DETAILED ACTION
Claims 1-10 are pending in this application and have been examined with the priority date of 11/23/2022 in accordance with the applicant’s claim for foreign priority.
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
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 limitations are:
Infrastructure sensor in claim 1
Acquisition unit in claim 6
And control unit I claims 6-10
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 § 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.
1. Claims 1-3, 5, 6-8 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Shen (US 20170243069 A1) in view of Alon (US 20180018547 A1).
Regarding claim 1, Shen discloses; A method for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors, the method comprising:
(a) acquiring an image from an infrastructure sensor (Shen, [0016] and [0017] an image sensor captures image frames and acquires pixel data, figure 6, image sensor 665);
(b) determining a first pixel corresponding to a corner of each object included in the image, and a second pixel which does not correspond to the corner of the object (Shen, [0022] candidate corners in the pixel data are detecting for object in the image, [0024] the system may generate a set of candidate corner pixels in the image frame and a set of pixel data which surrounds the candidate corner (non-corner pixels));
Shen does not teach; (c) generating a binary matrix corresponding to the first pixel and the second pixel;
and (d) calibrating an absolute coordinate of the image according to a similarity based on the binary matrix.
In the same field of endeavor Alon teaches; (c) generating a binary matrix corresponding to the first pixel and the second pixel (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not);
and (d) calibrating an absolute coordinate of the image according to a similarity based on the binary matrix (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not, for pixels containing a corner a value of 1 is assigned and for pixels not containing a corner a value of 0 is assigned, which is analogous to an absolute coordinate as detailed in page 4 of the applicant’ s specification).
The combination of Shen and Alon would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Shen teaches a corner detection method using arrays of corner detection values, but does not teach the use of binary matrices to simply show whether or not a corner is present. Alon teaches this limitation, the use of a binary threshold method for determining whether a corner exists or not would be advantageous in simplifying the encoding process and cutting down of processing power. (Alon, [0047]-[0050])
Regarding claim 2, the combination of Shen and Alon teaches; The method for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 1,
wherein step (c) above includes allocating an element corresponding to an absolute coordinate of the first pixel corresponding to the corner of the object with 1 and allocating an element corresponding to an absolute coordinate of the second pixel which does not correspond to the corner of the object with 0 to generate the binary matrix (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not, for pixels containing a corner a value of 1 is assigned and for pixels not containing a corner a value of 0 is assigned, which is analogous to an absolute coordinate as detailed in page 4 of the applicant’ s specification).
The combination of Shen and Alon would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Shen teaches a corner detection method using arrays of corner detection values, but does not teach the use of binary matrices to simply show whether or not a corner is present. Alon teaches this limitation, the use of a binary threshold method for determining whether a corner exists or not would be advantageous in simplifying the encoding process and cutting down of processing power. (Alon, [0047]-[0050])
Regarding claim 3, the combination of Shen and Alon teaches; The method for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 1,
wherein step (d) above includes calculating a similarity between a binary matrix based on the image at a previous time point and a binary matrix of the image at a current time point (Shen, [0029] the features between two sequential image frames may be compared to match features),
and maintaining the absolute coordinate of the image at the current time point when the similarity is larger than the threshold (Shen, [0028] the determination of the matching pair is done using comparison for a set of matched features which must have a certain number of matches features or higher to be determined as a pair, [0035] each pair of features may be compared).
