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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/11/2026 has been entered.
Response to Amendment
In light of Applicant’s amendment of the claims, the claims are no longer interpreted under 35 U.S.C. 112(f).
In light of Applicant’s amendment of the claims, the prior rejections of record under 35 U.S.C. 112(b) with respect to the claims are withdrawn.
In light of Applicant’s amendment of the claims, the claims now recite a practical application. Accordingly, claim rejections under 35 U.S.C. 101 are withdrawn.
Status of Claims
Claims 1-5, 7-23 and 25-27 are pending. Claims 1, 3-5, 10, 13 and 16-18 are amended. Claim 6 and 24 are cancelled.
Response to Arguments
Applicant's arguments filed on May 11, 2026 with respect to rejection of claims under 35 U.S.C. 103 has been fully considered; but they are not found persuasive. Specifically, in page 9 of its reply, Applicant argues in second paragraph that Barnes does not disclose representing motion as stored change coordinates expressed as translocation offsets within a coordinate space used for modeling an anonymized structure. Examiner respectfully disagrees. Barnes represents motion as change in coordinates expressed as translocation offsets— ¶0007: “obtaining real time translational movement of the coordinates of the feature points”, stores the movement data in a storage— ¶0007: “storing the dataset in a subject data store associated with the subject in a memory location”, constructs a subject model using the subject data— ¶0070: “Using the dataset… points (e.g., on the order of tens of thousands) representing the subject can be created”, wherein the feature points representing the subject are mapped in a coordinate bases system— ¶0089: “feature points that can be mapped to a predefined coordinate system (e.g., two or three-dimensional” and the final representation of the subject is anonymized such that the personally identifiable information is removed— ¶0156: “certain data may be anonymized in one or more ways before it is stored or used, so that personally identifiable information is removed”. Therefore, applicant’s arguments are not found persuasive.
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 13 and 18 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.
With respect to claim 13, it recites “establish, as an estimated established location, the estimated location relative to an estimated an established location of another established reference point, the location of one or more of the one of more known reference points, or -a combination thereof”, rendering the claim language vague and indefinite. Please clarify to overcome the rejection.
With respect to claim 18, the claim recites “an established reference point”. Independent base Claim 13 previously recited “an established reference point” rendering claim 18 indefinite. Examiner suggests amending the claim language to recite “the established reference point” in order to overcome the rejection.
Additionally, claim 18 recites “known reference points”. There is insufficient antecedent basis for this limitation. Independent base claim 13 provides antecedent basis for “one or more known reference points” in the claims. Examiner suggests amending the claim language to match the base claim in order to overcome the rejection.
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-5, 7-9, 11-22 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Vu et al. (US 2018/0049669 A1) in view of Radwin et al. (US 2020/0279102 A1) and in further view of Barnes et al. (US 2017/0323472 A1).
