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 .
Response to Amendment
Applicant’s amendments and arguments filed on 7/22/2026 have been considered. Claim 1-33
are pending in the application. Examiner has acknowledged the cancellation of claims 1-13 and the newly added claims 14-33. Applicant’s amendments to the claims have overcome the claim objections, the 35 U.S.C Section 112(b) rejections, and the 35 U.S.C Section 101 rejection previously set forth in the Non-Final Office Action mailed on 4/22/2026.
Response to Arguments
Applicant’s arguments with respect to claim(s) 14-33 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Please see 35 U.S.C Section 103 Rejection below:
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) 14, 16-19, 24, 26, 28-31 and 33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al (Face to Face: Anthropometry-Based Interactive Face Shape Modeling Using Model Priors) and Arunachala et al (US 20230115028 A1), hereinafter Zhang and Arunachala respectively.
Regarding claim 33, Zhang teaches a system comprising: a processor; and a non-transitory computer readable medium storing a set of instructions, which when executed by the processor, configure the system to:
"Our system runs on a 2.8 GHz PC with 1 GB of RAM. Table 5 shows the time cost of different procedures. " – Pg 9, Par 4, Lines 1
NOTE: Zhang’s proposed system would require a processor and memory to store and execute the instructions for generating controllable face models.
generate, from an initial phenotype dataset of phenotypes, a face model,
"It takes 3D face scans as examples in order to exploit the variations presented in the real faces of individuals. The system automatically learns a model prior from the data-sets of example meshes of facial features using principal component analysis (PCA) and uses it to regulate the naturalness of synthesized faces" - Abstract, Lines 2-5
NOTE: Zhang further discloses the USF face database that contains face scans of 186 subjects with a mixture of gender, race, and age which can be understood as phenotypes, see Section 2, Par 1. This corresponds to an initial phenotype dataset. Zhang also describes a method for generating face models: "This paper presents a new anthropometrics-based method for generating realistic, controllable face models." - Abstract, Line 1
the face model comprising a measurement table and a plurality of interpolation functions for each customizable region of the face model;
"In this paper, 68 anthropometric measurements are chosen as shape control parameters. As an example, Table 1 lists the nasal measurements used in our work. The example models are placed in the standard posture for anthropometric measurements. In particular, the axial distances correspond to the x, y, and z axes of the world coordinate system. Such a systematic collection of anthropometric measurements is taken through all example models in the database to determine their locations in a multi-dimensional measurement space." – Pg 6, Section 5, Par 2
NOTE: Zhang discloses a table that records measurements of the face, specifically of the nose facial feature as recorded in Table 1. Zhang further discloses: "Finally, the output model with the desired feature shape is generated by evaluating the shape reconstruction model (7) at those eigenmesh coordinates. Note that there exist as many RBF-based interpolation functions as the number of eigenmeshes." - Section 6, Par 2, lines 13-15 and "For each facial feature, we compute a set of anthropometric measurements to parameterize the example meshes into a measurement space." - Abstract, Lines 7-9. This implies that multiple interpolation functions are performed for each selected facial features of the face models. This corresponds to a face model comprising a measurement table and a plurality of interpolation functions for each customizable region of the face model.
generate, using the face model,
"Using PCA coefficients as a compact shape representation, we formulate the face modeling problem in a scattered data interpolation framework which takes the user-specified anthropometric parameters as input. Solving the interpolation problem in a reduced subspace allows us to generate a natural face shape that satisfies the user-specified constraints. At runtime, the new face shape can be generated at an interactive rate." - Abstract, Lines 6-9
NOTE: Zhang discloses creating a new face shape that is updated at an interactive rate as the user provides user-specific parameters and constraints to modify the face model. This corresponds to generating an initial configuration of a face with a plurality of customizable regions.
