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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. CN202411122864.0, filed on 08/15/2024.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/27/2025 and 05/11/2026 have been considered by the examiner.
Claim Objections
Claims 2-10 and 13-19 are objected to because of the following informalities:
Claims 2-10 and 13-19 lines 1 recite “is further to” Examiner suggests amending the phrase to “…is further configured to:” Appropriate correction is required.
Claim 7 line 3, “…the second feature…” lacks antecedent basis. Examiner suggests amending the phrase to “a second feature”.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Independent claim 1 lines 10-11, “…of the first frame data…” lack antecedent basis as claim 1 introduces a singular frame data. Examiner suggests removing “the first…”. Independent claims 12 and 20 are similarly rejected.
Dependent claims 2-11 and 13-19 are rejected due to their dependency.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-4, 6-7, 9-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion). The independent claims 1, 12, and 20 recite systems and a method. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that the independent claims 1, 12 and 20 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES. Independent claims 1, 12, and 20 are directed to a machine and method
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES, the claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Independent claims 1, 12, and 20 comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding independent claim(s) 1: the limitations recite:
A system, comprising:
a plurality of processors to (generic computer component):
determine a plurality of instances of frame data individually modified according to at least one dimension of a plurality of dimensions (mental process including observation and evaluation, and can be done mentally in the human mind), the plurality of instances of frame data each provided to respective processors of the plurality of processors that are each configured to execute input arranged in the plurality of dimensions (extra solution activity);
generate, based at least in part on the plurality of instances of the frame data, a plurality of features each respectively corresponding to an instance of frame data from the plurality of instances of the frame data (mental process including observation and evaluation, and can be done mentally in the human mind); and
generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property (mental process including observation and evaluation, and can be done mentally in the human mind).
Regarding independent claim(s) 12: the limitations recite:
A system-on-a-chip (SoC) (generic computer component), comprising:
at least one graphics processing unit (GPU) (generic computer component); and
a plurality of processors to (generic computer component):
determine a plurality of instances of frame data each modified according to at least one of the plurality of dimensions (mental process including observation and evaluation, and can be done mentally in the human mind);
generate, based at least in part on the plurality of instances of the frame data, a plurality of features each respectively corresponding to the instances of the frame data (mental process including observation and evaluation, and can be done mentally in the human mind); and
generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property (mental process including observation and evaluation, and can be done mentally in the human mind).
Regarding independent claim(s) 20: the limitations recite:
A method performed by a plurality of processors (generic computer component), comprising:
determining a plurality of instances of frame data each individually modified according to at least one dimension of a plurality of dimensions (mental process including observation and evaluation, and can be done mentally in the human mind), the plurality of instances of frame data each provided to respective processors of the plurality of processors that are each configured to execute input arranged in the plurality of dimensions (extra solution activity);
generating based at least in part on the plurality of instances of the frame data, a plurality of features each respectively corresponding to an instance of frame data from the plurality of instances of the frame data (mental process including observation and evaluation, and can be done mentally in the human mind); and
generating, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property (mental process including observation and evaluation, and can be done mentally in the human mind).
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As such, a person could mentally determine and organize different instances of frame data based off of various dimensions, and analyze those instances to determine corresponding features. A person could also evaluate those features and determine a metric based off of the features. The mere nominal recitation that the various steps are being executed by the generic computer component(s), for example, system-on-a-chip (SoC), at least one graphics processing unit (GPU), a plurality of processors, etc. does not take the limitations out of the mental process grouping. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Independent claims 1, 12, and 20 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Independent claims 1, 12, and 20 discloses a system-on-a-chip (SoC), at least one graphics processing unit (GPU), a plurality of processors and the plurality of instances of frame data each provided to respective processors of the plurality of processors that are each configured to execute input arranged in the plurality of dimensions, which are generic computer components and/or insignificant pre/post-solution extra activity that do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea in a method.
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Independent claims 1, 12, and 20 do not recite any additional elements that are not well-understood, routine or conventional. The use of a generic computer elements are routine, well-understood and conventional process that is performed by computers.
Thus, since independent claims 1, 12, and 20 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that independent claims 1, 12, and 20 are not eligible subject matter under 35 U.S.C 101.