Regarding claim 1, Vu teaches, A method (Vu, ¶0021: “method of estimating posture of a subject”) performed by one or more processors executing instructions, (Vu, ¶0097: “instructions for the operation of the apparatus. In certain embodiments, the kit further comprises a computer for processing the data”) comprising: identifying locations of one or more known reference points (Vu, ¶0232: “markers emulate the methodology of tracking known joint positions. This provides a highly-accurate method for providing a ground-truth of the patient's posture”) and estimating a location of an obscured reference point of a human subject (Vu, ¶0223: “identify and refine potential joint locations by analyzing thermally intense regions of the body and limiting ambiguities within the depth image to provide better joint estimates within the occluded region”) in a sequence of video images captured of the subject over time, (Vu, ¶0187: “detecting the chest surface of the patient is derived from the acquisition of the sampled depth-image D.sub.s(t) (depth samples per-timestep”) wherein the one or more known reference points are visible and the obscured reference point is obscured in the sequence of video images; (Vu, ¶0226: “if the known skeletal joint positions are provided for the observed thermal distribution, the patient's skeletal posture can be estimated even when the subject is highly occluded, has several ambiguous joint positions”) improving the accuracy of the estimated location to convert the obscured reference point to an established reference point (Vu, ¶0223: “To provide a reliable means of estimating occluded skeletal postures… performing accurate joint estimations”) comprising tracking changes in the sequence of video images using (Vu, ¶0014: “method further comprises monitoring any changes in the subject's posture or position”) and known anatomical relationships with respect to the obscured reference point and one or more of the one or more known reference points or a previously established reference point; (Vu, ¶0226: “if the known skeletal joint positions are provided for the observed thermal distribution, the patient's skeletal posture can be estimated even when the subject is highly occluded, has several ambiguous joint positions”) translating the locations of the one or more known reference points and the established reference point (Vu, ¶0187: “acquisition of the sampled depth-image D.sub.s(t) (depth samples per-timestep) containing the patient and the raw skeletal data”) into a coordinate space of a coordinate system (Vu, ¶0187: “samples collected from the depth-image, converted into three dimensional coordinates”) generate time sequenced coordinates for the one or more reference points and the established reference point, (Vu, ¶0187: “form a representation of the patient's entire chest region as an enclosed volume defined through a point-cloud containing oriented points that approximate the patient's chest deformation states as a function of time”). However, Vu does not explicitly teach, computer-implemented object detection operating on pixel data of the video image frames and wherein the time sequence coordinates comprise time sequenced change coordinates represented as translocation offsets from prior coordinate locations within the coordinate space; and constructing a coordinate-based subject model from the time sequenced change coordinates, wherein the subject model comprises an anonymized representation of the subject.
In an analogous field of endeavor, Radwin teaches, computer-implemented object detection (Radwin, ¶0069: “Joint locations or other body feature locations used to determine position information may be identified using computer vision algorithms”) operating on pixel data of the video image frames (Radwin, ¶0157: “monitoring system 10 may compare successive frames of the video by comparing corresponding pixels… joint locations and/or other body feature point locations, etc.) of a subject”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu using the teachings of Radwin to introduce tracking pixels of joint locations across video frames. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of accurately tracking the posture of a subject. Therefore, it would have been obvious to combine the analogous arts Vu and Radwin to obtain the above-described limitations in claim 1. However, the combination of Vu and Radwin does not explicitly teach, wherein the time sequence coordinates comprise time sequenced change coordinates represented as translocation offsets from prior coordinate locations within the coordinate space; and constructing a coordinate-based subject model from the time sequenced change coordinates, wherein the subject model comprises an anonymized representation of the subject.
In another analogous field of endeavor, Barnes teaches, wherein the time sequence coordinates comprise time sequenced change coordinates (Barnes, ¶0007: “thereby obtaining real time translational movement of the coordinates of the feature points”) represented as translocation offsets from prior coordinate locations within the coordinate space; (Barnes, ¶0084: “the time-stamped coordinates of features identified across the time-stamped images, and the translational movement of those coordinates across the time-stamped images”) and constructing a coordinate-based subject model from the time sequenced change coordinates, (Barnes, ¶0030: “constructs two or three-dimensional maps… where the constructed maps are used to create dense point clouds and/or generate textured meshes representing a subject”) wherein the subject model comprises an anonymized representation of the subject. (Barnes, ¶0156: “certain data may be anonymized in one or more ways before it is stored or used, so that personally identifiable information is removed”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin using the teachings of Barnes to introduce constructing a subject model using time-stamped coordinates data. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of modeling the tracked posture of a subject. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin and Barnes to obtain the invention in claim 1.
Regarding claim 2, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 1, further comprising transmitting the time sequence change coordinates over a network for analysis and/or storage. (Barnes, ¶0097: “client device 104 transmits the first dataset to the data repository 108 through the network 106”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin and in further view of Barnes using the additional teachings of Barnes to introduce data transmission. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of further analyzing or storing the transmitted data in a remote device. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin and Barnes to obtain the invention in claim 2.
