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 Objections
Claim 10 is objected to because of the following informalities: claim 10 recites “The estimation program according to claim 7”, it should recite “The estimation method according to claim 7. Appropriate correction is required.
Claim 18 objected to because of the following informalities: claim 18 recites “and the process estimates, in a case where the parameters are applied to the definition information, it should recite “and the processor estimates, in a case where the parameters are applied to the definition information”. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). The claim(s) recite(s) steps of estimating a position of a top of the head of a player based on the position of other joints in an image This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 7, and 13 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories?
Yes.
Claim(s) 1, 7, and 13 are directed to a non-transitory CRM, a method, and a device, respectively.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
Yes.
The claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The claims comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding Claim(s) 1, 7, and 13: the claims recite the steps (functions) of:
specifying positions of a plurality of joints included in a face of a player (mental process including observation and evaluation, and can be done mentally in the human mind)
estimating a position of a top of the head of the player using each of the positions of the plurality of joints (mental process including observation and evaluation, and can be done mentally in the human mind)
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As such, a person could look at an image of a person, specify the positions of the facial joints and determine the position of the top of the head based on the positions of the facial joints either mentally or using a pen and paper. The mere nominal recitation that the various steps are being executed by a device/in a device (e.g. processing unit) does not take the limitations out of the mental process grouping. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No.
The claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, 7, and 13 does/do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Claim(s) 1, 7, and 13 recite(s) the further limitations of:
inputting an image in which a head of the player is in a predetermined state to a machine learning model (generic computers or components configured to perform the method; the machine leaning model is recited with a high level of generality without any details on how the model’s structure or any specific training process that improves the functioning of a computer or improve another technology or technical field. See claims 2 and 3 in example 47 of the AI-related subject matter eligibility guidance);
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No.
The claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claim(s) 1, 7, and 13 does/do not recite any additional elements that are not well-understood, routine or conventional. The use of a computer to specify and estimate, as claimed in Claim(s) 1, 7, and 13 is a routine, well-understood and conventional process that is performed by computers.
Regarding claim 2-6, 8-12, and 14-18: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s) are directed to (mental process including observation and evaluation, and can be done mentally in the human mind) OR (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations) OR (insignificant pre/post-solution extra activity of gathering/generating data).
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.
Claim(s) 1, 7, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Morrell et al. (US 20230103129) in view of Ikeda et al. (US 20090046891).
Regarding claims 1, 7, and 13:
Morrell discloses: (claim 13 device): An information processing device (FIG. 14, computing device 1400) comprising:
a memory; and a processor coupled to the memory (Fig. 14, CPU 1405 and Memory 1410), or external circuitry”) and configured to:
specify positions of a plurality of joints included in a face of a player by inputting an image in which a head of the player is in a predetermined state to a machine learning model (¶ [0007] and [0210] disclose identifying a set of images, from a plurality of images captured by an imaging sensor, that satisfy defined orientation. ¶ [0030] discloses machine learning models are used to identify facial landmarks and determine face orientation. ¶¶ [0032] – [0034], and [0081] – [0081] disclose selecting images that meet defined orientation criteria, including tilt thresholds and defined turning angles. ¶ [0040] discloses using a machine learning model to identify and extract coordinate locations of facial landmarks, and ¶ [0207] – [0208] and [0210] disclose landmark-detection models); and
While Morrell discloses identifying coordinate locations of facial landmarks, including the “top and bottom of the head” in ¶ [0040] “…use a machine learning model to identify and extract, for each image in a stream of images (e.g., in a video), coordinate locations of various facial landmarks (such as the top and bottom of the head, center, top, bottom, and edges of the eyes and mouth, and the like).”
Morell does not expressly teach: that the position of a top of the head is specifically estimated using each of the positions of the plurality of joints.
However, in a related field, Ikeda teaches: estimate a position of a top of the head of the player using each of the positions of the plurality of joints (¶¶ [0008] – [0010] teach that there is a relationship among facial measurements including facial width, the distance between the lower facial edge and the eye line, and the distance between the eye line and the vertex (i.e. the top of the outline of the skull). ¶ [0089] teaches that the position of the vertex is obtained using the relation among the left/right eye edge distance, the lower-edge to eye line distance, and the eye line to vertex distance. And in ¶ [0094] it discloses computing the eye line to vertex distance and obtaining the vertex position Pd) .