Regarding claim 5, the combination of Shen and Alon teaches; The method for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 3,
wherein step (d) above includes calculating, when the similarity is smaller than the threshold, a similarity based on a direction for acquiring the image of the infrastructure sensor according to a 2D convolution of the binary matrix at the previous time point and the binary matrix at the current time point (Shen, figure 7, the pixel data undergoes feature matching and camera orientation estimation, and then a tolerance level is assessed, if this tolerance has not been met more data is acquired repeatedly, since the system recollects data and re-matches features between time points and computes the calibration in response to the threshold not being met, the steps of the data undergoing a gradient computation in two directions per [0025] would occur on the arrays of data in response to the threshold being met, the step of gradient computing is a convolution of the two matrices of data),
calculating pixel information corresponding to the similarity based on the direction of the infrastructure sensor (Shen, [0038] the matched features may be determined directionally based on the direction the vehicle is moving),
and calibrating the absolute coordinate of the image at the current time point based on the pixel information (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not, for pixels containing a corner a value of 1 is assigned and for pixels not containing a corner a value of 0 is assigned, which is analogous to an absolute coordinate as detailed in page 4 of the applicant’ s specification).
The combination of Shen and Alon would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Shen teaches a corner detection method using arrays of corner detection values, but does not teach the use of binary matrices to simply show whether or not a corner is present. Alon teaches this limitation, the use of a binary threshold method for determining whether a corner exists or not would be advantageous in simplifying the encoding process and cutting down of processing power. (Alon, [0047]-[0050])
Regarding claim 6, the combination of Shen and Alon teaches; An apparatus for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors, the apparatus comprising:
an acquisition unit acquiring an image from an infrastructure sensor (Shen, [0016] and [0017] an image sensor captures image frames and acquires pixel data, figure 6, image sensor 665);
and a control unit determining a first pixel corresponding to a corner of each object included in the image, and a second pixel which does not correspond to the corner of the object (Shen, [0022] candidate corners in the pixel data are detecting for object in the image, [0024] the system may generate a set of candidate corner pixels in the image frame and a set of pixel data which surrounds the candidate corner (non-corner pixels)),
generating a binary matrix corresponding to the first pixel and the second pixel (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not),
and calibrating an absolute coordinate of the image according to a similarity based on the binary matrix (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not, for pixels containing a corner a value of 1 is assigned and for pixels not containing a corner a value of 0 is assigned, which is analogous to an absolute coordinate as detailed in page 4 of the applicant’ s specification).
The combination of Shen and Alon would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Shen teaches a corner detection method using arrays of corner detection values, but does not teach the use of binary matrices to simply show whether or not a corner is present. Alon teaches this limitation, the use of a binary threshold method for determining whether a corner exists or not would be advantageous in simplifying the encoding process and cutting down of processing power. (Alon, [0047]-[0050])
Regarding claim 7, the combination of Shen and Alon teaches; The apparatus for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 6, wherein the control unit allocates an element corresponding to an absolute coordinate of the first pixel corresponding to the corner of the object with 1 and allocates an element corresponding to an absolute coordinate of the second pixel which does not correspond to the corner of the object with 0 to generate the binary matrix (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not, for pixels containing a corner a value of 1 is assigned and for pixels not containing a corner a value of 0 is assigned, which is analogous to an absolute coordinate as detailed in page 4 of the applicant’ s specification).
The combination of Shen and Alon would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Shen teaches a corner detection method using arrays of corner detection values, but does not teach the use of binary matrices to simply show whether or not a corner is present. Alon teaches this limitation, the use of a binary threshold method for determining whether a corner exists or not would be advantageous in simplifying the encoding process and cutting down of processing power. (Alon, [0047]-[0050])
Regarding claim 8, the combination of Shen and Alon teaches; The apparatus for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 6, wherein the control unit calculates a similarity between a binary matrix based on the image at a previous time point and a binary matrix of the image at a current time point (Shen, [0029] the features between two sequential image frames may be compared to match features), and maintains the absolute coordinate of the image at the current time point when the similarity is larger than the threshold (Shen, [0028] the determination of the matching pair is done using comparison for a set of matched features which must have a certain number of matches features or higher to be determined as a pair, [0035] each pair of features may be compared).
