DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This Office Action is in response to the application filed on 03/25/2024.
3. The IDS filed on 12/10/2024 is considered and entered into the application file.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
4. Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kumar et al (US 20250238595 A1).
Kumar et al (“Kumar”) relates to systems, non-transitory computer-readable media, and methods for generating and visualization font variation instances of a variable font using deep-aware focal points in a font variation space.
As per claim 1, Kumar discloses a computer-implemented method (flowchart of Fig. 11) comprising:
receiving a first font file comprising data that represents one or more fonts and an initial set of font variation axes, each font variation axis indicative of a style for the one or more fonts and comprising a range of allowable values ([0025] The client device 108 communicates with the server(s) 104 and/or the content editing system 106 via network 112. For example, the client device 108 receives visualization data to display variable font visualizations (e.g., font transition animations) and provides information to server(s) 104 indicating font data for a variable font and/or user interactions for modifying a variable font. Also see [0027, 0030]);
receiving data representing one or more font variation parameters, wherein each font variation parameter relates to a first selected allowable value within the range of allowable values for a corresponding font variation axis of the set of font variation axes ([0075] As illustrated in FIG. 8, the font variation system 102 generates and provides a font variation interface 804 for display on a client device 802. Within the font variation interface 804, the font variation system 102 provides a font visualization window 806 and a font manipulation window 808. As shown, the pucker or dot within the font manipulation window 808 indicates a location in font variation space corresponding to the depicted font instance variation in the font visualization window 806).
identifying a portion of the first font file based at least on the one or more font variation parameters ([0022] In addition, certain embodiments of the font variation system provide improved flexibility over existing variable font systems. For instance, the font variation system provides font creation or generation tools that are more intuitive than those available in prior systems. Indeed, by generating primary and secondary focal points to represent font instances in a font variation space, the font variation system flexibly adapts variable fonts across various style axes (e.g., axes specific to respective font characteristics or parameters) in n-dimensional space, providing robust coverage of various styles and appearances. Also see [0041, 0065]);
generating a second font file comprising data that represents an updated set of font variation axes based at least on the portion of the first font file identified by the one or more font variation parameters ([0070] As shown in FIG. 6, the font variation system 102 thus generates a modified transition path 608. Indeed, the font variation system 102 generates the modified transition path 608 by identifying a candidate path with the shortest total distance based on the two-opt comparisons. Once the iterations are complete, the font variation system 102 selects the shortest path as the modified transition path 608. [0075] As the font variation system 102 receives data from the client device 802 indicating user interaction moving the handle, the font variation system 102 updates the font variation instance shown in the font visualization window 806 to coincide with the font metrics defined by the location of the handle in the font variation space (e.g., relative to the various axes or dimensions). Abstract, [0027] , [0038], [0058], [0076] , 0092]); and
initiating transmission of the second font file ([0027] As also illustrated in FIG. 1, the environment includes the server(s) 104. The server(s) 104 generates, tracks, stores, processes, receives, and transmits electronic data, such as font data, font visualizations, and data pertaining deep-aware focal points (e.g., primary focal points and secondary focal points). For example, the server(s) 104 receives data from the client device 108 in the form of interaction data requesting a modification to, or a visualization of, a variable font. In response, the server(s) 104 provides data to the client device 108 in the form of modified variable font data, including additional font instances or typefaces corresponding to deep-aware focal points and/or a graphical visualization of a variable font, such as a font transition animation playable at the client device 108. [0030, 0092] and , Fig. 11]).
As per claim 2, Kumar further discloses that the computer-implemented method of claim 1, wherein the data of the first font file represents a first design space parametrized by the initial set of font variation axes and the data of the second font file represents a second design space parametrized by the updated set of font variation axes ([0030] In one or more embodiments, the server(s) 104 includes all, or a portion of, the font variation system 102. For example, the font variation system 102 operates on the server(s) 104 to: i) implement a primary focal point algorithm 116 for determining primary focal points in a font variation space, ii) implement a secondary focal point algorithm 118 for determining secondary focal points in the font variation space, and/or iii) implement a transition path algorithm 120 for determining a transition path among font instances (or focal points) of a variable font. [0033] As mentioned, in one or more embodiments, the font variation system 102 generates and reorders font variation instances of a variable font. In particular, the font variation system 102 generates or extracts deep-aware focal points in a font variation space and reorders font instances of a variable font. FIG. 2 illustrates an example overview of generating and reordering font variation instances of a variable font in accordance with one or more embodiments. Additional detail regarding the various acts and aspects discussed in relation to FIG. 2 is provided thereafter with reference to subsequent figures. Also see [0035-0036, 0041, 0050, 0053], Figs. 2 and 4 ).