adjust,
"We can alter the feature of the source model with a feature-adjustment step which coerces the anthropometric measurement vector to match that of the target feature of an example face. The new shape of the selected feature is reconstructed on the source model and can be further edited if needed." – Pg 13, Section 9.2 Par 2
NOTE: Zhang discloses using a feature adjustment step that modifies the parameters of a particular face region to match the target feature such as the input user specified parameter/constraints. Adjusting the face model will naturally modify the measurements in the measurement table corresponding to the customizable region.
and generate, from the measurement using an interpolation function in the plurality of interpolation functions corresponding to the customizable region, an adjusted configuration
"Using PCA coefficients as a compact shape representation, we formulate the face modeling problem in a scattered data interpolation framework which takes the user-specified anthropometric parameters as input. Solving the interpolation problem in a reduced subspace allows us to generate a natural face shape that satisfies the user-specified constraints." - Abstract, Lines 9-13
NOTE: Zhang discloses generating a new face shape that matches the input user-specified constraints using an interpolation function. This corresponds to using an interpolation function to generate an adjusted configuration of the face model.
Zhang still does not teach generate, using the face model, an initial configuration of a digital avatar, the initial configuration comprising a face with a plurality of customizable regions; display the initial configuration of the digital avatar on a display of an electronic device; receive, via an audio-visual user interface of the electronic device, an instruction to adjust a first customizable region of the plurality of customizable regions; adjust, according to the instruction, a measurement in the measurement table corresponding to the customizable region; and generate, from the measurement using an interpolation function in the plurality of interpolation functions corresponding to the customizable region, an adjusted configuration of the digital avatar. However, Arunachala teaches generate, using the face model, an initial configuration of a digital avatar, the initial configuration comprising a face with a plurality of customizable regions;
“An automatic avatar system can build a custom avatar with features extracted from one or more sources" - Abstract, Lines 1-2
NOTE: Arunachala discloses a system for generating a custom avatar and modifying selected facial features. This corresponds to an initial configuration of a digital avatar with customizable regions. After the combination, initial configuration of the digital avatar as taught by Arunachala can modify Zhang’s face model so that the generated face model can provide the appearance for the initial digital avatar.
display the initial configuration of the digital avatar on a display of an electronic device;
The processors 110 can communicate with a hardware controller for devices, such as for a display 130" - Par 28, Lines 4-5
NOTE: Arunachala discloses displaying the digital avatar on a display of an electronic device. One of ordinary skill would also find it obvious to present the digital avatar using the electronic display for the user to interact with..
receive, via an audio-visual user interface of the electronic device, an instruction to adjust a first customizable region of the plurality of customizable regions;
"The automatic avatar system can identify avatar features from a user-provided description of an avatar by applying natural language processing (NLP) models and techniques to a user-supplied textual description of one or more avatar features (e.g., supplied in textual form or spoken and then transcribed). " - Par 21, Lines 1-6
NOTE: Arunachala discloses a user-provided description of an avatar which can be supplied in text form or spoken form. One example includes: "As yet another example, a user can supply a natural language description of one or more avatar features (e.g., spoken or typed commands such as “put my avatar in a green hat”)," - Par 56 Lines 21-24. Arunachala also shows in Fig 10 a user interface that shows the digital avatar and the updates after the user instructions. After the combination, the concept of receiving spoken instructions by the audio-visual interface to modify a digital avatar as taught by Arunachala can modify Zhang’s face model generation system. This modification would allow the user to enter user-defined parameters/constraints for the face as a spoken instruction to then update the face model displayed on the audio-visual interface.
adjust, according to the instruction, a measurement in the measurement table corresponding to the customizable region;
"We can alter the feature of the source model with a feature-adjustment step which coerces the anthropometric measurement vector to match that of the target feature of an example face. The new shape of the selected feature is reconstructed on the source model and can be further edited if needed." – Zhang Section 9.2 Par 2, Lines 2-6
NOTE: After the combination, the concept of providing a spoken instruction to modify the digital avatar as taught by Arunachala can be added to Zhang’s system for generating a face model to modify facial regions using interpolation functions. This would allow the input user-defined parameters/constraints for modifying facial features to be spoken instructions
and generate, from the measurement using an interpolation function in the plurality of interpolation functions corresponding to the customizable region, an adjusted configuration of the digital avatar.
