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 .
Claims 1-20 are present for examination.
Claim Interpretation
The term “scalar vector graphics” has been used throughout the disclosure. Specification, para. [0016], discloses scalar vector graphics (SVG) and para. [0052] discloses a scalar vector graphics (SVG) image includes an SVG digital image made up of vector graphics, and an SVG image can include one or more points, lines, shapes, or curves defined by vector graphics. Para. [0053] discloses an SVG object includes an object portrayed in an SVG image, and an SVG object can include an object in which the shape, colors, dimensions, boundaries, and/or other visible attributes of the object are defined by vector graphics. It appears that an SVG object and/or an SVG image are defined or made up of vector graphics, and there are no special meanings for the term “scalar” in the scalar vector graphics in this application. Therefore, the scalar vector graphics (SVG) in this application has been interpreted as vector graphics.
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, 4, 9, 17, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Publication No. 20260065546 A1 to Karuppasamy et al. in view of US Patent Publication No. 20190122333 A1 to Baron et al.
Regarding claim 1, Karuppasamy discloses A method (Karuppasamy, Abstract) comprising:
receiving, from a client device, a data file and a raster image depicting at least one raster object within a scene (Karuppasamy, FIG. 2, showing receiving input raster image, para. [0046], disclosing receiving a first image in a raster format, known as a raster image, the raster image can be a sketch, a photograph, a video frame, or any other type of raster image, and preprocessing the raster image to form a second image, para. [0053], disclosing receiving the preprocessed image and further generate images with enhanced objects in the image and generating a graph schema representing the objects, relationships between individual ones of the objects, and a context of use of the objects);
generating, from the at least one raster object of the raster image, at least one scalar vector graphic object (Karuppasamy, para. [0069], disclosing determining image attributes of the identified objects based on the graph schema, para. [0070], disclosing generating vector images of the object in the raster image by generating an individual vector image for each of the objects);
generating a scalar vector graphic image depicting the at least one scalar vector graphic object within the scene based on the at least one scalar vector graphic object (Karuppasamy, para. [0082], disclosing providing an individual vector image for each of the objects, para. [0083], disclosing the vector images are recombined into a scalable image operable under modern software, such as CAD, the individual objects can be manipulated, enlarged, removed, etc. within the seventy image as desired).
However, Karuppasamy does not expressly disclose receiving, from a client device, a data file; binding the at least one scalar vector graphic object to data from the data file; generating a scalar vector graphic image depicting the at least one scalar vector graphic object within the scene based on the data bound to the at least one scalar vector graphic object; and providing the scalar vector graphic image for display on a graphical user interface.
On the other hand, Baron discloses receiving, from a client device, a data file (Baron, para. [0027], disclosing the processing server may include a receiving device configured to receive data from computing devices, para. [0033], disclosing the processing server may include a parsing module configured to receive data as input, the parsing module may be supplied a data file received by the receiving device as input and may parse the data file to identify the plurality of dimensional data sets included therein); binding the at least one scalar vector graphic object to data from the data file (Baron, para. [0033], disclosing the data file can include information such as dimensions, colors, or aspect ratios of the image files or other data associated with design rules for the vector images to be generated, para. [0034], disclosing generating new vector images, modifying existing vector images, and processing images to generate a vector image from one or more base images that has a specified length and height corresponding to a dimensional data set parsed from the received data file, indicating the dimensional data from the data file can be bound to the existing vector images as the at least one scalar vector graphic object); generating a scalar vector graphic image depicting the at least one scalar vector graphic object within the scene based on the data bound to the at least one scalar vector graphic object (Baron, para. [0033], disclosing the data file can include information such as dimensions, colors, or aspect ratios of the image files or other data associated with design rules for the vector images to be generated, para. [0034], disclosing generating new vector images, modifying existing vector images, and processing images to generate a vector image from one or more base images that has a specified length and height corresponding to a dimensional data set parsed from the received data file, indicating the modified existing vector images can correspond to a scalar vector graphic image depicting the existing vector images as the at least one scalar vector graphic object within the scene based on the dimensional data as the data bound to the at least one scalar vector graphic object); and providing the scalar vector graphic image for display on a graphical user interface (Baron, para. [0049], disclosing the generated vector graphics image files may be displayed on a web page).
Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy and Baron. The suggestion/motivation would have been to provide a plurality of customized vector graphics via an automated process that can accommodate the needs of webpages and other graphical design implementations without requiring the image provider to do any more than supplying the base vector graphic, as suggested by Baron (see Baron, para. [0005]).