Regarding claim 3, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 2, wherein the time sequenced change coordinates comprise coordinates of the established refence point within the coordinate space at specified times within the time sequence. (Vu, ¶0039: “Each of the identified steps must be recalculated for each frame during the monitoring process. This provides an active representation of the patient as they are monitored and the resulting surface deformations closely illustrate the patient's breathing state”).
Regarding claim 4, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 2, wherein the time sequenced change coordinates comprise translocation instructions within the coordinate system space from a prior coordinate location with the coordinate space. (Barnes, ¶0084: “the time-stamped coordinates of features identified across the time-stamped images, and the translational movement of those coordinates across the time-stamped images”). The proposed combination as well as the motivation for combining Vu, Radwin and Barnes references presented in the rejection of claim 1, apply to claim 4 and are incorporated herein by reference. Thus, the method recited in claim 4 is met by Vu, Radwin and Barnes.
Regarding claim 5, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 1, wherein the coordinate system comprises a grid system, a vector based system, or a grid system based on pixels of an image sensor, digital camera, or digital image. (Vu, ¶0139: “a posture detection algorithm is used to detect the cross section vector of human chest movement”).
Regarding claim 7, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 1, wherein the subject model comprises a stick figure abstraction. (Vu, ¶0049: “skeletal posture estimations”; also see Fig. 26A-26D).
Regarding claim 8, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 7, further comprising analyzing the subject model to track movements, (Vu, ¶0067: “the system tracks the large-scale movements and posture changes of the person”) growth, behavior, or combination thereof. (Vu, ¶0178: “extracting a complete volumetric iso-surface that includes the deformation behavior of the patient's left thorax, right thorax, and abdominal region”).
Regarding claim 9, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 7, further comprising applying AI or machine learning (Vu, ¶0163: “A machine learning technique was used to realize area recognition”) to subject models of a population of subjects for early detection of conditions. (Vu, ¶0219: “the breathing volume waveforms was found to represent unique patterns of a participant, which can contribute to clinical analysis of the patient's condition”).
Regarding claim 11, Vu in view of Radwin and in further view of Barnes teaches, A machine-readable medium carrying machine readable instructions, which when executed by a processor of a machine, causes the machine to carry out the method of claim 1. (Vu, ¶0018: “a kit comprising the apparatus of the invention and instructions for the operation of the apparatus. In certain embodiments, the kit further comprises a computer for processing the data collected by the apparatus”).
Regarding claim 12, Vu in view of Radwin and in further view of Barnes teaches, A system comprising a processor and memory comprising instructions that when executed by the processor causes the system to perform the operations of claim 1. (Vu, ¶0018: “a kit comprising the apparatus of the invention and instructions for the operation of the apparatus. In certain embodiments, the kit comprises a computer for processing the data collected by the apparatus”).
Regarding claim 13, Vu teaches, A system configured to perform data abstraction (Vu, ¶0067: “the system tracks the large-scale movements and posture changes of the person”) and (Vu, ¶0018: “a kit comprising the apparatus of the invention and instructions for the operation of the apparatus. In certain embodiments, the kit comprises a computer for processing the data collected by the apparatus”) identifying, with a model generator, a location of one or more known reference points of a human subject (Vu, ¶0232: “markers emulate the methodology of tracking known joint positions. This provides a highly-accurate method for providing a ground-truth of the patient's posture”) visible in one or more video image frames captured of the subject; (Vu, ¶0252: “The image sequences in FIGS. 38A-38F illustrate six common postures”) estimating a location of an obscured reference point of interest with respect to the subject obscured in one or more video image frames captured of the subject (Vu, ¶0223: “identify and refine potential joint locations by analyzing thermally intense regions of the body and limiting ambiguities within the depth image to provide better joint estimates within the occluded region”) based on one or more of object detection or a known relationship with one or more of the one or more known reference points in which the location is identified-, (Vu, ¶0226: “if the known skeletal joint positions are provided for the observed thermal distribution, the patient's skeletal posture can be estimated even when the subject is highly occluded, has several ambiguous joint positions”) converting the obscured reference point of interest to an established reference point by improving the accuracy of the estimated location (Vu, ¶0223: “To provide a reliable means of estimating occluded skeletal