate a sensor fusion track. "; Examiner's Note - Half line maps to anything and unclear how the selection would occur based on the proximity to half line.) identifying second LIDAR points that satisfy a position condition determined based on a difference in position between the point corresponding to the target fusion track and a first LIDAR point, a position of the radar, and a position of the camera, or an angle condition identified based on the half line, or any combination thereof, among first LIDAR points of the at least one target LIDAR track; identifying at least one third LIDAR point that satisfies a distance condition identified based on a distance from the point corresponding to the host vehicle to the second LIDAR point, among the second LIDAR points; ([0139], " The sensor fusion system 200 may be configured to determine a second coordinate value of a corner corresponding to the first corner among the corners of each of the target vehicle 3 and 4 based on the two-dimensional equation and the first coordinate value P1, and calculate a third coordinate value P3 corresponding to a location of a midpoint of a rear bumper of each of the target vehicles 3 and 4, thereby updating the location information of the existing sensor fusion track. "; Examiner's Note - Any combination thereof makes all of the conditions listed as potentially optional besides one. A position of the radar also is broad enough to always be true based on the existence of a radar in a position.) and associating and storing the target fusion track and the at least one third LIDAR point based on identifying the at least one third LIDAR point. ([0139], " The sensor fusion system 200 may be configured to determine a second coordinate value of a corner corresponding to the first corner among the corners of each of the target vehicle 3 and 4 based on the two-dimensional equation and the first coordinate value P1, and calculate a third coordinate value P3 corresponding to a location of a midpoint of a rear bumper of each of the target vehicles 3 and 4, thereby updating the location information of the existing sensor fusion track. "; Examiner's Note - The third point comes from the fusion track so it would be associated and stored.) Regarding claim 2 , Yun teaches: The apparatus of claim 1, wherein the program further includes instructions for identifying the target fusion track among the at least one fusion track based on the at least one fusion track being identified via the camera and the radar, the at least one fusion track being classified into a specified category, and identifying that the longitudinal component is less than a specified distance. ([0090], " For example, in order to generate and update the sensor fusion track, the processor 250 may be configured to utilize data illustrated in FIG. 4, that is, sensor fusion track data 41, front-side LiDAR data 43 received from the front-side LiDAR 21, surrounding vehicle detection data 45 acquired using the surround view monitoring camera, and/or rear side view camera data 47 received from the rear side view camera 27. "; Examiner's Note - The claim language make longitude component no longer optional, but the specified distance is still unclear, maps to just a potential systems or physical limitation as well as an artificial limitation.) Regarding claim 3 , Yun teaches: The apparatus of claim 1, wherein the program further includes instructions for identifying the at least one target LIDAR track among the at least one LIDAR track, based on the half line passing through a track box representing at least one LIDAR track identified through the LIDAR or based on identifying that at least one of vertical distances from the half line to four vertices of the track box is less than or equal to a specified distance. ([0118], " For example, the sensor fusion system 200 may be configured to detect the target vehicle located around the vehicle 2 based on sensor data of the sensing device 20 and predict a plurality of sensor tracks of the detected target vehicle. In addition, the sensor fusion system 200 may be configured to identify whether the sensor tracks are the same object by varying weights using an overlapping range and distances between the plurality of predicted sensor tracks, and fuse the sensor tracks identified as the same object to generate a sensor fusion track. "; Examiner's Note - Half line maps to anything and unclear how the selection would occur based on the proximity to half line.) Regarding claim 4 , Yun teaches: The apparatus of claim 1, wherein the position condition comprises: a first condition that a first value satisfies a first specified range, the first value being identified based on a difference between a longitudinal position of the radar and a longitudinal position of the first LIDAR point, and a difference between a lateral position of the camera and a lateral position of the first LIDAR point; and a second condition that a second value satisfies a second specified range different from the first specified range, the second value being identified based on a difference between a position of a center point of one of four line segments of a track box representing the target fusion track and a position of the first LIDAR point. (Examiner's Note - This extrapolates on an optional enumerated condition) Regarding claim 5 , Yun teaches: The apparatus of claim 1, wherein the angle condition comprises a condition that, in a state in which the first LIDAR points are arranged in a decreasing order of angles between each of half lines from the point corresponding to the host vehicle to the first LIDAR points and the half line, a LIDAR point is included within a specified order, among the first LIDAR points. (Examiner's Note - This extrapolates on an optional enumerated condition) Regarding claim 6 , Yun teaches: The apparatus of claim 1, wherein the distance condition comprises a condition that a LIDAR point is closest to the point corresponding to the host vehicle, among the second LIDAR points. (Examiner's Note - This extrapolates on an optional enumerated condition) Regarding claim 7 , Yun teaches: The apparatus of claim 1, wherein the distance condition comprises a first condition that the at least one third LIDAR point corresponds to a smallest angle among angles between each of half lines from the point corresponding to the host vehicle to the second LIDAR points and the half line among the second LIDAR points, or a second condition that the at least one third LIDAR point is closest to the target fusion track among the second LIDAR points. (Examiner's Note - This extrapolates on an optional enumerated condition) Regarding claim 8 , Yun teaches: The apparatus of claim 