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 .
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.
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: “means for capturing an image of a performance area; means for detecting or more performers in the performance area using the captured image; means for estimating positions of the one or more detected performers; means for smoothing the estimated positions of the one or more detected performers based on prior estimated locations; and means for providing the smoothed estimated positions to display controller circuitry for generation of an interactive effect based on the smoothed estimated positions” (emphasis added) in claim 20.
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 specification1 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.
Claims 1–5, 10–14 and 20–24 are rejected under 35 U.S.C. § 103 as being unpatentable over McKennoch et al. (U.S. 11,373,318 B1) in view of Zhang et al. (U.S. 12,670,602 B2).
Regarding claim 1, McKennoch discloses an apparatus for a real-time interactive performance, the apparatus comprising:
at least one memory; (Fig. 3, 312A–312B recording devices)
machine readable instructions; and (Fig. 3, 312A–312B recording devices)
processor circuitry to at least one of instantiate or execute the machine readable instructions to: (Fig. 3, 312A–312B recording devices)
capture an image of a performance area; (Per Fig. 3, at least one of McKennoch’s camera 312–312B analyzes a scene of a physical environment 302. McKennoch col. 8 lines 12–27. [s]uch as the video recording devices 312A-312B, view a scene in the physical environment 302 from two distinct positions)
detect one or more performers in the performance area using the captured image; (Per Fi.g 3, McKennoch’s cameras 312A–312B detect myriad participants. Ibid. [t]wo objects in separate images may be said to match if they correspond to the same participant or object, or satisfy one or more matching criteria.)
estimate locations of the one or more detected performers. (Per Fig. 5, McKennoch discloses point clouds applying a prediction algorithm where participant’s position is estimated. Ibid. col. 11 lines 25–30. [t]he point clouds 520A-520C are sets of points generated as a result of applying a prediction algorithm, such as one or more particle filters, to positions of the first participant 506A.)
However, McKennoch fails to specifically disclose smooth the estimated locations of the one or more detected performers based on prior estimated locations; and provide the smoothed estimated locations to display controller circuitry for generation of an interactive effect based on the smoothed estimated locations.
In related art, Zhang discloses smooth the estimated locations of the one or more detected performers based on prior estimated locations; and (Per Fig. 1, Zhang’s bounding shape estimator 110 filters a location of a bounding shape 112. Zhang col. 8 line 57 – col. 9 line 17. The bounding shape estimator 110 may then apply a filter to predict the location 116 of the bounding shape 112 in the second set of images 106 based on location information for the bounding shape output by the object tracker 108 in the first set of images 106. Zhang’s use of a filter, such as a Kalman filter is understood to produce a smoothing effect on the tracked object.)
provide the smoothed estimated locations to display controller circuitry for generation of an interactive effect (Under a broadest reasonable interpretation (BRI), Examiner construed an interactive effect as a bounding shape.) based on the smoothed estimated locations. (Per Fig. 3, Zhang’s bounding shape estimator 110 discloses a bounding shape of a person corresponding to detected motion and proximity thereof. Ibid. col. 9 line 56 – col. 10 line 8. The processor 104 may also determine that the bounding shape of the first person was in close proximity to the bounding shape of the second person.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Zhang into the teachings of McKennoch while other objects remain untracked because of obscurity, a machine learning model outputs a geometrical effect for a tracked object. Ibid. col. 2 lines 47–54.
Regarding claim 10, McKennoch discloses a non-transitory machine readable storage medium comprising instructions that, when executed, cause processor circuitry to at least:
capture an image of a performance area; (Per Fig. 3, at least one of McKennoch’s camera 312–312B analyzes a scene of a physical environment 302. McKennoch col. 8 lines 12–27. [s]uch as the video recording devices 312A-312B, view a scene in the physical environment 302 from two distinct positions)
detect one or more performers in the performance area using the captured image; (Per Fi.g 3, McKennoch’s cameras 312A–312B detect myriad participants. Ibid. [t]wo objects in separate images may be said to match if they correspond to the same participant or object, or satisfy one or more matching criteria.)
estimate locations of the one or more detected performers. (Per Fig. 5, McKennoch discloses point clouds applying a prediction algorithm where participant’s position is estimated. Ibid. col. 11 lines 25–30. [t]he point clouds 520A-520C are sets of points generated as a result of applying a prediction algorithm, such as one or more particle filters, to positions of the first participant 506A.)
However, McKennoch fails to specifically disclose smooth the estimated locations of the one or more detected performers based on prior estimated locations; and provide the smoothed estimated locations to display controller circuitry for generation of an interactive effect based on the smoothed estimated locations.
In related art, Zhang discloses smooth the estimated locations of the one or more detected performers based on prior estimated locations; and (Per Fig. 1, Zhang’s bounding shape estimator 110 filters a location of a bounding shape 112. Zhang col. 8 line 57 – col. 9 line 17. The bounding shape estimator 110 may then apply a filter to predict the location 116 of the bounding shape 112 in the second set of images 106 based on location information for the bounding shape output by the object tracker 108 in the first set of images 106.)
provide the smoothed estimated locations to display controller circuitry for generation of an interactive effect (Under a broadest reasonable interpretation (BRI), Examiner construed an interactive effect as a bounding shape.) based on the smoothed estimated locations. (Per Fig. 3, Zhang’s bounding shape estimator 110 discloses a bounding shape of a person corresponding to detected motion and proximity thereof. Ibid. col. 9 line 56 – col. 10 line 8. The processor 104 may also determine that the bounding shape of the first person was in close proximity to the bounding shape of the second person.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Zhang into the teachings of McKennoch while other objects remain untracked because of obscurity, a machine learning model outputs a geometrical effect for a tracked object. Ibid. col. 2 lines 47–54.