Regarding claim 4, Karuppasamy in view of Baron discloses the method of claim 1, further comprising generating, from the raster image, a cropped image for a raster object from the at least one raster object (Karuppasamy, FIGs. 4A and 4F, showing a cropped image for a raster object from the at least one raster object is generated from the raster image, para. [0057], disclosing borders are added to objects of the third image based on the fourth image to achieve a desired size or aspect ratio, the features can be extracted, para. [0059], disclosing the sixth image illustrated in FIG. 4F), wherein generating the at least one scalar vector graphic object from the at least one raster object comprises generating a scalar vector graphic object using the cropped image of the raster object (Karuppasamy, para. [0070], disclosing generating the vector images of the objects in the raster image by ungrouping the sixth image based on the identified edges of the objects, thereby generating an individual vector image for each of the objects).
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Regarding claim 9, Karuppasamy in view of Baron discloses the method of claim 1, wherein binding the at least one scalar vector graphic object to the data from the data file comprises binding the at least one scalar vector graphic object to the data in accordance with user input received from the client device (Baron, para. [0018], disclosing the computing device may submit the data file to the processing server and the data file comprising a request for a plurality of vector images, para. [0024], disclosing the computing device may be operated by an entity that they want to include in the vector images generated by the processing server, the data file submitted by the computing device may include or be accompanied by an image file, para. [0033], disclosing receiving the data file as input, the data file can include information such as dimensions, colors, or aspect ratios of the image files or other data associated with design rules for the vector images to be generated, para. [0034], disclosing generating new vector images, modifying existing vector images, and processing images to generate a vector image from one or more base images that has a specified length and height corresponding to a dimensional data set parsed from the received data file, indicating the dimensional data from the data file can be bound to the existing vector images as the at least one scalar vector graphic object based on the input from the entity operating the computing device as user input). Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy and Baron. The suggestion/motivation would have been to provide a plurality of customized vector graphics via an automated process that can accommodate the needs of webpages and other graphical design implementations without requiring the image provider to do any more than supplying the base vector graphic, as suggested by Baron (see Baron, para. [0005]).
Regarding claim 17, it recites similar limitations of claim 1 but in a non-transitory computer-readable medium form. The rationale of claim 1 rejection is applied to reject claim 17. In addition, Karuppasamy discloses a non-transitory computer-readable medium (Karuppasamy, para. [0044], disclosing computer-readable instructions stored in the memory).
Regarding claim 18, Karuppasamy in view of Baron discloses the non-transitory computer-readable medium of claim 17, wherein binding the at least one scalar vector graphic object to the data from the data file comprises: generating, from a data field of the data, a scaled data field having a value within a range supported by a corresponding scalar vector graphic property (Baron, para. [0033], disclosing the parsing module may receive data as input, parse the received data to identify data included therein, output the resulting data, the parsing module may be supplied a data file, parse the data file to identify the plurality of dimensional data sets included therein, may parse additional data from the received data file such as dimensions, colors, or aspect ratios of the image files, or other data associated with design rules specified for the vector images to be generated, para. [0034], disclosing generating vector images having a specified length and height corresponding to the dimensional data set parsed from the received data file, indicating the dimensional data sets can correspond to the data field of the data, and one dimensional data set can correspond to a scaled data field having a value within a range supported by a corresponding scalar vector graphic property (i.e., length, height, etc. of the vector image to be generated that is within a range supported by the corresponding dimension as the scalar vector graphic property)); and binding the at least one scalar vector graphic object to the scaled data field (Baron, para. [0034], disclosing generating vector images having a specified length and height corresponding to the dimensional data set parsed from the received data file, indicating the vector image to be generated can correspond to the at least one scalar vector graphic object bound to the length and height as the scaled data field). Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy and Baron. The suggestion/motivation would have been to provide a plurality of customized vector graphics via an automated process that can accommodate the needs of webpages and other graphical design implementations without requiring the image provider to do any more than supplying the base vector graphic, as suggested by Baron (see Baron, para. [0005]).
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karuppasamy in view of Baron as applied to claim 1 above, and further in view of US Patent Publication No. 20170032492 A1 to Block et al.