1, wherein: the point corresponding to the host vehicle comprises a center point of a line segment representing a front bumper module of the host vehicle; and the point corresponding to the target fusion track comprises a center point of a track box representing the camera track. ([0139], " The sensor fusion system 200 may be configured to determine a second coordinate value of a corner corresponding to the first corner among the corners of each of the target vehicle 3 and 4 based on the two-dimensional equation and the first coordinate value P1, and calculate a third coordinate value P3 corresponding to a location of a midpoint of a rear bumper of each of the target vehicles 3 and 4, thereby updating the location information of the existing sensor fusion track. ") Regarding claim 9 , Yun teaches: The apparatus of claim 1, wherein the program further includes instructions for identifying a point corresponding to the target fusion track through the camera. ([0139], " The sensor fusion system 200 may be configured to determine a second coordinate value of a corner corresponding to the first corner among the corners of each of the target vehicle 3 and 4 based on the two-dimensional equation and the first coordinate value P1, and calculate a third coordinate value P3 corresponding to a location of a midpoint of a rear bumper of each of the target vehicles 3 and 4, thereby updating the location information of the existing sensor fusion track. ") Regarding claim 10 , Yun teaches: The apparatus of claim 1, wherein the program further includes instructions for identifying a category into which the at least one fusion track is classified, based on a portion of an image acquired through the camera. ([0139], " The sensor fusion system 200 may be configured to determine a second coordinate value of a corner corresponding to the first corner among the corners of each of the target vehicle 3 and 4 based on the two-dimensional equation and the first coordinate value P1, and calculate a third coordinate value P3 corresponding to a location of a midpoint of a rear bumper of each of the target vehicles 3 and 4, thereby updating the location information of the existing sensor fusion track. ") Regarding claim 11 , Yun teaches: The apparatus of claim 1, wherein: a category into which the at least one fusion track is classified represents a pedestrian; the target fusion track has the longitudinal component of the distance from the point corresponding to the host vehicle to the at least one fusion track which is less than a specified distance, among the at least one fusion track identified as the pedestrian through the camera; the at least one target LIDAR track comprises at least one candidate track capable of corresponding to the pedestrian represented by the target fusion track; and the at least one third LIDAR point comprises a LIDAR point corresponding to the pedestrian represented by the target fusion track. ([0095], “ The first tracking unit 253 (also referred to as a track prediction unit) may be configured to predict a sensor track of each object located around the vehicle 2. The sensor track may have a box shape fit to the periphery of the object, and the object may comprise the target vehicle located around the vehicle. ”; [0139], " The sensor fusion system 200 may be configured to determine a second coordinate value of a corner corresponding to the first corner among the corners of each of the target vehicle 3 and 4 based on the two-dimensional equation and the first coordinate value P1, and calculate a third coordinate value P3 corresponding to a location of a midpoint of a rear bumper of each of the target vehicles 3 and 4, thereby updating the location information of the existing sensor fusion track. ") Regarding claim 12 , Yun teaches: The apparatus of claim 1, wherein the program further includes instructions for associating and storing the target fusion track and the at least one third LIDAR point by changing the point of the target fusion track to the point of the at least one third LIDAR point, based on identifying the at least one third LIDAR point. ([0139], " The sensor fusion system 200 may be configured to determine a second coordinate value of a corner corresponding to the first corner among the corners of each of the target vehicle 3 and 4 based on the two-dimensional equation and the first coordinate value P1, and calculate a third coordinate value P3 corresponding to a location of a midpoint of a rear bumper of each of the target vehicles 3 and 4, thereby updating the location information of the existing sensor fusion track. ") Regarding claim 13 , claim 13 has been analyzed with regard to claim 1 and is rejected for the same reasons of obviousness as used above. Regarding claim 14 , claim 14 has been analyzed with regard to claim 2 and is rejected for the same reasons of obviousness as used above. Regarding claim 15 , claim 15 has been analyzed with regard to claim 3 and is rejected for the same reasons of obviousness as used above. Regarding claim 16 , claim 16 has been analyzed with regard to claim 4 and is rejected for the same reasons of obviousness as used above. Regarding claim 17 , claim 17 has been analyzed with regard to claim 5 and is rejected for the same reasons of obviousness as used above. Regarding claim 18 , claim 18 has been analyzed with regard to claim 6 and is rejected for the same reasons of obviousness as used above. Regarding claim 19 , claim 19 has been analyzed with regard to claim 7 and is rejected for the same reasons of obviousness as used above. Regarding claim 20 , claim 20 has been analyzed with regard to claim 8 and is 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 Jinsu Hwang whose telephone number is (703)756-1370. The examiner can normally be reached Mon 6am-8am, 3pm-9pm EST; Thu 12pm - 8pm EST. 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, Matthew Bella can be reached at (571) 272-7778. 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. /JINSU HWANG/Examiner, Art Unit 2667 /MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667 Application/Control Number: 18/652,122 Page 2 Art Unit: 2667 Application/Control Number: 18/652,122 Page 3 Art Unit: 2667 Application/Control Number: 18/652,122 Page 4 Art Unit: 2667 Application/Control Number: 18/652,122 Page 5 Art Unit: 2667 Application/Control Number: 18/652,122 Page 6 Art Unit: 2667 Application/Control Number: 18/652,122 Page 7 Art Unit: 2667 Application/Control Number: 18/652,122 Page 8 Art Unit: 2667 Application/Control Number: 18/652,122 Page 9 Art Unit: 2667 Application/Control Number: 18/652,122 Page 10 Art Unit: 2667 Application/Control Number: 18/652,122 Page 11 Art Unit: 2667
Prosecution Insights