It would have been obvious to a PHOSITA before the effective filing date of the present application to have modified Morell in view of Ikeda so that, after Morrell selects images satisfying defined orientation criteria and extracts facial landmarks coordinate locations using a machine learning model, the system would further estimate the top of the head from those facial positions as taught by Ikeda. Morrell provides the automated ML pipeline for obtaining facial landmark positions from images captured in predefined head states. Ikeda teaches that facial positional relationships can be used to estimate the top of the skill where directed determination is difficult. A PHOSITA would have been motivated to use Morrell’s automatically extracted facial landmark coordinates as positional unput to Ikeda’s head top estimation approach to automate top of head estimation from images using known facial geometry relationship, with predicable results.
Claim(s) 3, 9, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Morrell et al. (US 20230103129) in view of Ikeda et al. (US 20090046891) and Gernoth (US 20190080149).
Regarding claims 3, 9, and 15:
Morrell in view of Ikeda teaches the limitations of claims 1, 7, and 13 as applied above.
Morell in view of Ikeda does not specifically teach: wherein the image input to the machine learning model is any one of an image in a state where a background color and a color of hair of the player are similar, an image in a state where the hair of the player is disordered, and an image in a state where the head of the player is hidden.
However, in a related field, Gernoth teaches: wherein the image input to the machine learning model is any one of an image in a state where a background color and a color of hair of the player are similar, an image in a state where the hair of the player is disordered, and an image in a state where the head of the player is hidden (¶ [0004] “…Occlusion of the user includes the blocking or obscuring of the user (e.g., the face of the user or some portion of the user's face) by some object (e.g., a finger, a hand, hair, masks, scarfs, etc.) in the image. Occlusion of the user in captured images may reduce the effectiveness of processing the image in the facial recognition process.”; ¶ [0005] “Landmark and occlusion heat maps may be generated and used to assess occlusion of landmarks on a user's face in a captured image.”; ¶ [0049] “…after landmark heat maps 206 are generated, landmark locations are identified (e.g., estimated) in identify landmark locations 210. Identify landmark locations 210 may include generating two-dimensional representations of where the selected landmark points (e.g., landmark point 302) are positioned in each landmark heat map 206.”; ¶ [0053] “…the landmark point may still be estimated based on the grid representation of the face. For example, a neural network (or other processor) may predict where the landmark point may be based on other data. For example, the neural network can estimate the location of the nose relative to the estimated location of the corners of the eyes.”, and see FIG 8. Though Gernoth is stating that the face is occluded, one of ordinary skill in the art can easily apply the same concept to the head without any undue experimentations).
It would have been obvious to a PHOSITA before the effective filing date of the present invention to have modified Morrell in view of Ikeda to include the that the landmark-based head-top estimation process is applied to images in which the user’s face or head region is hidden or occluded. Morrell already extracts facial landmarks coordinates from input images, and Ikeda already teaches estimating the top of the skull when direct determination is difficult. Gernoth teacher the well-known problem that facial-recognition imagers may include occlusion by hand, hair, mask, or scarfs, and teaches continuing to estimate landmark locations under those occluded conditions. A PHOSITA would have been motivated to incorporate Gernoth’s occluded images state into Morrell in view of Ikeda in order to make the claimed head top estimation robust to occluded input images, with predicable results.
Claim(s) 4, 10, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Morrell et al. (US 20230103129) in view of Ikeda et al. (US 20090046891) and Sakata (WO 2021064830 ( the US document US 20220189042 is used for English translation)).
Regarding claims 4, 10, and 16 :
Morrell in view of Ikeda teaches the limitations of claims 1, 7, and 13 as applied above.
Morell in view of Ikeda does not specifically teach: evaluates a performance related to a balance beam or a floor exercise based on the position of the top of the head.