"Using PCA coefficients as a compact shape representation, we formulate the face modeling problem in a scattered data interpolation framework which takes the user-specified anthropometric parameters as input. Solving the interpolation problem in a reduced subspace allows us to generate a natural face shape that satisfies the user-specified constraints." – Zhang Abstract, Lines 9-13
NOTE: After the combination, the digital avatar as displayed in the audio-visual interface as taught by Arunachala can modify Zhang’s system for generating a face model to modify facial regions using interpolation functions. This will allow Zhang’s system to use interpolation functions based on spoken user-defined parameters/constraints to adjust the appearance of the face model representing the digital avatar.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to modify Zhang by incorporating the teachings of Arunachala to generate a digital avatar using the face model, displaying the digital avatar, receiving an instruction to adjust a first customizable region via an audio-visual user interface, adjusting a measurement in the measurement table corresponding to the customizable region, and generating an adjusted configuration of the digital avatar using an interpolation function corresponding to the customizable region. One would be motivated to make this combination since it would lead to the predicted result of a more intuitive and convenient mechanism for a user to specify desired facial feature modifications rather than directly manipulating facial parameters.
Regarding claim 14, the claim recites similar limitations to claim 33. Therefore, method claim 14 corresponds to the system disclosed in claim 33 and is rejected for the same reasons of obviousness as used above.
Regarding claim 26, the claim recites similar limitations to claim 33. Therefore, non-transitory computer-readable medium claim 26 corresponds to the system disclosed in claim 33 and is rejected for the same reasons of obviousness as used above.
Regarding claim 16, Zhang in view of Arunachala teaches the method of claim 16. Zhang as modified further teaches wherein each interpolation function in the plurality of interpolation functions comprises a radial basis function,
“Finally, the output model with the desired feature shape is generated by evaluating the shape reconstruction model (7) at those eigenmesh coordinates. Note that there exist as many RBF-based interpolation functions as the number of eigenmeshes” – Zhang Pg 6, Section 6, Par 2, Lines 19-23
NOTE: Zhang discloses “many RBF-based interpolation functions” which are used for the generation of face models according to user input parameter/constraints. The RBF-based interpolation functions refer to radial based interpolation functions (RBF). Zhang also discusses “radial basis function Ri(q)”, see Pg 6, Section 6, Par 2 Equation 10
the radial basis function generating a set of parameters corresponding to a deformation to an input measurement,
“With the input shape control thus parameterized, our goal is to generate a new deformation of the facial feature by computing the corresponding eigenmesh coordinates with control through the measurement parameters. Given an arbitrary input measurement vector q in the measurement space, such controlled deformation should interpolate the example models.” – Zhang Pg 6, Section 6, Par 2, lines 1-4
NOTE: Zhang discloses receiving an input measurement, evaluating the radial basis function at q and using the resulting radial basis function values to compute eigenmesh coordinates which describe the new deformation of the facial feature and then using the coordinates to generate an output facial model with the desired feature shape.
the set of parameters usable to generate an interpolated shape corresponding to the deformation.
“Given the input anthropometric control parameters, a novel output model with the desired shapes of facial features is obtained in runtime by blending the example models. Figure 7 illustrates this process. Our scheme first evaluates the predefined RBFs at the input measurement vector and then computes the eigenmesh coordinates by blending those of the example models with respect to the produced RBF values and pre-computed weight values.” – Zhang Pg 6, Section 6, Par 2, Lines 11-19
NOTE: Zhang discloses using the input user parameters to generate a facial model with the desired facial features using the radial basis interpolation function.
Regarding claim 28, the claim recites similar limitations to claim 16. Therefore, non-transitory computer-readable medium claim 28 corresponds to the method disclosed in claim 16 and is rejected for the same reasons of obviousness as used above.