postures… performing accurate joint estimations”) by tracking changes in subsequently captured video image frames of the subject (Vu, ¶0014: “method further comprises monitoring any changes in the subject's posture or position”) and applying one or more statistical methods to establish, as an estimated established location, the estimated location relative to an estimated an established location of another established reference point, the location of one or more of the one or more known reference points, or combination thereof; (Vu, ¶0192: “The radius of this cylinder is defined by the average distance of both the left 1 and right r shoulder joints”; interpreting the spine joint as the obscured point, the spine joint is known to be equally distant from the two shoulder joints, and therefore, the location can be estimated) translating the identified and estimated established locations of the respective known and established reference points into a coordinate space of a coordinate system to (Vu, ¶0187: “The samples collected from the depth-image, converted into three dimensional coordinates”) generate time sequenced coordinates of the reference points, (Vu, ¶0187: “form a representation of the patient's entire chest region as an enclosed volume defined through a point-cloud containing oriented points that approximate the patient's chest deformation states as a function of time”). However, Vu does not explicitly teach, wherein the object detection is computer-implemented and operates on pixel data of the video image frames and wherein the time sequenced coordinates comprise time sequenced change coordinates represented as translocation offsets from prior coordinate locations within the coordinate space; and constructing, by the processor executing the instructions, a subject model from the time sequenced change coordinates of the reference points, wherein the subject model comprises an anonymized representation of the subject.
In an analogous field of endeavor, Radwin teaches, wherein the object detection is computer-implemented (Radwin, ¶0069: “Joint locations or other body feature locations used to determine position information may be identified using computer vision algorithms”) and operates on pixel data of the video image frames (Radwin, ¶0157: “monitoring system 10 may compare successive frames of the video by comparing corresponding pixels… joint locations and/or other body feature point locations, etc.) of a subject”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu using the teachings of Radwin to introduce tracking pixels of joint locations across video frames. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of accurately tracking the posture of a subject. Therefore, it would have been obvious to combine the analogous arts Vu and Radwin to obtain the above-described limitations in claim 13. However, the combination of Vu and Radwin does not explicitly teach, wherein the time sequenced coordinates comprise time sequenced change coordinates represented as translocation offsets from prior coordinate locations within the coordinate space; and constructing, by the processor executing the instructions, a subject model from the time sequenced change coordinates of the reference points, wherein the subject model comprises an anonymized representation of the subject.
Barnes teaches, wherein the time sequenced coordinates comprise time sequenced change coordinates (Barnes, ¶0007: “thereby obtaining real time translational movement of the coordinates of the feature points”) represented as translocation offsets from prior coordinate locations within the coordinate space; Barnes, ¶0084: “the time-stamped coordinates of features identified across the time-stamped images, and the translational movement of those coordinates across the time-stamped images”) and constructing, by the processor executing the instructions, a subject model from the time sequenced change coordinates of the reference points, (Barnes, ¶0030: “constructs two or three-dimensional maps… where the constructed maps are used to create dense point clouds and/or generate textured meshes representing a subject”) wherein the subject model comprises an anonymized representation of the subject. (Barnes, ¶0156: “certain data may be anonymized in one or more ways before it is stored or used, so that personally identifiable information is removed”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin using the teachings of Barnes to introduce constructing an anonymized subject model using time-stamped coordinates data. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of modeling the tracked posture of a subject. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin and Barnes to obtain the invention in claim 13.
Regarding claim 14, Vu in view of Radwin and in further view of Barnes teaches, The system of claim 13, wherein the time sequenced coordinates comprise time sequenced change coordinates. (Barnes, ¶0007: “thereby obtaining real time translational movement of the coordinates of the feature points”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin and in further view of Barnes using the additional teachings of Barnes to introduce tracking the changes in coordinates. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of accurately modeling the joint movements of the subject over time. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin and Barnes to obtain the invention in claim 14.
