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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/03/2025 and 03/13/2026 has/have been considered by the examiner.
Specification
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
The abstract of the disclosure is objected to because it has phrase “means”. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
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 1-9 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.
Regarding claims 1 and 8-9, the claim limitation "where mobile bodies have been detected on the road in the past" renders the claim indefinite because it is unclear whether “mobile bodies” include “the mobile body” or not. The claims recites the term "the past" in the claim limitation. There is insufficient antecedent basis for this limitation in the claim. In addition, the term “past” in claim limitation is a relative term which renders the claim indefinite. The term “past” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For examination purpose, the claim limitation has been interpreted as where the mobile body has been detected on the road as shown in the past information.
Claims 2-7 are also rejected under 35 U.S.C. 112(b) as being dependent upon a rejected 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.
Claim(s) 1-4 and 8-9 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Park et al (US 20060140447 A1), hereinafter Park.
-Regarding claim 1, Park discloses a mobile body tracking apparatus comprising (Abstract; FIGS. 1-9; [0061]): at least one memory storing instructions; and at least one processor configured to execute the instructions to (FIG. 1; [0035]; one or more memory and processor has to be used in order to implement the system shown in Park’s FIGS. 1, 8): detect a mobile body from each of time-series images obtained by capturing images of a road (FIG. 1, video pre-processor 110, optical flow detector 125, vehicle detector 140; FIGS. 8-9; [0006], “designating a vehicle candidate area using a shadow where the vehicle meets a road and detecting the vehicle …”; [0010], “detected in real time”; [0011], “… processes video data input through a camera …”; [0028], “detects a moving target vehicle”); predict a destination area of the mobile body by using past information indicating positions where mobile bodies have been detected on the road in the past (FIG. 1, template matching unit 150, vehicle information unit 160; FIGS. 6, 8-9; [0046]; [0049]: “predicts the position of the target vehicle in the next frame based on vehicle information … on a current image of the moving target vehicle and information on a previous image of the moving target vehicle …”); and track, in a case where the mobile body is detected from a second image in the destination area that is predicted for the mobile body detected from a first image included in the time-series images, the second image being captured at a time later than a time at which the first image has been captured, the mobile body detected from the first image and the mobile body detected from the second image as a same mobile body (FIG. 1, tracking state determining unit 165; FIGS. 8-9; [0053], “determines the accuracy of the tracking by comparing information on the actual position of the target vehicle in the next frame with the predicted information on the target vehicle …”).
-Regarding claim 2, Park discloses the apparatus of claim 1. Park further discloses to predict a position of the mobile body at the time when the second image is captured, and predict an area including the predicted position and the positions where mobile bodies have been detected in the past information as the destination area (FIGS. 1, 5-6, 8-9; [0034]; [0046]; [0049]; [0055], “vehicle candidate area”).
-Regarding claim 3, Park discloses the apparatus of claim 1. Park further discloses wherein in a case where the mobile body detected in the first image is a mobile body that is subsequently tracked from before the time at which the first image has been captured the at least one processor is configured to execute the instructions to calculate a moving speed and a moving direction of the mobile body by using a result of the tracking, and predict a position of the mobile body at the time when the second image is captured by using the calculated moving speed and moving direction (FIGS. 2-4; FIGS. 1, 8-9; [0036]-[0037]; [0049]; [0058]-[0059]).
-Regarding claim 4, Park discloses the apparatus of claim 1. Park further discloses wherein the past information is stored for each type of the mobile body, and the at least one processor is configured to execute the instructions to predict the destination area by using the past information corresponding to the type of the detected mobile body (FIGS. 1, 6, 8-9; [0038]; [0043]-[0044]; [0046]-[0047]).
-Regarding claim 8, Park discloses a mobile body tracking method comprising (Abstract; FIGS. 1-9; [0061]): detecting a mobile body from a first image included time-series images obtained by capturing images of a road (FIG. 1, video pre-processor 110, optical flow detector 125, vehicle detector 140; FIGS. 8-9; [0006], “designating a vehicle candidate area using a shadow where the vehicle meets a road and detecting the vehicle …”; [0010], “detected in real time”; [0011], “… processes video data input through a camera …”; [0028], “detects a moving target vehicle”; [0026], “ … previous image … current image …”; [0043]-[0044]); predicting a destination area of the mobile body detected from the first image by using past information indicating positions where mobile bodies have been detected on the road in the past (FIG. 1, template matching unit 150, vehicle information unit 160; FIGS. 6, 8-9; [0046]; [0049]: “predicts the position of the target vehicle in the next frame based on vehicle information … on a current image of the moving target vehicle and information on a previous image of the moving target vehicle …”); detecting the mobile body from a second image captured at a time later than a time at which the first image has been captured, the second image being included in the time-series images (FIGS. 1, 8-9; [0029]; [0038]; [0046]-[0047]); and tracking, in a case where the mobile body detected from the second image is detected in the destination area that is predicted for the mobile body detected from the first image, the mobile body detected from the first image and the mobile body detected from the second image as a same mobile body (FIG. 1, tracking state determining unit 165; FIGS. 8-9; [0053], “determines the accuracy of the tracking by comparing information on the actual position of the target vehicle in the next frame with the predicted information on the target vehicle …”; [0056]).