Regarding claim 17, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified further teaches wherein each customizable region in the plurality of customizable regions characterized by one or more customizable region parameters.
“For each facial feature, we compute a set of anthropometric measurements to parameterize the example meshes into a measurement space” – Zhang, Abstract, Lines 5-6
NOTE: Zhang discloses that each facial feature is characterized by one or more measurements/parameters. The reference further discloses the goal of using user-defined constraints/parameters to generate the desired facial features.
Regarding claim 29, the claim recites similar limitations to claim 17. Therefore, non-transitory computer-readable medium claim 29 corresponds to the method disclosed in claim 17 and is rejected for the same reasons of obviousness as used above.
Regarding claim 18, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified further teaches wherein the initial configuration further comprises one or more customizable appearance parameters.
“Using PCA coefficients as a compact shape representation, we formulate the face modeling problem in a scattered data interpolation framework which takes the user-specified anthropometric parameters as input. Solving the interpolation problem in a reduced subspace allows us to generate a natural face shape that satisfies the user-specified constraints” – Zhang Abstract Lines 6-9
NOTE: Zhang teaches providing input user-specified constraints to an interpolation function to generate a new face that satisfies the user-specified parameters/constraints. Changing these parameters would obviously change the appearance of the generated face. This functionally corresponds to a configuration comprising customizable appearance parameters.
Regarding claim 30, the claim recites similar limitations to claim 18. Therefore, non-transitory computer-readable medium claim 30 corresponds to the method disclosed in claim 18 and is rejected for the same reasons of obviousness as used above.
Regarding claim 19, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified further teaches wherein the instruction to adjust the first customizable region of the plurality of customizable regions is received as speech input from a user via a microphone of the electronic device.
“Each input device 120 can include, for example, a mouse, a keyboard, a touchscreen, a touchpad, a wearable input device (e.g., a haptics glove, a bracelet, a ring, an earring, a necklace, a watch, etc.), a camera (or other light-based input device, e.g., an infrared sensor), a microphone, or other user input devices.” – Arunachala Par 27, Lines 6-11
NOTE: Arunachala discloses an input device 120 which can include the microphone. This microphone would naturally be used to provide the speech input for modifying the customizable regions. After the combination, the microphone used to input spoken instructions to adjust the appearance of the digital avatar as taught by Arunachala can modify Zhang’s system for generating face models from a phenotype dataset and modifying the appearance with user-specific parameter/constraints. This combination will allow the user to provide spoken instructions on how to adjust the face model according to the desired appearance.
Regarding claim 31, the claim recites similar limitations to claim 19. Therefore, non-transitory computer-readable medium claim 31 corresponds to the method disclosed in claim 19 and is rejected for the same reasons of obviousness as used above.
Regarding claim 24, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified further teaches displaying the adjusted configuration of the digital avatar on the display of the electronic device.
“If the user selects confirm button 1110, the automatic avatar system will update the avatar of the user to be wearing the baseball hat 1106.”- Par 77, Lines 15-17
NOTE: Arunachala describes confirming the desired adjustments to the avatar with the user and performing the update on the avatar. This adjusted configuration would obviously be displayed using display 130, see par 28. After the combination, the concept of displaying the adjusted configuration of the digital avatar as taught by Arunachala can modify Zhang’s system for generating a new face based on the user-specific parameter/constraints. This would allow the system to then receive the desired facial adjustments from the user and display the new face model representing the digital avatar using the display of an electronic device.
Claim(s) 15 and 27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang, Arunachala and Ward (Craniofacial Variability Index), hereinafter Ward respectively.