Regarding claim 15, it recites a system with elements corresponding to the steps of the method recited in claim 2. Therefore, the recited elements of system claim 15 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 2. Additionally, the rationale and motivation to combine Vu, Radwin and Barnes presented in rejection of claim 1, apply to this claim.
Regarding claim 16, it recites a system with elements corresponding to the steps of the method recited in claim 3. Therefore, the recited elements of system claim 16 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 3. Additionally, the rationale and motivation to combine Vu, Radwin and Barnes presented in rejection of claim 1, apply to this claim.
Regarding claim 17, it recites a system with elements corresponding to the steps of the method recited in claim 4. Therefore, the recited elements of system claim 17 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 4. Additionally, the rationale and motivation to combine Vu, Radwin and Barnes presented in rejection of claim 1, apply to this claim.
Regarding claim 18, Vu in view of Radwin and in further view of Barnes teaches, The system of claim 17, wherein the operations further comprise: estimating locations of a plurality of obscured reference points of interest based on known relationships with known reference points, an established reference point, or both; (Vu, ¶0226: “if the known skeletal joint positions are provided for the observed thermal distribution, the patient's skeletal posture can be estimated even when the subject is highly occluded, has several ambiguous joint positions”) and translating the estimated locations of the estimated obscured reference points of interest into time sequenced coordinates (Barnes, ¶0007: “Time-stamped coordinates of the feature points in the workflow are acquired at each of the first plurality of time points”) with the coordinate space comprising time sequenced change coordinates. (Barnes, ¶0007: “thereby obtaining real time translational movement of the coordinates of the feature points”). The proposed combination as well as the motivation for combining Vu, Radwin and Barnes references presented in the rejection of claim 14, apply to claim 18 and are incorporated herein by reference. Thus, the system recited in claim 18 is met by Vu, Radwin and Barnes.
Regarding claim 19, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 13, wherein the coordinate system comprises a grid system or a vector based system. (Vu, ¶0205: “a voxel grid size that provides an accurate chest surface representation was selected”).
Regarding claim 20, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 13, wherein the coordinate system comprises a grid system (Vu, ¶0205: “a voxel grid size that provides an accurate chest surface representation was selected”) is based on pixels of an image sensor, digital camera, or digital image. (Vu, ¶0193: “stability scheme based on pixel tracking history is provided. A visualization of this pixel-history is provided in FIG. 17B”).
Regarding claim 21, it recites a system with elements corresponding to the steps of the method recited in claim 8. Therefore, the recited elements of system claim 21 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 8. Additionally, the rationale and motivation to combine Vu, Radwin and Barnes presented in rejection of claim 1, apply to this claim.
Regarding claim 22, it recites a system with elements corresponding to the steps of the method recited in claim 9. Therefore, the recited elements of system claim 22 are mapped to the proposed combination in the same manner as the corresponding steps in method claim 9. Additionally, the rationale and motivation to combine Vu, Radwin and Barnes presented in rejection of claim 1, apply to this claim.
Regarding claim 25, Vu in view of Radwin and in further view of Barnes teaches, The system of claim 13, wherein the one or more statistical methods includes averaging the estimated location as correlated to the known relationships. (Vu, ¶0192: “The radius of this cylinder is defined by the average distance of both the left 1 and right r shoulder joints”; interpreting the spine joint is the obscured point, it will be equally distant from the two shoulder joints).
Claims 10 and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Vu et al. (US 2018/0049669 A1), in view of Radwin et al. (US 2020/0279102 A1), in further view of Barnes et al. (US 2017/0323472 A1) and still in further view of Wang et al. (US 2023/0298204 A1).
Regarding claim 10, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 1, further comprising. However, the combination of Vu, Radwin and Barnes does not explicitly teach, applying a confidence score to the estimated location of the obscured reference point.
