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.
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 limitations 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: “an image acquisition module configured to acquire”, “a key frame extraction module configured to input”, “a face 3D reconstruction module configured to input”, “an eye 3D reconstruction module configured to select”, and “and a deviation angle measurement module configured to fix” in claim 8.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they 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 these limitations 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 limitations recite sufficient structure to perform the claimed function so as to avoid 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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, 4, 7-9, 12, 15-16, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Drozdov et al. (US 20240121377 A1), hereinafter referred to as Drozdov, in view of Yang et al. (“A digital mask to safeguard patient privacy”)hereinafter referred to as Yang, and in view of Berard et al. (“Practical Person-Specific Eye Rigging”), hereinafter referred to as Berard.
In regards to claim 1, Drozdov discloses a method for measuring a deviation angle of a gaze position based on three-dimensional (3D) reconstruction, comprising: acquiring video streaming information of a face of a testee, and obtaining a face image sequence of the testee based on the video streaming information (Paragraph 113, This discloses the use of a video capturing characteristics of the head such as a pose from video frames); inputting the face image sequence into a first neural network to obtain covering conditions of the face image sequence, and determining key frame images of the face image sequence based on the covering conditions (Paragraph 76, 65, and 45, The disclosure of each eye of each one of the viewers would mean that the covering conditions of each eye are implicitly covered with paragraph 65 covering obstructions to a person’s face and paragraph 45 covering multiple neural networks which implies a first neural network); inputting the key frame images into a second neural network to obtain feature point heat maps of the key frame images, and converting the feature point heat maps into facial feature point coordinates (Paragraph 114-115, 103, and 45, Paragraphs 114-115 disclose the usage of heat maps while paragraph 103 discloses the use of point coordinates with paragraph 45 disclosing multiple neural networks); constructing a 3D face model, obtaining a function between the facial feature point coordinates and projection coordinates of the 3D face model based on the facial feature point coordinates and the 3D face model, and obtaining a head pose corresponding to the facial feature point coordinates of the key frame images based on the function (Paragraph 103, Describes using an eyeball-face model which is within a BRI of 3d face model and the disclosure of the orientation and coordinates show that it includes the pose); selecting a reference gaze position image of a left eye and a reference gaze position image of a right eye from the key frame images to initialize an eyeball position, setting an eyeball rotation angle of a reference gaze position as a preset angle based on the head pose, and solving reference 3D coordinates of an eyeball in the reference gaze position images in a head coordinate system (Paragraph 69, Paragraph 69 states that the angles are narrowed due to the physical position of a person or the head pose); and fixing 3D coordinates of the eyeball in a to-be-measured image in the head coordinate system based on the reference 3D coordinates and solving an eyeball rotation angle in the to-be-measured image (Paragraph 72 and 106, Describes mapping the eyeball to a Cartesian coordinate system and 106 also specifies a head coordinate system that maps the eyeballs); and obtaining a deviation angle of a gaze position in the to-be-measured image based on the eyeball rotation angle in the to-be-measured image and the eyeball rotation angle of the reference gaze position (Paragraph 103, The described Corneal-eyeball deviation would fit within a BRI of a deviation angle) wherein the acquiring video streaming information of a face of a testee comprises: disposing a first visual target at a first preset distance and a second visual target at a second preset distance in front of the testee (Paragraph 63, covers a preset distance where it would not be acceptable for either a first or second target as there is a minimum distance and a maximum distance which reads on the preset distances) and the first visual target and the second visual target are in a straight line, and the camera is disposed coaxially with the first visual target and the second visual target (Paragraph 31 and Figure 2, the point of regard of the figure is within the same axis and a straight vertical line from the middle camera while the respective viewers are in a straight line and within the same axis as their respective cameras meaning that multiple targets are within a straight line of at least the central camera in the image and are within the same axis which would cover both coaxial and straight line).
However, Drozdov does not disclose an objective function; selecting a reference gaze position image of a left eye and a reference gaze position image of a right eye from the key frame images to initialize an eyeball position; and solving an eyeball rotation angle in the to-be-measured image and acquiring, through a camera, video streaming information of the testee gazing at the first visual target and the second visual target when the left eye is covered, the right eye is covered, both the left eye and the right eye are covered, and neither the left eye nor the right eye is covered.
Yang does disclose an objective function (Section entitled “face reconstruction”, describes the usage of an objective function for making 3d face landmarks correspond to 2d images) and solving an eyeball rotation angle in the to-be-measured image( section entitled “Eyeball reconstruction”, which shows that the eyeballs are reconstructed using the Euler angles of eyeball rotation and acquiring, through a camera, video streaming information of the testee gazing at the first visual target and the second visual target when the left eye is covered, the right eye is covered, both the left eye and the right eye are covered, and neither the left eye nor the right eye is covered (Page 1884, Second Column, first new Paragraph, The images are put into a first neural network along with a disclosure of using the cover test which would read on these covering conditions).