Regarding claim 15, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified teaches wherein the measurement table comprises a plurality of measurement vectors, each measurement vector in the plurality of measurement vectors comprising a plurality of facial measurements of the generated face model
“we obtain a set of examples of each facial feature with measured shape characteristics, each of them consisting of the same set of dimensions, where every dimension is an anthropometric measurement” – Zhang Pg 6, Section 6, Par 1, Lines 1-3
NOTE: Zhang discloses obtaining a set of examples from each facial feature (scanned faces from dataset) wherein each example has the same set of dimensions. Each dimension corresponds to a measurement, and these measurements are collected across the example models. For each example model, the measurements are represented by a measurement vector qi, see Section 6, Par 1, Lines 3-9. The measurement vector qi is then provided to the interpolation function to generate the desired shapes of facial features. The number of measurement vectors corresponds to the number of example models which implies a plurality of measurement vectors each comprising a plurality of facial measurements of the generated face model.
Zhang as modified still does not teach wherein the measurement table comprises a plurality of measurement vectors, each measurement vector in the plurality of measurement vectors comprising a plurality of facial measurements of the generated face model, each facial measurement expressed as a z-score. However, Ward teaches wherein the measurement table comprises
“Then the raw values for the selected variables (Table I) for each individual in the sample were converted to z-scores by subtracting each from the mean of its appropriate age and sex category and dividing by its appropriate standard deviation. The individual’s σz (variability index) was then calculated by obtaining the standard deviation of the average of the z-scores for the 16 variables” – Pg 4, Section: Statistical Analysis, Par 1
NOTE: Ward discloses obtaining head and face measurements and converting each measurement value to a standardized Z-score. After the combination, the calculation of the Z-score for each facial measurement as taught by Ward can modify Zhang’s system for generating a face model to be customized based on user input parameters/constraints. This combination would then allow Zhang’s system to perform the calculations to obtain the z-score for the recorded measurements from the measurement table corresponding to the face model.
Regarding claim 27, the claim recites similar limitations to claim 15. Therefore, non-transitory computer-readable medium claim 27 corresponds to the method disclosed in claim 15 and is rejected for the same reasons of obviousness as used above.
Claim(s) 20-22 and 32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang, Arunachala and German et al (US 20230222723 A1), hereinafter German respectively.
Regarding claim 20, Zhang in view of Arunachala teaches the method of claim 19. Zhang as modified does not teach providing, by the digital avatar via a speaker of the electronic device, speech output indicating a response to the instruction and simultaneously animating the digital avatar on the display of the electronic device consistently with the speech output. However, German teaches providing, by the digital avatar via a speaker of the electronic device, speech output indicating a response to the instruction
“For example, the natural language engine 45a may indicate an intent being a question about color, and the response may be the text 61 of “Would you like me to show you some color samples?” – Par 57, Lines 8-11
NOTE: German teaches a digital avatar that processes speech using natural language processing and providing an appropriate response. When a user requests a customization request, it is obvious that the natural language process will understand the user’s desires for customizing the digital avatar and respond in context of the conversation of avatar customization. This speech output comes from a speech file after being parsed through text-to-speech converter. This is then sent to a consumer computer which would have a speaker for the user to hear the response, see Par 65 and 66. After the combination, the concept of having a digital avatar provide a speech output indicating a customization response can be added to the face model digital avatar of Zhang as modified by Arunachala. This combination would then allow the face model to respond back with a speech output to indicate a customization response.
and simultaneously animating the digital avatar on the display of the electronic device consistently with the speech output.
In turn, the preprocessor computer 12e serves the speech files 91 to the browser 18 of the consumer computer 12d and uses the metadata of the lip synchronization signals and animation tags to provide rendering information to the browser 18 of the consumer computer 12d necessary to animate a rendering of the avatar figure 36 in time with the speech files 91” – Par 54
NOTE: After the combination, the concept of animating the lips of the digital avatar to synchronize with the speech output as taught by German can be added to Zhang as modified by Arunachala. This would allow for the lips of the face model to be animated during the speech output indicating a customization response.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to modify Zhang by incorporating the teachings of German to provide the digital avatar a speech output while simultaneously animating the digital avatar on the electronic device display to indicate the customization response. One would be motivated to make this combination to provide a more intuitive way for the user to interact with the digital avatar customization process. This would lead to the predicted result of a system that is easier to perform modifications to the face model without having to manually input the desired facial feature parameters/constraints.