-Regarding claim 9, Park discloses non-transitory computer readable medium storing a program for causing a computer to execute processing including (Abstract; FIGS. 1-9; [0061]; one or more memory and processor has to be used in order to implement the system shown in Park’s FIGS. 1, 8): detecting a mobile body from a first image included time-series images obtained by capturing images of a road (FIG. 1, video pre-processor 110, optical flow detector 125, vehicle detector 140; FIGS. 8-9; [0006], “designating a vehicle candidate area using a shadow where the vehicle meets a road and detecting the vehicle …”; [0010], “detected in real time”; [0011], “… processes video data input through a camera …”; [0028], “detects a moving target vehicle”; [0026], “ … previous image … current image …”; [0043]-[0044]); predicting a destination area of the mobile body detected from the first image by using past information indicating positions where mobile bodies have been detected on the road in the past (FIG. 1, template matching unit 150, vehicle information unit 160; FIGS. 6, 8-9; [0046]; [0049]: “predicts the position of the target vehicle in the next frame based on vehicle information … on a current image of the moving target vehicle and information on a previous image of the moving target vehicle …”); detecting the mobile body from a second image captured at a time later than a time at which the first image has been captured, the second image being included in the time-series images (FIGS. 1, 8-9; [0029]; [0038]; [0046]-[0047]); and tracking, in a case where the mobile body detected from the second image is detected in the destination area that is predicted for the mobile body detected from the first image, the mobile body detected from the first image and the mobile body detected from the second image as a same mobile body (FIG. 1, tracking state determining unit 165; FIGS. 8-9; [0053], “determines the accuracy of the tracking by comparing information on the actual position of the target vehicle in the next frame with the predicted information on the target vehicle …”; [0056]).
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.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park et al (US 20060140447 A1), hereinafter Park in view of Chen et al (US 20230126957 A1), hereinafter Chen.
-Regarding claim 5, Park discloses the apparatus of claim 1.
Park does not disclose wherein the time-series images include a plurality of images obtained by capturing images of an intersection including the road in a time series. However, Park has no limitation on the images captured with or without an intersection including the road. In addition, it is not clear how does an intersection in the images have any impact on the tracking and limit the claim. Thus, the claim limitation is not an inventive concept.
In the same field of endeavor, Chen teaches a method for a moving vehicle trajectory determination by tracking the vehicle based on captured image frames(Chen: FIGS. 3, 6; [0051]-[0052]). Chen further teaches wherein the time-series images include a plurality of images obtained by capturing images of an intersection including the road (Chen: FIG. 4).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Park with the teaching of Chen by using images of an intersection including the road in order to perform accurate tracking in different road environment.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park et al (US 20060140447 A1), hereinafter Park in view of Hong et al (US 20200110416 A1), hereinafter Hong.
-Regarding claim 6, Park teaches the apparatus of claim 1.
Park does not disclose wherein the time-series images include a plurality of images obtained by capturing images of an intersection including the road in a time series. Park does not disclose to acquire a lighting state of a traffic signal installed in the intersection and predict the destination area based on the acquired lighting state.
In the same field of endeavor, Hong teaches a method for determining predicted trajectories based on a top-down representation of an environment (Hong: Abstract; FIGS. 1-6). Hong further teaches wherein the time-series images include a plurality of images obtained by capturing images of an intersection including the road in a time series (Hong: FIG. 1, images 118, 120, 122; [0026]). Hong teaches to acquire a lighting state of a traffic signal installed in the intersection and predict the destination area based on the acquired lighting state (Hong: FIG. 4; [0009],”traffic light state”; [0012]; “the image to be input into the prediction system can be represented by … intersections, traffic lights, … traffic light status … to generate at least one predicted trajectory”; [0101])
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Park with the teaching of Hong by using images of an intersection including the road and traffic light in order to perform accurate tracking in different road environment.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park et al (US 20060140447 A1), hereinafter Park in view of Higashikubo et al (JP 2011118450 A), hereinafter Higashikubo.
-Regarding claim 7, Park discloses the apparatus of claim 1. Park further discloses to extract a feature value of the detected mobile body from the time-series images (FIG. 5; [0041], “extracting an optical flow for a target vehicle”); match the feature value of the mobile body detected in the first image and the feature value of the mobile body detected in the second image (FIGS. 1, 8-9; [0042]); and track the mobile body detected from the first image and the mobile body detected from the second image as a same mobile body in a case where template matching is performed on the vehicle candidate area for vehicle detection and a detected vehicle can be tracked by continuously comparing the detected optical flow and the background optical flow (Abstract; FIGS. 1, 8-9; [0025]; [0049]).
Park does not disclose matching optical flow based on a threshold. However, a person of ordinary skills in the art would understand that it is a common practice to perform similarity analysis of features based on a pre-determined threshold for a target tracking.
In the same field of endeavor, Higashikubo also teaches to extract a feature value of a detected mobile body from the time-series images (page 6, last paragraph – page 7, 2nd paragraph; page 7, last paragraph – page 8, 1st paragraph); calculate a degree of similarity between the feature value of the mobile body detected in the first image and the feature value of the mobile body detected in the second image (FIG. 8; Page 12, 4th – 5th paragraphs, “After acquiring the pair feature of the vehicle to be tracked from the
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captured by the camera 3, the vehicle tracking device 1 determines the destination of the tracking target in the
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captured by the camera 3 …”; page 12, last paragraph – page 13, 1st paragraph; equations (1) –(6)); Higashikubo further teaches to track the mobile body detected from the first image and the mobile body detected from the second image as a same mobile body in a case where the calculated degree of similarity is equal to or greater than a predetermined value (FIGS. 8-9; page 12, last paragraph – page 13, 1st paragraph; page 11, section [12]; page 17, 1st paragraph, “above the threshold”; page 23, 3rd paragraph).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Park with the teaching of Higashikubo by determining the similarity or matching based on a pre-determined threshold in order to achieve desired accuracy of tracking.
Conclusion
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/XIAO LIU/Primary Examiner, Art Unit 2664
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