Regarding claim 2, Karuppasamy in view of Baron discloses the method of claim 1. However, Karuppasamy or Baron does not expressly disclose wherein generating the scalar vector graphic image depicting the at least one scalar vector graphic object based on the data bound to the at least one scalar vector graphic object comprises generating an animated scalar vector graphic image depicting an animation of the at least one scalar vector graphic object within the scene based on one or more animation attributes included in the data bound to the at least one scalar vector graphic object.
On the other hand, Block discloses generating an animated scalar vector graphic image depicting an animation of the at least one scalar vector graphic object within the scene based on one or more animation attributes included in the data bound to the at least one scalar vector graphic object (Block, para. [0014], disclosing retrieving animation templates and applying the animation templates to a basic graphic character in order to display animations of the basic graphic character, performing an animation section that upon selection of one of the animation templates, applying the selected animation template to the scaled vector graphic character, and display an animation of the scaled two dimensional character based on the selected animation template, indicating the animation of the scaled vector graphic character can correspond to an animation scalar vector graphic image depicting an animation of the scalar vector graphic object within the scene based on the animation templates as one or more animation attributes included in the data bound to the scaled vector graphic character as the at least one scalar vector graphic object).
Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy in view of Baron with Block. The suggestion/motivation would have been to provide parametric generation of custom scalable animated characters on the Web, as suggested by Block (see Block, para. [0010]).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Karuppasamy, Baron, and Block as applied to claim 2 above, and further in view of US Patent Publication No. 20090288012 A1 to Hertel et al.
Regarding claim 3, the combination of Karuppasamy, Baron, and Block discloses the method of claim 2. However, Karuppasamy, Baron, or Block does not expressly disclose wherein generating the animated scalar vector graphic image depicting the animation of the at least one scalar vector graphic object comprises generating the animated scalar vector graphic image depicting a motion-path animation of the at least one scalar vector graphic object.
On the other hand, Hertel discloses generating the animated scalar vector graphic image depicting a motion-path animation of the at least one scalar vector graphic object (Hertel, para. [0331], disclosing defining the skin as a vector graphic and defining motion paths for the various vector graphics to animate the skin, indicating the skin can correspond to the at least one scalar vector graphic object and animating the skin can correspond to generating the animated scalar vector graphic image depicting a motion-path animation of the skin as the at least one scalar vector graphic object).
Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy, Baron, and Block with Hertel. The suggestion/motivation would have been to provide customized look of digital objects, as suggested by Hertel (see Hertel, para. [0331]).
Claim(s) 10, 11, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karuppasamy in view of Block.
Regarding claim 10, Karuppasamy discloses A system comprising: one or more memory components (Karuppasamy, para. [0044], disclosing memory 206); and one or more processing devices coupled to the one or more memory components (Karuppasamy, para. [0044], disclosing the processor 204 may be programmed to cooperate with computer-readable instructions stored in the memory 206 (also referred to be as computer-readable medium) for performing operations according to the present disclosure), the one or more processing devices to perform operations comprising:
determining, using an object detection model, a raster object depicted within a scene of a raster image (Karuppasamy, para. [0046], disclosing receiving a raster image, para. [0057], disclosing the edge extracting module extracts a set of features from the image, para. [00558], disclosing the edge extracting module performs the relation, event, and object extraction);
generating, from the raster object of the raster image, a scalar vector graphic object (Karuppasamy, para. [0070], disclosing generating the vector images of the objects in the raster image by ungrouping to generate an individual vector image for each of the objects).
However, Karuppasamy does not expressly disclose binding the scalar vector graphic object to data from a data file, the data comprising one or more animation attributes; and generating an animated scalar vector graphic image depicting an animation of the scalar vector graphic object within the scene based on the one or more animation attributes bound to the scalar vector graphic object.
On the other hand, Block discloses binding the scalar vector graphic object to data from a data file, the data comprising one or more animation attributes (Block, para. [0014], disclosing retrieving animation templates and applying the animation templates to a basic graphic character in order to display animations of the basic graphic character, performing an animation section that upon selection of one of the animation templates, applying the selected animation template to the scaled vector graphic character, indicating the animation templates can correspond to data from data file and the data comprising animation templates as one or more animation attributes); and generating an animated scalar vector graphic image depicting an animation of the scalar vector graphic object within the scene based on the one or more animation attributes bound to the scalar vector graphic object (Block, para. [0014], disclosing retrieving animation templates and applying the animation templates to a basic graphic character in order to display animations of the basic graphic character, performing an animation section that upon selection of one of the animation templates, applying the selected animation template to the scaled vector graphic character, and display an animation of the scaled two dimensional character based on the selected animation template, indicating the animation of the scaled vector graphic character can correspond to an animated scalar vector graphic image depicting an animation of the scalar vector graphic object within the scene based on the animation templates as the one or more animation attributes bound to the scalar vector graphic object).
Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy with Block. The suggestion/motivation would have been to provide parametric generation of custom scalable animated characters on the Web, as suggested by Block (see Block, para. [0010]).
Regarding claim 11, Karuppasamy in view of Block discloses the system of claim 10, wherein binding the scalar vector graphic object to the data comprising the one or more animation attributes comprises binding the scalar vector graphic object to the data comprising one or more in-situ animation attributes (Block, para. [0014], disclosing retrieving animation templates and applying the animation templates to a basic graphic character in order to display animations of the basic graphic character, performing an animation section that upon selection of one of the animation templates, applying the selected animation template to the scaled vector graphic character, para. [0084], disclosing animation data format including properties such as position, rotation, and scale, para. [0159], disclosing creating animation specification, indicating the animation template with animation object include in-situ animation attributes such as rotation and scale). Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy with Block. The suggestion/motivation would have been to provide parametric generation of custom scalable animated characters on the Web, as suggested by Block (see Block, para. [0010]).
Regarding claim 16, Karuppasamy in view of Block discloses the system of claim 10, wherein generating the animated scalar vector graphic image comprises generating an animated scalar vector graphic pictorial poster (Block, para. [0014], disclosing applying the animation template to the scaled vector graphic character and displaying in the display device an animation of the scaled two dimensional character based on the animation template, indicating applying the animation template to the scaled vector graphic character can generate the animated scalar vector graphic pictorial poster that can be displayed in the display device). Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy with Block. The suggestion/motivation would have been to provide parametric generation of custom scalable animated characters on the Web, as suggested by Block (see Block, para. [0010]).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karuppasamy in view of Block as applied to claim 10 above, and further in view of US Patent Publication No. 20080252723 A1 to Park.
Regarding claim 12, Karuppasamy in view of Block discloses the system of claim 10, wherein: the operations further comprise: generating a cropped image of the raster object using the raster image (Karuppasamy, FIGs. 4A and 4F, showing a cropped image for a raster object from the at least one raster object is generated from the raster image, para. [0057], disclosing borders are added to objects of the third image based on the fourth image to achieve a desired size or aspect ratio, the features can be extracted, para. [0059], disclosing the sixth image illustrated in FIG. 4F).
However, Karuppasamy or Block does not expressly disclose removing a background of the cropped image; and generating the scalar vector graphic object from the raster object comprises generating the scalar vector graphic object from the cropped image of the raster object with the background removed.
On the other hand, Park discloses removing a background of the image (Park, para. [0075], disclosing background may be removed from the video prior to the analysis); and generating the scalar vector graphic object from the raster object comprises generating the scalar vector graphic object from the image of the raster object with the background removed (Park, para. [0075], disclosing background may be removed from the video prior to the analysis, para. [0176], disclosing after video analysis, a scalable vector graphics (SVG) component is generated and output from the video analysis module, indicating the SVG component is generated from the image of the raster object with the background removed because the background removal can be prior to the analysis and the SVG component is generated after the analysis). Because Karuppasamy discloses cropping images, combining Karuppasamy in view of Block with Park could remove the background from the cropped image and generating the SVG object from the cropped image of the raster object with the background removed.
Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy in view of Block with Park. The suggestion/motivation would have been to allow a client to draw an outline around (or draw the edges of) detected video elements, as suggested by Park (see Park, para. [0176]).
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karuppasamy in view of Block as applied to claim 10 above, and further in view of Baron.
Regarding claim 13, Karuppasamy in view of Block discloses the system of claim 10, wherein: the operations further comprise generating, using a language machine learning model, a label and a textual description for the raster object depicted in the raster image (Karuppasamy, para. [0059], disclosing performing the entity extraction, recognition, and linking for creating the sixth image by highlighting the objects in the fifth object based on the associated features and its relationships and a layering of the objects determined within the fifth image, para. [0060], disclosing the nested deep level profiling and schema indexing may be performed on the sixth image based on the features, the objects, the knowledge graph and the relationships using the nested profiling knowledge graphs models, and the nested deep level profiling and schema indexing may involve entity alignment, taxonomy formation and find the profiling, nested relationships identification, and context identification, para. [0067], disclosing performing semantic search, indicating the edge detection module can correspond to a language machine learning model to generate entity alignment, taxonomy formation about the objects as a label and a textual description for the raster object depicted in the raster image).