In an analogous field of endeavor, Wang teaches, applying a confidence score to the estimated location of the obscured reference point. (Wang, ¶0061: “pose detector 216 may assign a lower confidence score C.sub.2d.sup.k to keypoints in the image that are occluded and a higher confidence score C.sub.2d.sup.k to keypoints that are not occluded”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin and in further view of Barnes using the teachings of Wang to introduce applying confidence scores to key point estimation. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of computing the accuracy of an estimated obscured point. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin, Barnes and Wang to obtain the invention in claim 10.
Regarding claim 26, Vu in view of Radwin and in further view of Barnes teaches, The system of claim 13, wherein the operations further comprise. However, the combination of Vu, Radwin and Barnes does not explicitly teach, applying a confidence score to the estimated established location of the established reference point, the estimated location of the obscured reference point of interest, or both.
In an analogous field of endeavor, Wang teaches, applying a confidence score to the estimated established location of the established reference point, the estimated location of the obscured reference point of interest, or both. (Wang, ¶0061: “pose detector 216 may assign a lower confidence score C.sub.2d.sup.k to keypoints in the image that are occluded and a higher confidence score C.sub.2d.sup.k to keypoints that are not occluded”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin and in further view of Barnes using the teachings of Wang to introduce applying confidence scores to key point estimation. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of computing the accuracy of an estimated obscured point. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin, Barnes and Wang to obtain the invention in claim 26
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Vu et al. (US 2018/0049669 A1), in view of Radwin et al. (US 2020/0279102 A1), in further view of Barnes et al. (US 2017/0323472 A1) and still in further view of Biswas et al. (US 2024/0311983 A1).
Regarding claim 23, Vu in view of Radwin and in further view of Barnes teaches, The system of claim 13, wherein the operations further comprise. However, the combination of Vu, Radwin and Barnes does not explicitly teach, identifying a non-subject object having a known dimension in the video image frames to scale the image frames.
In an analogous field of endeavor, Biswas teaches, identifying a non-subject object having a known dimension in the video image frames to scale the image frames. (Biswas, ¶0019: “using a known object's dimensions as a reference point (e.g., scaling sections of a video frame using a scaling factor calculated based upon a known length of an object”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin and in further view of Barnes using the teachings of Biswas to introduce detecting an object of known size. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of automatically scaling the image frames with respect to the size of the known object. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin, Barnes and Biswas to obtain the invention in claim 23.
Claim 27 is rejected under 35 U.S.C. 103 as being unpatentable over Vu et al. (US 2018/0049669 A1), in view of Radwin et al. (US 2020/0279102 A1), in further view of Barnes et al. (US 2017/0323472 A1) and still in further view of He (US 2021/0142677 A1).
Regarding claim 27, Vu in view of Radwin and in further view of Barnes teaches, The method of claim 1. However, the combination of Vu, Radwin and Barnes does not explicitly teach, further comprising outputting the time sequenced change coordinates in response to detecting a change in a coordinate value for at least one reference point.
In an analogous field of endeavor, He teaches, further comprising outputting the time sequenced change coordinates in response to detecting a change in a coordinate value for at least one reference point. (He, ¶0006: “a Dynamic Vision Sensor (DVS) coupled to the vehicle, the timestamp matrix representing a coordinate position and a timestamp of each event when the event is triggered by movement of the object”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Vu in view of Radwin and in further view of Barnes using the teachings of He to introduce a dynamic vision sensing triggering system. A person skilled in the art would be motivated to combine the known elements as described above and achieve the predictable result of automatically tracking the coordinate positions of an object triggered by a movement of the object. Therefore, it would have been obvious to combine the analogous arts Vu, Radwin, Barnes and He to obtain the invention in claim 27.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEHRAZUL ISLAM whose telephone number is (571)270-0489. The examiner can normally be reached Monday-Friday: 8am-5pm.
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, Saini Amandeep can be reached on (571) 272-3382. 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.
/MEHRAZUL ISLAM/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
Prosecution Insights