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 09/03/2024 is being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: a feature amount corrector, dynamic background generator, a background feature amount vector calculator, a complementary space projection matrix calculator, and a projection vector calculator in claim 1, a correlator in claim 2, a predictor and a predicted feature amount corrector in claim 3, and a flow rate estimator in claim 8.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
The term “partially” in claim 1 is a relative term which renders the claim indefinite. The term “partially” 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. Examiner is unsure of the meets and bounds of the word partially. If the applicant is meant to teach partially as only using a scene prior to the subject being introduced in that scene/frame, the applicant is encouraged to amend the claim language to reflect that.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Boult (US 11288820 B2), and further in view of Arbabian (US 20220026557 A1).
Regarding claim 1, Boult discloses A target tracker that tracks a plurality of targets by a bounding box, the target tracker comprising ("abstract: The transformations can also be used to produce labeled data for training machine learning models: bounding-boxes provided in sweep image can be transformed to bound boxes in video, and boxes in video can be transformed into boxes in the sweep image.
col 14, lines 26-30: With the front edge detected and tracked 830 and trailing edge 832 identified the object in the frame can be converted to a template 850 and tracked in the video, ideally both forward and backwards in time."):
a feature amount corrector including a dynamic background generator, a background feature amount vector calculator, a complementary space projection matrix calculator, and a projection vector calculator, wherein (col 9, lines 24-28: In both cases, the thresholds or background can be adjusted accordingly to maintain a desired range of pixels above the low threshold but below the high threshold which can maintain sensitivity under dynamic conditions.)
the dynamic background generator generates a moving image of a background by partially adding a background image of a place where the targets are not shown in a past image to the moving image in a region of the bounding box in which movement of the targets is shown (col 7, lines 1-5: For the same reasons that video-based systems need to adapt their background, it may be better for the background column to be dynamic rather than static. In addition, especially in outdoor scenes, the lighting changes can be too fast for unchanging background columns to work effectively.
fig. 8: object is not detected until it passes line 820.). Boult does not explicitly disclose the background feature amount vector calculator calculates a background feature amount vector by referring to an image of the background,
the complementary space projection matrix calculator calculates a projection matrix of the background feature amount vector to a complementary space, and
the projection vector calculator multiplies a feature amount vector of the target by the projection matrix.
In a similar field of endeavor of background subtraction, Arbabian teaches the background feature amount vector calculator calculates a background feature amount vector by referring to an image of the background ([0121] The feature extraction module 1920 extracts features from the filtered latest CVD-based background estimate 1916, to produce latest running CVD-based background features 1922.),
the complementary space projection matrix calculator calculates a projection matrix of the background feature amount vector to a complementary space ([0089] In response to no match, the process ends. In response to a match, operation 1210 determines whether either the radar target or the image ROI is mapped to a location in a background estimation (either radar-based background 1242 or the CVD-based background estimation 1244). In response to a determination that mapping is to a location in a background estimation, at operation 1212, radar subtracts the background target.), and
the projection vector calculator multiplies a feature amount vector of the target by the projection matrix ([0148] As illustrated at the bottom of FIG. 24, the input is a vector x. The input is passed through multiple layers 2406, where weights W.sub.1, W.sub.2, . . . , W.sub.i are applied to the input to each layer to arrive at f.sup.1(x), f.sup.2(x), . . . , f.sup.−1(x), until finally the output f(x) is computed.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of object tracking, as disclosed by Boult, with known technique of technique of background subtraction, as taught by Arbabian, in order to yield the predictable results of saving computing power by isolating moving objects from a scene in order to maintain adaptability.
Regarding claim 2, Boult does not explicitly disclose but Arbabian teaches a correlator, wherein the correlator solves an assignment problem of an existing locus and an observation value for the target ([0058] In the example first spatial sensor system 100, a background mask indicates location in the radar scene 103 of a background object that behaves as a radar clutter source. An example background mask is used to suppress target detection at the indicated location of the clutter source.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of object tracking, as disclosed by Boult, with known technique of technique of background subtraction, as taught by Arbabian, in order to yield the predictable results of saving computing power by isolating moving objects from a scene in order to maintain adaptability.