However, Karuppasamy or Block does not expressly disclose binding the scalar vector graphic object to the data from the data file comprises binding the scalar vector graphic object to the data using the label and the textual description for the raster object.
On the other hand, Baron discloses binding the scalar vector graphic object to the data from the data file comprises binding the scalar vector graphic object to the data using the label and the textual description for the raster object (Baron, para. [0027], disclosing the processing server may include a receiving device configured to receive data from computing devices, para. [0033], disclosing the processing server may include a parsing module configured to receive data as input, the parsing module may be supplied a data file received by the receiving device as input and may parse the data file to identify the plurality of dimensional data sets included therein, the data file can include information such as dimensions, colors, or aspect ratios of the image files or other data associated with design rules for the vector images to be generated, para. [0034], disclosing generating new vector images, modifying existing vector images, and processing images to generate a vector image from one or more base images that has a specified length and height corresponding to a dimensional data set parsed from the received data file. Because Karuppasamy discloses generate entity alignment, taxonomy formation about the objects, which can correspond to the label and the textual description for the raster object, combining Karuppasamy in view of Block with Baron could bind the data including the respective dimensions, colors, and aspect ratios of the objects in the image with the corresponding scalar vector graphic object).
Before the invention was effectively filed, it would have been obvious for a person skilled in the art to combine Karuppasamy in view of Block with Baron. The suggestion/motivation would have been to provide a plurality of customized vector graphics via an automated process that can accommodate the needs of webpages and other graphical design implementations without requiring the image provider to do any more than supplying the base vector graphic, as suggested by Baron (see Baron, para. [0005]).
Allowable Subject Matter
Claim(s) 5-8, 14, 15, 19, and 20 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 5, Karuppasamy in view of Baron discloses the method of claim 4. However, Karuppasamy, Baron, or any other prior art references on the record, alone or in combination, fails to disclose further comprising generating, from the raster image, a plurality of quantized bitmaps for the raster object using the cropped image for the raster object, wherein generating the scalar vector graphic object using the cropped image of the raster object comprises generating the scalar vector graphic object using the plurality of quantized bitmaps for the raster object.
Claim 6 depends from claim 5 with additional limitations.
Regarding claim 7, Karuppasamy, Baron, or any other prior art references on the record, alone or in combination, fails to disclose wherein binding the at least one scalar vector graphic object to the data from the data file comprises: determining one or more scalar vector graphic properties for the at least one scalar vector graphic object; generating a first set of embeddings for the one or more scalar vector graphic properties; generating a second set of embeddings for the data from the data file; and binding the at least one scalar vector graphic object to the data from the data file using the first set of embeddings and the second set of embeddings.
Claim 8 depends from claim 7 with additional limitations.
Regarding claim 14, Karuppasamy, Block, Baron, or any other prior art references on the record, alone or in combination, fails to disclose wherein binding the scalar vector graphic object to the data using the label and textual description for the raster object comprises: generating, using a sentence transformer neural network, a first set of embeddings for the label and the textual description generated for the raster object; generating, using, the sentence transformer neural network, a second set of embeddings for the data from the data file; and binding the scalar vector graphic object to the data using the first set of embeddings and the second set of embeddings.
Claim 15 depends from claim 14 with additional limitations.
Regarding claim 19, Karuppasamy, Baron, or any other prior art references on the record, alone or in combination, fails to disclose the operations further comprise providing, to a client device, a recommended mapping between the at least one scalar vector graphic object and the data from the data file; and binding the at least one scalar vector graphic object to the data from the data file comprises binding the at least one scalar vector graphic object to the data based on user input received via the client device with respect to the recommended mapping.
Regarding claim 20, Karuppasamy, Baron, or any other prior art references on the record, alone or in combination, fails to disclose wherein binding the at least one scalar vector graphic object to the data from the data file comprises binding the at least one scalar vector graphic object to the data using a plurality of embeddings representing row names for the data, column names for the data, a label for the at least one raster object, a textual description of the at least one raster object, and one or more scalar vector graphic property names for the at least one scalar vector graphic object.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US Patent Publication No. 20230377221 A1 to Sandsmark et al., which discloses an algorithm for generating a vector graphic based on a raster graphic input.
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/HAIXIA DU/Primary Examiner, Art Unit 2611
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