As per claim 3, Kumar further discloses that the computer-implemented method of claim 2, wherein the data of the second font file is renderable to present a graphical representation of the second design space ([0075] As illustrated in FIG. 8, the font variation system 102 generates and provides a font variation interface 804 for display on a client device 802. Within the font variation interface 804, the font variation system 102 provides a font visualization window 806 and a font manipulation window 808. As shown, the pucker or dot within the font manipulation window 808 indicates a location in font variation space corresponding to the depicted font instance variation in the font visualization window 806. As the font variation system 102 receives data from the client device 802 indicating user interaction moving the handle, the font variation system 102 updates the font variation instance shown in the font visualization window 806 to coincide with the font metrics defined by the location of the handle in the font variation space (e.g., relative to the various axes or dimensions). [0099] In addition, the series of acts 1100 includes an act of providing, for display on a client device, a graphical visualization of the modified set of font variation instances).
As per claim 4, Kumar further discloses that the computer-implemented method of claim 3, wherein the graphical representation comprises a default style center point and a radial line for each font variation axis in the updated set of font variation axes beginning at the default style center point, wherein a length of each radial line is indicative of the range of allowable values from the default style center point to a terminus representing the first selected allowable value for the corresponding font variation axis ([0062] The font variation system 102 initializes the radial basis function 508 at the normalized primary focal points 504 and applies the radial basis function 508 to the primary grid 506, assigning weights to each axis/dimension based on font metrics and metadata to emphasize and de-emphasize the various characteristics of the font. Using the radial basis function 508 scales well to higher dimensions where, as the dimensionality of the font variation space increases, the number of points required to represent the space does not grow exponentially as it might otherwise do with other methods. Also see ([0043] and Figs. 3-6, and 8).
As per claim 5, Kumar further discloses that the computer-implemented method of claim 4, wherein the graphical representation comprises a graphical representation of one or more glyphs at the terminus of each radial line corresponding with the first selected allowable value for the updated font variation axis ([0057] In these or other cases, the font variation system 102 determines a centroid based on a combination of font variation space axis values and font metrics, to capture intrinsic variation of a font design (as indicated by axis values on the font variation space) and observable characteristics of a font's glyphs (as quantified by the font metrics). Accordingly, the font variation system 102 determines a centroid of a font variation space by determining axis-specific values that flexibly adapt to both aspects font metrics and axis values. [0062] The font variation system 102 initializes the radial basis function 508 at the normalized primary focal points 504 and applies the radial basis function 508 to the primary grid 506, assigning weights to each axis/dimension based on font metrics and metadata to emphasize and de-emphasize the various characteristics of the font. Using the radial basis function 508 scales well to higher dimensions where, as the dimensionality of the font variation space increases, the number of points required to represent the space does not grow exponentially as it might otherwise do with other methods. also see Fig. 4, [0055-0056, 0058-0059]).
As per claim 6, Kumar further discloses that the computer-implemented method of claim 4, further comprising receiving data corresponding to one or more termini of each radial line, wherein the data comprises a selection of the one or more font variation parameters along each font variation axis ([0022] In addition, certain embodiments of the font variation system provide improved flexibility over existing variable font systems. For instance, the font variation system provides font creation or generation tools that are more intuitive than those available in prior systems. Indeed, by generating primary and secondary focal points to represent font instances in a font variation space, the font variation system flexibly adapts variable fonts across various style axes (e.g., axes specific to respective font characteristics or parameters) in n-dimensional space, providing robust coverage of various styles and appearances. Consequently, the font variation system also provides user interface tools for intuitively manipulating navigating among the various font instances that smoothly transition from one to the next without the visually jarring effects of prior systems. Also see [0035, 0041-0044]).