Regarding claim 32, the claim recites similar limitations to claim 20. Therefore, non-transitory computer-readable medium claim 32 corresponds to the method disclosed in claim 20 and is rejected for the same reasons of obviousness as used above.
Regarding claim 21, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified does not teach receiving, from a user, a query for customization options of the digital avatar; and responding to the query with at least one customization option dependent on a state of a current customization session. However, German teaches receiving, from a user, a query for customization options of the digital avatar;
“For example, the natural language engine 45a may indicate an intent being a question about color, and the response may be the text 61 of “Would you like me to show you some color samples?” – German Par 57, Lines 8-11
NOTE: The example shown by German teaches a question sked by a user regarding color to which the context-aware response from the digital avatar addresses the question by asking the user if they would like to see options for different color samples. After the combination, the concept of providing the digital avatar a query for customization options can modify Zhang’s system as modified by Arunachala for generating face models to customize face regions based on user parameters/constraints. This combination would allow for a user to ask a query to the face model representing the digital avatar for customization options.
and responding to the query with at least one customization option dependent on a state of a current customization session.
“For example, the natural language engine 45a may indicate an intent being a question about color, and the response may be the text 61 of “Would you like me to show you some color samples?” – German Par 57, Lines 8-11
NOTE: The state of the current customization session could be interpreted as the speech input question regarding the customization of the digital avatar as taught by German. During a customization session, if the user asks for hair color options, the digital avatar’s natural language processor must process the current state of the conversation regarding avatar customization so that the response is tailored to addressing the user’s query for customization options. After the combination, the concept of responding to the user’s question with customization options dependent on the current state of the customization session as taught by German can be added to Zhang’s system as modified by Arunachala. This combination would then allow for the face model representing the digital avatar to process the user’s question regarding customization options and provide a response to address that desired customization.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to modify Zhang by incorporating the teachings of Zhang to receive a user query for customizing the digital avatar and having the response to the query be a customizable option dependent on the state of the current customization session. One would be motivated to make this combination to create an intuitive way for the user to design the avatar with their preferences without having to manually search for the customization option. This would also ensure that the responses to the user’s query are relevant to the desired customization asked by the user.
Regarding claim 22, Zhang in view of Arunachala and German teaches the method of claim 21. Zhang as modified further teaches wherein the instruction conforms to at least one customization option.
“In example 1100, the automatic avatar system has determined that the user has an upcoming event, which is a trigger for offering to update the user's avatar. Thus, the automatic avatar system provides notification 1102 with the option. In response, the user speaks phrase 1104 with a description of how to update her avatar, including to add a “baseball hat” to it. The automatic avatar system has transcribed this input, identified the “hat” avatar feature and the “baseball” characteristic for the hat, and has matched these to a hat 1106 from an avatar library. The automatic avatar system has also provided a notification 1108 to the user, informing her of an option to have her avatar updated to have the hat she requested” – Arunachala Par 77
NOTE: Arunachala discloses the user providing a request to customize the avatar by adding a baseball hat to the digital avatar. The system processes the request for adding a hat to the digital avatar and adds the specifically requested baseball hat to the digital avatar. After the combination, the concept of having the instruction conform to the customization option as taught by Arunachala can modify Zhang as modified. This combination would then allow a user input spoken instruction for updating the face model representing the digital avatar from the system’s response indicating the customization options after processing the user’s query for customization options.
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang, Arunachala and Rodrigues et al (3D Modelling and Recognition), hereinafter Rodrigues respectively.