However, in a related field, Sakata teaches: evaluates a performance related to a balance beam or a floor exercise based on the position of the top of the head (¶ [0036] “…captures three-dimensional data of a performer 1 who is an object, recognizes a skeleton and the like, and accurately scores elements. Note that, in the present embodiment, as an example, an example of recognizing skeleton information of a performer in a gymnastics competition will be described.”; ¶ [0037] “and recognizes a skeleton, which is an orientation of each joint, an angle of each joint, and the like of the athlete from the distance image…a performed element or the like is recognized from the result of the skeleton recognition, and scoring is performed according to a scoring rule”; ¶ [0038] “ for some competitions such as women's balance beam, floor exercise, uneven bars, and men's floor exercise and horizontal bar, scoring is performed according to a combination of elements” ¶ [0055] “…The example of FIG. 5 illustrates that the positions of the 18 joints including coordinates “X3, Y3, Z3” of HEAD are known in “image data A1” that is the distance image. Note that the joint positions may also be extracted by using, for example, a learning model which has been learned in advance and which extracts each joint position from a distance image.”)
It would have been obvious to a PHOSITA before the effective filing date of the present invention to have modified Morrell in view of Ikeda so that the top of the head position as obtained by Morrell in view of Ikeda is used in a known gymnastics performance evaluation such as balance beam or floor exercise. Sakata teaches scoring gymnastics techniques and performance from recognized skeleton position information including the head. A PHOSITA would have been motivated to use the top of the head positional information from Morell in view of Ikeda as part of that known position based evaluation framework in order to improve evaluation accuracy and support automated judging with predicable results.
Claim(s) 5, 11, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Morrell et al. (US 20230103129) in view of Ikeda et al. (US 20090046891) and Lee (US 20120057753).
Regarding claims 5, 11, and 17:
Morrell in view of Ikeda teaches the limitations of claims 1, 7, and 13 as applied above.
Morell in view of Ikeda does not specifically teach: determining whether or not the position of the top of the head of the player estimated by the processing of estimating is abnormal, and correcting the position of the top of the head of the player in a case where the position of the top of the head of the player is abnormal.
However, in a related field, Lee teaches: determining whether or not the position of the top of the head of the player estimated by the processing of estimating is abnormal (¶ [0106] “at 1005, a determination may be made regarding whether a location or a position estimated for the one or more extremities may be valid... determine whether one or more of the locations or positions determined or estimated for the extremities such as the head, the shoulders, the hips, the hands, the feet, or the like may not have been accurate locations or positions for the actual extremities of the human target.”; Also see ¶¶ [0074] – [0076]), and
correcting the position of the top of the head of the player in a case where the position of the top of the head of the player is abnormal (¶ [0108] “…the target recognition, analysis, and tracking system may relax one or more body parts such as the joints j1-1j16 of the model based on a default location or position in a default pose at 1020. To relax one or more body parts of the model, the target recognition, analysis, and tracking system may adjust the one or more body parts to the default location or position such that that the one or more body parts may return to a neutral pose or default pose such as a T-pose, Di Vinci pose, a natural pose, or the like. Thus, in one embodiment, at 1010, the target recognition, analysis, and tracking system may adjust a body part such as the joint j9-j12 to default location or positions including default X-values, Y-values, and depth values for a left and right elbow and a left and right hand in a default pose when a location or a position may not have been estimated for the left and right elbow and the left and right hand associated with the human target.”; ¶ [0109] “…one or more body parts of the model may then be magnetized to a closest voxel associated with, for example, the human target. For example, in one embodiment, the target recognition, analysis, and tracking system may position the model over the human target in the grid of voxels, at 1025, such that the model may be imposed or overlaid on the human target. The target recognition, analysis, and tracking system may then magnetize or adjust the one or more body parts such as the joints j1-j16 of the model to a location or position of a voxel associated with the human target that may be closest to the default location or position of the one or more body parts”).
It would have been obvious to a PHOSITA before the effective filing date of the present invention to have modified Morrell in view of Ikeda to further determine whether the estimated top of the head position is abnormal and to correct the position when it is abnormal as taught by Lee because Lee teaches a known reliability improvement technique for image based human position estimation system, and modifying Morrell in view of Ikeda to include such technique would have predictable improved robustness and reduced erroneous head position estimates.
Allowable Subject Matter
Claims 2, 6, 8, 12, 14, and 18 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Relevant art not relied upon
Savvides (US 20180068414) teaches a3D-model-generating system 100 executes an estimation algorithm to compute an estimated camera projection matrix for the input 2D image.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WASSIM MAHROUKA whose telephone number is (571)272-2945. The examiner can normally be reached Monday-Thursday 8:00-5:00 EST.
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, Stephen 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.
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.
/WASSIM MAHROUKA/Primary Examiner, Art Unit 2665
Prosecution Insights