However, Yang does not disclose selecting a reference gaze position image of a left eye and a reference gaze position image of a right eye from the key frame images to initialize an eyeball position
Berard discloses selecting a reference gaze position image of a left eye and a reference gaze position image of a right eye from the key frame images to initialize an eyeball position (paragraph above 2.2, abstract, the Overview section on page 443, Figure 5, and section 4.3, the abstract shows that they use multi-view imagery for their reference images, section 4.3 and figure 5 show how that impacts the eye positioning, and the overview expresses similar ideas. Further, the paragraph above 2.2 shows that the implementation of the techniques included here would be of benefit to applications similar to the claimed invention).
It would have been prima facie obvious to combine the teachings of Yang, Berard, and Drozdov as it would lead to a predictable increase in accuracy for the method. Berard outlines explicitly that they believe the techniques they use would benefit the current art. Yang’s use of objective functions would similarly lead to predictable increases in accuracy as it would allow for optimization of the problem allowing for more accurate and efficient results. Therefore, it would have been prima facie obvious to combine the teachings of all three.
In regards to claim 4, wherein the fixing 3D coordinates of the eyeball in a to-be-measured image in the head coordinate system based on the reference 3D coordinates and solving an eyeball rotation angle in the to-be-measured image comprises: fixing the 3D coordinates of the eyeball in the to-be-measured image in the head coordinate system (Paragraph 72 and 106, Describes mapping the eyeball to a Cartesian coordinate system and 106 also specifies a head coordinate system that maps the eyeballs), constructing an objective function between an iris feature point and an iris model projection point, and solving the eyeball rotation angle in the to-be-measured image through iterative optimization (Paragraph 103, Describes the angle and orientation of the eyeball).
In regards to claim 7, wherein the covering condition of the face image sequence is one of the following conditions: the left eye is covered, the right eye is covered, both the left eye and the right eye are covered, and neither the left eye nor the right eye is covered (Page 1884, Second Column, first new Paragraph, the images are put into a first neural network along with a disclosure of using the cover test which would read on these covering conditions).
In regards to claim 8, it is similar to claim 1, and it is similarly rejected.
In regards to claim 9, Drozdov discloses a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to claim 1 (Paragraph 172, Describes multiple kinds of processor and memory to execute the program).
Claims 12 and 15 is similar to claim 9, and it is rejected similarly.
In regards to claim 16, Drozdov discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, implements the steps of the method according to claim 1 (Paragraph 172, Describes multiple kinds of storage medium and processors).
In regards to claim 19, it is similar to claim 16.
Claims 12 and 15 is similar to claim 9, and it is rejected similarly.
Claims 2, 10, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Drozdov et al. (US 20240121377 A1), hereinafter referred to as Drozdov, in view of Yang et al. (“A digital mask to safeguard patient privacy”)hereinafter referred to as Yang, and in view of Berard et al. (“Practical Person-Specific Eye Rigging”), hereinafter referred to as Berard, as applied to claims 1, 4, 7-9, 12, 15-16, and 19 and further in view of Wu et al. (US 20230143034 A1), hereinafter referred to as Wu.
In regards to claim 2, Drozdov does not disclose the limitations of this claim.
However, Wu does disclose before the inputting the face image sequence into a first neural network to obtain covering conditions of the face image sequence, further comprising: training the first neural network, which specifically comprises: constructing an initial first neural network, acquiring a face image sequence, and labeling real covering conditions of the face image sequence (Paragraph 56, Describes the usage of labeling to cover objects in a 2d frame); and sequentially inputting each image in the face image sequence as a training image into the initial first neural network to obtain a predicted covering condition of the training image, constructing a cross-entropy loss function based on the predicted covering condition and a corresponding real covering condition (Paragraph 145, Describes using an entropy loss function to account for errors), and performing supervised training on the initial first neural network based on the cross-entropy loss function to obtain a trained neural network as the first neural network (Paragraphs 145 and 146, Further specifies that the training is done to reduce the loss shown in paragraph 145).
It would have been prima facie obvious to combine the teachings of Wu and Drozdov as it combines known methods which led to predictable results. The usage of a loss function to find the error is known in the art, and the benefits that it provides during a supervised training is a predictable decrease in the error rate as the training can be adjusted. As such, the usage of this and other methods led to a predictable increase in the overall accuracy of the training as well. As such, it is prima facie obvious to combine the teachings of both disclosures.
Claim 10 is similar to claim 9, and it is rejected similarly.
Claim 17 is similar to claim 16, and it is rejected similarly.
Claims 3, 11, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Drozdov et al. (US 20240121377 A1), hereinafter referred to as Drozdov, in view of Yang et al. (“A digital mask to safeguard patient privacy”)hereinafter referred to as Yang, and in view of Berard et al. (“Practical Person-Specific Eye Rigging”), hereinafter referred to as Berard, as applied to claims 1, 4, 7-9, 12, 15-16, and 19 and further in view of Qi et al. (“Application of face recognition in port unrestricted scene”), hereinafter referred to as Qi.
In regards to claim 3, Drozdov does not disclose the limitations of this claim.