Regarding claim 23, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified teaches wherein the measurement in the measurement table corresponding to the customizable region is selected from a range of acceptable measurement values,
“we obtain a set of examples of each facial feature with measured shape characteristics, each of them consisting of the same set of dimensions, where every dimension is an anthropometric measurement. The example measurements are normalized. Generally, we assume that an example model Fi of feature F has m dimensions, where each dimension is represented by a value in the interval (0,1]. A value of 1 corresponds to the maximum measurement value of the dimension.” – Pg 6, Section 6, Par 1
NOTE: Zhang discloses the collection of measurements from all of the example face models from the phenotype dataset, determining the measurement space, normalizing each measurement, and constraining the measurement values to a defined range of the interval (0.1]. Since the system receives an input measurement vector q in the measurement space, this implies that the selected input measurement vector q used to generate the facial feature is constrained to the measurement space defined in the measurement range.
Zhang still does not teach the range of acceptable measurement values determined using a covariance of a plurality of measurements in the initial phenotype dataset of phenotypes. However, Rodrigues teaches the range of acceptable measurement values determined using a covariance of a plurality of measurements in the initial phenotype dataset of phenotypes.
“Let x1, . . . , xp be our set of original variables (the 3D facial measurements) and let _i, i = 1, . . . , p be linear combination of these variables… The variance of ξ1 is var(ξi) = aT1 ξa1 where Σ is the covariance matrix of x.” – Pg 3, Section 4, Lines 26-29 and Equation 3
NOTE: Rodrigues discloses each face using 84 facial measurements (plurality of facial measurements) and represents this collection as variables x1-xp as the 3D facial measurements. Rodrigues further teaches calculating the variance of ξ1 where the formula includes Σ which is the covariance matrix of x (the 3D facial measurements). This functionally corresponds to a covariance of a plurality of facial measurements. After the combination, the concept of using a covariance of a plurality of measurements as taught by Rodrigues can modify Zhang’s range of acceptable facial measurements by using the concept of obtaining and applying covariance information to determine the range of acceptable measurement.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to modify Zhang by incorporating the teachings of Rodrigues to have the range of acceptable measurement values determined using a covariance of a plurality of measurements in the initial phenotype dataset of phenotypes. One would be motivated to make this combination to account for the statistical relationships and variation among the facial measurements when selecting measurement values, thereby generating of facial modifications representative of the dataset from which the example faces were obtained.
Claim(s) 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang, Arunachala and Tong et al (US 20210105438 A1), hereinafter Tong.
Regarding claim 25, Zhang in view of Arunachala teaches the method of claim 14. Zhang as modified does not teach animating the adjusted configuration of the digital avatar on the display of the electronic device. However, Tong teaches animating the adjusted configuration of the digital avatar on the display of the electronic device.
Avatar control module 214 is configured to determine an animation command based on a user input identifier (i.e., an identified user input). Animation command is configured to identify a desired avatar animation. For example, desired animations include changing a color of a displayed avatar's face, changing a size of a feature of the displayed avatar (e.g., making the nose larger)” – Par 38, Lines 1-8
NOTE: Tong teaches receiving user input for adjusting a facial feature for a digital avatar such as making a nose larger. This digital avatar is naturally displayed by an electronic device: “In one embodiment, displays 108 and 118 are configured to display avatars 110 and 120, respectively.”, see Par 21 Lines 24-25. Tong further discloses that the avatar is animated to reflect the user’s desired changes, see par 44 and 45. After the combination the concept of animating the adjusted configuration of the digital avatar on the display as taught by Tong can be added to Zhong’s system as modified. This will allow the user to provide a spoken instruction comprising user-specified parameters/constraints to modify the facial model representing the digital avatar. Then an animation that reflects the desired change is performed to visually present the newly adjusted face model configuration.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to modify Zhang by incorporating the teachings of Tong to animate the adjust configurations of the digital avatar on the display. One would be motivated to make this combination to visually show the user the modifications to the facial model that were requested.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, King Y Poon can be reached at 571-270-0728. 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.
/DAVID VAN NGUYEN/Examiner, Art Unit 2617 /KING Y POON/Supervisory Patent Examiner, Art Unit 2617
Prosecution Insights