As per claim 7, Kumar further discloses that the computer-implemented method of claim 1, wherein identifying the portion of the first font file comprises, for each font variation parameter: truncating the range of allowable values of the corresponding font variation axis to generate an updated variation axis in accordance with the first selected allowable value of the font variation parameter ([0018] As also mentioned, in one or more embodiments, the font variation system determines a transition path among the typeface instances or font variations of a variable font. For instance, the font variation system determines a transition path by comparing distances between focal points in the font variation space and reordering the typeface instances/variations to reduce (e.g., minimize) a total distance or difference between them. In some cases, the font variation system further generates a font transition animation that visually depicts the changes in visual appearance of the variable font instances/typefaces defined by the transition path of focal points. [0025] The client device 108 communicates with the server(s) 104 and/or the content editing system 106 via network 112. For example, the client device 108 receives visualization data to display variable font visualizations (e.g., font transition animations) and provides information to server(s) 104 indicating font data for a variable font and/or user interactions for modifying a variable font. [0026] The client application 110 presents or displays information to a user, including variable font interfaces for editing, modifying, generating, animating, or visualizing variable fonts. [0043] In some cases, the primary focal point algorithm also involves rounding off to a standardized input axis value (if included as part of the input font data 302) for each of the primary focal points 304. Also see [0044], [0059]. Also see Figs. 3 and 5).
As per claim 8, Kumar further discloses that the computer-implemented method of claim 1, wherein the first font file is an open-type variable font file ([0035] In some embodiments, a variable font is a single digital font file that contains or includes multiple variations of its typeface, where different parameter values for various (axis-specific) characteristics, such as weight, width, and slant, impact its appearance. In some cases, the variations of a variable font are defined as axes within the font file, and the font variation system 102 varies the values along axes to change typeface appearance (where each axis has a minimum and maximum value as defined by the variable font file), allowing for more flexibility in design as well as smaller file sizes or storage requirements compared to systems that use multiple static font files (e.g., one for each typeface). [0050] As illustrated in FIG. 4, the font variation system 102 performs an act 402 to generate a primary focal point. To elaborate, the font variation system 102 generates a primary focal point by extracting a feature vector or an embedding from a font variation instance of a variable font).
As per claim 9, Kumar further discloses that the computer-implemented method of claim 1, further comprising: receiving a user-defined font variation axis; and adding the additional font variation axis to the initial set of font variation axes ([0037] Indeed, in some embodiments, primary focal points include plot points of vector representations or embeddings of known or predefined font instances (or embeddings extrapolated from predefined font embeddings) within a font variation space, as determined via a primary focal point algorithm. In these or other embodiments, a font variation space includes or refers to an n-dimensional embedding space that includes n axes representing respective font characteristics (e.g., weight, width, slant, etc.) of a variable font. Within a font variation space, in certain embodiments, secondary focal points include or refer to vector representations or embeddings of additional font variation instances generated from (or informed by) primary focal points, in accordance with a secondary focal point algorithm).
As per system claims 10-15, these system claims include similar limitations as that of method claims 1-4 and 6, respectively. Thus the system claims are also rejected under similar citations given to the method claims.
As per system claims 16-20, these storage medium claims include similar limitations as that of method claims 1, 2, 4, and 5, respectively. Thus the storage medium claims are also rejected under similar citations given the method claims.
Conclusion
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 10074042 B2 discloses Font recognition and similarity determination techniques and systems are described. In a first example, localization techniques are described to train a model using machine learning (e.g., a convolutional neural network) using training images. The model is then used to localize text in a subsequently received image, and may do so automatically and without user intervention, e.g., without specifying any of the edges of a bounding box. In a second example, a deep neural network is directly learned as an embedding function of a model that is usable to determine font similarity. In a third example, techniques are described that leverage attributes described in metadata associated with fonts as part of font recognition and similarity determination (Abstract).
6. Any inquiry concerning this communication or earlier communications from the examiner should be directed to TADESSE HAILU whose telephone number is (571)272-4051; and the email address is Tadesse.hailu@USPTO.GOV. The examiner can normally be reached Monday- Friday 9:30-5:30 (Eastern time).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bashore, William L. can be reached (571) 272-4088. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TADESSE HAILU/ Primary Examiner, Art Unit 2174