Claim(s) 3-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Boult (US 11288820 B2), in view of Arbabian (US 20220026557 A1) and further in view of Liu (US 20190103026 A1).
Regarding claim 3, Boult discloses the predictor calculates a predicted value of a feature amount of the target at a current time that has not been determined yet by referring to only a feature amount of the target at a past time (col 14, lines 21-30: In addition the ground truth box in the sweep images continues to produce intersections 871 with the line 820 in other frames 801 expanding the back edge of the object 831 and providing an estimate of its vertical location in that frame. The final trailing edge of the ground truth box in the sweep image predicts 872, the trailing edge 832 of the object crossing line 820. With the front edge detected and tracked 830 and trailing edge 832 identified the object in the frame can be converted to a template 850 and tracked in the video, ideally both forward and backwards in time.).
Boult does not explicitly disclose but Arbabian teaches the predicted feature amount corrector corrects the predicted value by referring to a ([0142] Machine learning techniques train models to accurately make predictions on data fed into the models (e.g., what was said by a user in a given utterance; whether a noun is a person, place, or thing; what the weather will be like tomorrow). During a learning phase, the models are developed against a training dataset of inputs to optimize the models to correctly predict the output for a given input. Generally, the learning phase may be supervised, semi-supervised, or unsupervised, indicating a decreasing level to which the “correct” outputs are provided in correspondence to the training inputs.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of object tracking, as disclosed by Boult, with known technique of technique of background subtraction, as taught by Arbabian, in order to yield the predictable results of saving computing power by isolating moving objects from a scene in order to maintain adaptability. Boult and Arbabian do not explicitly disclose a vanishing point position.
In a similar field of endeavor of collision avoidance system, Liu teaches a vanishing point position ([0027] The collision warning system 100 may detect the lane markers or other objects such as buildings for vanishing point determination using image processing or object detection algorithms known to one skilled in the art.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of Boult and Arbabian’s disclosure of object tracking using background subtraction, with the known technique of vanish point detection, as taught by Liu, in order to yield the predictable results of accurately improve safety, path planning, and distance judgment of a scene using the cameras of an autonomous vehicle.
Regarding claim 4, Boult implicitly discloses the predicted feature amount corrector determines a size of the bounding box at the current time by referring to a geometric positional relationship between the vanishing point position and a position of the bounding box (fig. 8 (a bounding box is around the object when it passes through a vanishing line)).
Boult and Arbabian do not explicitly disclose but Liu teaches the predicted feature amount corrector determines a size of the bounding box at the current time by referring to a geometric positional relationship between the vanishing point position and a position of the bounding box ([0044] The tracker 330 may predict how the bounding box 630 may change as the detected object moves closer toward a provider's vehicle 140, e.g., based on changes in a vertical direction of the image frames. For instance, a first bounding box tracking a first vehicle in a different lane on the road will have greater change in the vertical direction than a second bounding box tracking a second vehicle in a same lane as the provider's vehicle 140.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of Boult and Arbabian’s disclosure of object tracking using background subtraction, with the known technique of vanish point detection, as taught by Liu, in order to yield the predictable results of accurately improve safety, path planning, and distance judgment of a scene using the cameras of an autonomous vehicle.
Regarding claim 5, Boult and Arbabian do not disclose but Liu teaches the predicted feature amount corrector predicts a three-dimensional position of the bounding box at the current time by referring to a difference between three-dimensional positions of the bounding box at two different past times ("[0035] As shown in FIG. 4A, the attention-processing engine 300 may determine a tilt angle or a pan angle of the client device 110 relative to a 3D x-y-z coordinate system of the client device 110.
[0044] FIGS. 6B-C show diagrams illustrating bounding boxes for tracking objects according to various embodiments. To track a detected object, the tracker 330 may predict motion of the detected object. For example, as shown in FIG. 6B, given an old position 610 of the detected object, the tracker 330 uses optical flow (or another suitable algorithm) to determine a candidate position for a new position 620. The tracker 330 performs a local search around an initial predicted position using a bounding box (e.g., a rectangular search window) having fixed dimensions to find the new position 620.").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of Boult and Arbabian’s disclosure of object tracking using background subtraction, with the known technique of vanish point detection, as taught by Liu, in order to yield the predictable results of accurately improve safety, path planning, and distance judgment of a scene using the cameras of an autonomous vehicle.