Regarding claim 20, McKennoch an apparatus for real-time interactive performances, the apparatus comprising:
means for capturing an image of a performance area; (Per Fig. 3, at least one of McKennoch’s camera 312–312B analyzes a scene of a physical environment 302. McKennoch col. 8 lines 12–27. [s]uch as the video recording devices 312A-312B, view a scene in the physical environment 302 from two distinct positions)
means for detecting one or more performers in the performance area using the captured image; (Per Fi.g 3, McKennoch’s cameras 312A–312B detect myriad participants. Ibid. [t]wo objects in separate images may be said to match if they correspond to the same participant or object, or satisfy one or more matching criteria.)
means for estimating positions of locations of the one or more detected performers. (Per Fig. 5, McKennoch discloses point clouds applying a prediction algorithm where participant’s position is estimated. Ibid. col. 11 lines 25–30. [t]he point clouds 520A-520C are sets of points generated as a result of applying a prediction algorithm, such as one or more particle filters, to positions of the first participant 506A.)
However, McKennoch fails to specifically disclose means for smoothing the estimated locations of the one or more detected performers based on prior estimated locations; and means for providing the smoothed estimated locations to display controller circuitry for generation of an interactive effect based on the smoothed estimated locations.
In related art, Zhang discloses means for smoothing the estimated locations of the one or more detected performers based on prior estimated locations; and (Per Fig. 1, Zhang’s bounding shape estimator 110 filters a location of a bounding shape 112. Zhang col. 8 line 57 – col. 9 line 17. The bounding shape estimator 110 may then apply a filter to predict the location 116 of the bounding shape 112 in the second set of images 106 based on location information for the bounding shape output by the object tracker 108 in the first set of images 106.)
means for providing the smoothed estimated locations to display controller circuitry for generation of an interactive effect (Under a broadest reasonable interpretation (BRI), Examiner construed an interactive effect as a bounding shape.) based on the smoothed estimated locations. (Per Fig. 3, Zhang’s bounding shape estimator 110 discloses a bounding shape of a person corresponding to detected motion and proximity thereof. Ibid. col. 9 line 56 – col. 10 line 8. The processor 104 may also determine that the bounding shape of the first person was in close proximity to the bounding shape of the second person.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Zhang into the teachings of McKennoch while other objects remain untracked because of obscurity, a machine learning model outputs a geometrical effect for a tracked object. Ibid. col. 2 lines 47–54.
Regarding claim 2, McKennoch as modified by Zhang, discloses the apparatus, wherein the processor circuitry is further to compensate the estimated locations to account for latency. (Per Fig. 5, McKennoch discloses filter inputs to compensate reduced image quality. McKennoch col. 12 lines 35–51. [d]ue to any of a variety of factors (e.g., inclement weather, reduced image quality, obscured visibility, an object being blocked by another object, etc.) embodiments of the kinematic analysis system may be unable to detect the object 506A within a particular image frame. In such cases, the particle filter inputs may include such data)
Regarding claim 3, McKennoch as modified by Zhang, discloses the apparatus, wherein to estimate the locations of the one or more detected performers, the processor circuitry is to apply a homograph matrix to translate from a pixel location within the image to a physical location in the performance area. (Per Fig. 1, Zhang’s processor discloses pixel size information to create a bounding box of a tracked object. Zhang col. 7 lines 18–33. The size information may include a size (e.g., number of pixels, or area) for a bounding shape of a tracked object.)
Regarding claim 4, McKennoch as modified by Zhang, discloses the apparatus, wherein to estimate the locations of the one or more detected performers, the processor circuitry is to generate bounding boxes corresponding to each of the detected one or more performers. (Per Fig. 3, Zhang’s bounding shape estimator 110 discloses a bounding shape of a person corresponding to detected motion and proximity thereof. Zhang col. 9 line 56 – col. 10 line 8. The processor 104 may also determine that the bounding shape of the first person was in close proximity to the bounding shape of the second person.)
Regarding claim 5, McKennoch as modified by Zhang, discloses the apparatus, wherein the estimation of the locations of the one or more detected performers is based on locations of midpoints of lower edges of the bounding boxes. (Per Fig. 3, Zhang’s bounding shape estimator 110 discloses a bounding shape of a person corresponding to detected motion and proximity thereof. Zhang col. 9 line 56 – col. 10 line 8. The processor 104 may also determine that the bounding shape of the first person was in close proximity to the bounding shape of the second person.)
Regarding claim 11, it has been rejected in the same manner as claim 2.
Regarding claim 12, it has been rejected in the same manner as claim 3.
Regarding claim 13, it has been rejected in the same manner as claim 4.
Regarding claim 14, it has been rejected in the same manner as claim 5.
Regarding claim 21, it has been rejected in the same manner as claim 2.
Regarding claim 22, it has been rejected in the same manner as claim 3.
Regarding claim 23, it has been rejected in the same manner as claim 4.
Regarding claim 24, it has been rejected in the same manner as claim 5.
Allowable Subject Matter
Claims 6–9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
De Aguiar et al. (U.S. 8,384,714 B2) discloses a variety of methods to create digital representations of figures.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BENEDICT LEE whose telephone number is (571)270-0390. The examiner can normally be reached 10:00-17:00 (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen R. Koziol can be reached at (408) 918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BENEDICT E LEE/Examiner, Art Unit 2665
/Stephen R Koziol/Supervisory Patent Examiner, Art Unit 2665
1 See Applicant’s Spec. ¶49. He discloses that the means are implemented by image collection circuitry 510.
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