Regarding claim 10, the combination of Shen and Alon teaches; The apparatus for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 8,
wherein the control unit calculates, when the similarity is smaller than the threshold, a similarity based on a direction for acquiring the image of the infrastructure sensor according to a 2D convolution of the binary matrix at the previous time point and the binary matrix at the current time point (Shen, figure 7, the pixel data undergoes feature matching and camera orientation estimation, and then a tolerance level is assessed, if this tolerance has not been met more data is acquired repeatedly, since the system recollects data and re-matches features between time points and computes the calibration in response to the threshold not being met, the steps of the data undergoing a gradient computation in two directions per [0025] would occur on the arrays of data in response to the threshold being met, the step of gradient computing is a convolution of the two matrices of data),
calculates pixel information corresponding to the similarity based on the direction of the infrastructure sensor (Shen, [0038] the matched features may be determined directionally based on the direction the vehicle is moving),
and calibrates the absolute coordinate of the image at the current time point based on the pixel information (Alon, [0049] corner encoding may be a binary matric corresponding to pixels which contain a corner or not, for pixels containing a corner a value of 1 is assigned and for pixels not containing a corner a value of 0 is assigned, which is analogous to an absolute coordinate as detailed in page 4 of the applicant’ s specification).
The combination of Shen and Alon would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Shen teaches a corner detection method using arrays of corner detection values, but does not teach the use of binary matrices to simply show whether or not a corner is present. Alon teaches this limitation, the use of a binary threshold method for determining whether a corner exists or not would be advantageous in simplifying the encoding process and cutting down of processing power. (Alon, [0047]-[0050])
2. Claims 4 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Shen (US 20170243069 A1) in view of Alon (US 20180018547 A1) and Mirza (US 20220165063 A1).
Regarding claim 4, the combination of Shen and Alon fails to teach; The method for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 3,
wherein step (d) above includes controlling a control server to transmit a positioning error occurrence message by the infrastructure sensor when the similarity is smaller than the threshold.
However, Mirza teaches; wherein step (d) above includes controlling a control server to transmit a positioning error occurrence message by the infrastructure sensor when the similarity is smaller than the threshold (Mirza, [0204]-[0214] and figure 8, pixel positions are matched, and if they do not match, and alert is sent that the sensor has moved and must be returned (positioning error), [0162]-[0164] thresholds are used to determine if the positions have changed, this determination is made by verifying that if the determined accuracy/similarity is less than a threshold, that the position has changed.).
The combination of Shen, Alon and Mirza, would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Neither Shen nor Alon teach a method of sending a positioning error if a threshold of similarity is not met, however Mirza teaches this deficiency. The addition of this feature of Mirza would reasonably improve the systems of Shen and Alon because this feature allows for the user to be alerted if the calibrated position of the sensor is compromised so this can be corrected. (Mirza, [0104]-[2014] and [0162]-[0164])
Regarding claim 9, the combination of Shen, Alon and Mirza teaches; The apparatus for detecting and correcting positioning errors of sensed objects in real time in infrastructure sensors of claim 8, wherein the control unit controls a control server to transmit a positioning error occurrence message by the infrastructure sensor when the similarity is smaller than the threshold (Mirza, [0204]-[0214] and figure 8, pixel positions are matched, and if they do not match, and alert is sent that the sensor has moved and must be returned (positioning error), [0162]-[0164] thresholds are used to determine if the positions have changed, this determination is made by verifying that if the determined accuracy/similarity is less than a threshold, that the position has changed.).
The combination of Shen, Alon and Mirza, would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Neither Shen nor Alon teach a method of sending a positioning error if a threshold of similarity is not met, however Mirza teaches this deficiency. The addition of this feature of Mirza would reasonably improve the systems of Shen and Alon because this feature allows for the user to be alerted if the calibrated position of the sensor is compromised so this can be corrected. (Mirza, [0104]-[2014] and [0162]-[0164])
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. For a listing of analogous prior art please see the attached PTO-892 Notice of References cited sheet.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JORDAN M ELLIOTT whose telephone number is (703)756-5463. The examiner can normally be reached M-F 8AM-5PM ET.
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/J.M.E./Examiner, Art Unit 2666
/EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666