Regarding claim 6, Boult and Arbabian do not disclose but Liu teaches the vanishing point position is set by referring to lane information ([0027] The collision warning system 100 may detect the lane markers or other objects such as buildings for vanishing point determination using image processing or object detection algorithms known to one skilled in the art.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of Boult and Arbabian’s disclosure of object tracking using background subtraction, with the known technique of vanish point detection, as taught by Liu, in order to yield the predictable results of accurately improve safety, path planning, and distance judgment of a scene using the cameras of an autonomous vehicle.
Regarding claim 7, Boult and Arbabian do not disclose but Liu teaches the correlator solves the assignment problem using a likelihood ratio ([0030] In some embodiments, the collision warning system 100 selectively tracks one or more objects with corresponding bounding boxes that overlap with the vanishing point of the image frame, which indicates that the tracked objects are likely in the same lane as the vehicle.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the known system of Boult and Arbabian’s disclosure of object tracking using background subtraction, with the known technique of vanish point detection, as taught by Liu, in order to yield the predictable results of accurately improve safety, path planning, and distance judgment of a scene using the cameras of an autonomous vehicle.
Regarding claim 8, Boult discloses the flow rate estimator counts a number of the targets passing through a count line (col 11, lines 16-25: For many applications (for example, counting vehicles or people), there are rules of behavior that govern the direction of flow and position in the field of view. In FIG. 4, one sees two sweep images (410, 415) of two objects (440/445) and (450/455). In a vehicular application, there is often a real or imaginary line on the road 430 that separates the direction of leftward and rightward travel. When there is only one object in the scene, it may stray over the line, but it is uncommon for the center of the object to cross over that real or imaginary line.), and
the count line is set to cross a parallel line for defining the vanishing point position (fig. 8).
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Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20190251695 A1 to claim 1: [0060] To address such a situation, if the result of the comparison at step S400, S401 is negative, that is, if the probability S.sub.t.sup.BG(x) exceeds the first predetermined threshold T.sub.BG and the difference S.sub.t.sup.FG(x) is lower than the second predetermined threshold T.sub.FG, a third rule is applied in the next step S600, assigning the pixel at pixel position x and time t to either the foreground pixel set or the background pixel set according to a conventional background subtraction algorithm comparing a pixel value {right arrow over (I)}(x) of the pixel at pixel position x and time t with a pixel value of a corresponding pixel in a background model based on at least another image of the plurality of related Images.
US 20220086324 A1 to claim 1 “dynamic background”: [0066] In step S161, a background image photographed before a dynamic object appears may be acquired.
US 9805301 B1 to claim 1: "col 6, lines 6-10: Additionally, the cost function to be optimized is J(x)=d(I(x),Io), with J:custom character.sup.2.fwdarw.[0, 1]. J(x) takes a parameter x as input and outputs a normalized scalar score corresponding the match between the current camera view and background template patch.
col 7, lines 56-62: This is essentially a discrete time dynamical system. Here x.sub.i(t) and v.sub.i(t) are the position and velocity vectors. At time t of the i-th particle, q˜[0,1] is a uniformly distributed random variable, and c.sub.1 and c.sub.2 are parameters that weigh the influence of their respective terms in the velocity update equation. w is a decay constant which controls the swarm's asymptotic (convergence) behavior. The parameter q facilitates an initially random search of the solution space. The search becomes more directed after a few iterations, depending on f(x) and system parameters, as the swarm is attracted towards “favorable” regions."
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AHMED A NASHER whose telephone number is (571)272-1885. The examiner can normally be reached Mon - Fri 0800 - 1700.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emily Terrell can be reached at (571) 270-3717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AHMED A NASHER/Examiner, Art Unit 2675
/EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666
Prosecution Insights