However, Qi does disclose before the inputting the key frame images into a second neural network to obtain feature point heat maps of the key frame images, further comprising: training the second neural network, which specifically comprises (Under Face training Module, Discloses the training of neural networks): constructing an initial second neural network, obtaining a face image from a public dataset, labeling real feature point coordinates on the face image, and converting the real feature point coordinates into a real feature point heat map (Abstract and section B. Face preprocessing, describes the use of coordinates and heat maps here); and inputting the face image into the initial second neural network to obtain a predicted feature point heat map of the face image, constructing an L1 loss function based on the real feature point heat map and the predicted feature point heat map (Abstract and section B. Face preprocessing, Describes the usage of L1 loss function as a way to find errors in the map), and performing supervised training on the initial second neural network based on the L1 loss function until the L I loss function converges to obtain a trained initial second neural network as the second neural network (Section D. Face Recognition, States that training supervision takes place after the preprocessing which included the previous steps).
It would have been prima facie obvious to combine the teachings of Qi and Drozdov as it combines known methods which led to predictable results. The usage of a loss function to find the error is known in the art, and the benefits that it provides during a supervised training is a predictable decrease in the error rate as the training can be adjusted. As such, the usage of this and other methods led to a predictable increase in the overall accuracy of the training as well. As such, it is prima facie obvious to combine the teachings of both disclosures.
Claim 11 is similar to claim 9, and it is rejected similarly.
Claim 18 is similar to claim 16, and it is rejected similarly.
Claims 5, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Drozdov et al. (US 20240121377 A1), hereinafter referred to as Drozdov, in view of Yang et al. (“A digital mask to safeguard patient privacy”)hereinafter referred to as Yang, and in view of Berard et al. (“Practical Person-Specific Eye Rigging”), hereinafter referred to as Berard, as applied to claims 1, 4, 7-9, 12, 15-16, and 19 and further in view of Lu et al. (US 20190204439 A1), hereinafter referred to as Lu.
In regards to claim 5, Drozdov does not disclose wherein the eyeball rotation angle of the reference gaze position is set as the preset angle, and the preset angle is set to 0 degrees.
Lu does disclose wherein the eyeball rotation angle of the reference gaze position is set as the preset angle, and the preset angle is set to 0 degrees (Paragraph 70, States that the preset angle can be 0 degrees between the mobile device recording their eye position).
It would have been prima facie obvious to combine the teachings of Lu and Drozdov as it is simple substitution. The preset angle is changed from a person’s gaze at a mobile device to the eyeball rotation of a model. This is the known angle of looking in front of you, and as such one could easily make the eyeball in the model match the angle of directly in front of the eye. As such, it is prima facie obvious to combine these disclosures.
Claim 13 is similar to claim 9, and it is rejected similarly.
Claim 20 is similar to claim 16, and it is rejected similarly.
Response to Amendment
The amendments submitted 10/12/2025 have been admitted. They have overcome all grounds for the 35 U.S.C. 101 rejections, and they have been withdrawn.
Response to Arguments
Applicant's arguments filed 10/12/2025 have been fully considered but they are not persuasive.
In regards to the 103 arguments, the first claimed technical feature that Drozdov is alleged to not disclose is “acquiring video streaming information of a face of a testee, and obtaining a face image sequence of the testee based on the video streaming information”. The claim language does not require that the viewer or testee to be restrained, and it makes no mentions of any restraints being applied to the individual. If such a limitation was to be included within the claims themselves, then this point would be more persuasive. Similarly, the second objection is that Drozdov focuses on acquiring the gaze of the viewer, and this is true. However, all the claim requires to read upon it is that the face image sequence is obtained from the face of a testee. There is no exclusionary language in the claim language that would exclude the pose of a user, and even with such language, the cited paragraph still describes the disclosure of finding “facial-eye landmarks” which would read upon this claim language still.
For the second feature, “disposing a first visual target at a first preset distance and a second visual target at a second preset distance in front of the testee, and acquiring,” , the 3d projections disclosed within paragraph 63 are analogous to the claimed visual targets, and the further minimum and maximum distance disclosed to see these objects would read upon the fixed positions disclosed within the claim. Further, this section does not state that the viewer’s head or pose must be fixed.
For the last disclosed technical feature, “and the first visual target and the second visual target are in a straight line, and the camera is disposed coaxially with the first visual target and the second visual target”, this statement merely requires that the target are organized in a straight line and share at least one axis, as such, a disclosure or showing that a camera can be positioned directly in front of multiple targets that are in a straight line and share an axis. Drozdov’s figure 2 depicts the 3d object and the viewer directly in front of the central camera in the image which would constitute a straight line. Further, they all would share the same x-axis as they are all positioned in front of each other. As such, it would be enough to read upon the claim language.
As such, all arguments are considered unpersuasive by the examiner.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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CONOR AIDAN. O'MALLEY
Examiner
Art Unit 2675
/CONOR A O'MALLEY/ Examiner, Art Unit 2675
/ANDREW M MOYER/ Supervisory Patent Examiner, Art Unit 2675
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