Regarding claims 2-4, 6-7, 9-11, 13-15, and 17-19: the additional elements the additional elements do not integrate the mental process into practical application or add significantly more to the mental process. In detail claims 6-7 and 9-11 depend on claim 1, and claims 13-15 and 17-19 depend on claim 12 and add:
determining a first instance and modifying the first instance based off of another instance (claims 2 and 13).
providing each instance to a processor (claims 3, 4, 14, and 15).
determining a feature and modifying the feature based on the first instance (claims 6 and 17).
providing each feature to a processor (claims 7 and 18).
providing an output based on whether or not the metric satisfies a condition (claims 9 and 10, and 19).
various systems the plurality of processors could be comprised in (claim 11).
Regarding claim 5: the additional limitations do integrate the mental process into practical application or add significantly more to the mental process. The limitation: "wherein the at least one dimension corresponds to at least one of a shift in a horizontal dimension of one or more bits or a vertical direction of the one or more bits." integrates the mental process into a practical application.
Regarding claim 8: the additional limitations do integrate the mental process into practical application or add significantly more to the mental process. The limitation: "wherein the at least one dimension corresponds to at least one of a shift in a horizontal dimension of one or more bits or a vertical direction of the one or more bits." integrates the mental process into a practical application.
Regarding claim 16: Claim 16 mirrors claim 5 in a system-on-a-chip (SoC) and similarly integrates the mental process into practical application or add significantly more to the mental process.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Beaumont (US 8,856,493 B2) in view of Hong et al. (US 2020/0250807 A1) (hereinafter, “Hong”).
Regarding claim 1, Beaumont discloses a system (Column 3 [lines 34-38] “The active memory device 18 of FIG. 2 is intended to be deployed in a computer system as a slave device, where a host processor (e.g. CPU 12 in FIG. 1) sends commands to the active memory device 18 to initiate processing within the active memory device 18.”), comprising:
a plurality of processors to (Column 1 [lines 38-44] “memory processors 14, can be instructed to perform tasks on its data without the data being transferred to the CPU 12 or to any other part of the system over a system bus 16. The memory processors 14 are a processing resource distributed throughout the main memory 10. The processing resource is most often partitioned into many similar processing elements (PEs).”):
determine a plurality of instances of frame data (rows of data values in Column 9 [lines 14-21] equates to the plurality of instances) individually modified according to at least one dimension of a plurality of dimensions (Column 9 [lines 14-21] “In FIG. 15A, a two-dimensional array of data is illustrated. A right wrap shift is performed on the data illustrated in FIG. 15A in a manner such that the top row of data, r0, remains fixed while each row thereunder is shifted from west to east. The data in row r1 is shifted west to east by one position, row r2 by two positions, etc. while the data in row r7 is shifted west to east by seven positions.”), the plurality of instances of frame data each provided to respective processors of the plurality of processors that are each configured to execute input arranged in the plurality of dimensions (Column 9 [lines 4-11] “Thus, although all of the PEs are responding to the same command, e.g., an east to west wrap shift, each of the PEs is capable of selecting different data at different points during the execution of the instruction thereby enabling various types of data manipulations, e.g., transpose, reflection. Furthermore, by determining which PEs are active, additional flexibility is provided so that subsets of data can be manipulated.”);
generate, based at least in part on the plurality of instances of the frame data, [a plurality of features] each respectively corresponding to an instance of frame data from the plurality of instances of the frame data (Column 8 [lines 10-17] “As the instructions are executed and the shifting proceeds, each PE will be presented with different array values. For example, if a wrap shift is performed a number of times equal to the number of PEs in a row, each PE in the row will see every value held by all of the other PEs in the row. A PE can conditionally select any of the values it sees as its final output value by conditionally loading that value, which is representative of an output result matrix.” Examiner interprets the values as being generated through the shifting process and selected as a final output by conditionally loading those value.); and
[generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property].
However, Beaumont fails to teach a plurality of feature; and generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property.
Hong teaches a plurality of feature (the key-points in Paragraph [0152] equate to plurality of feature) (Paragraph [0152] "At act 310, potential key-points in the input image data are detected, based on which image blocks have a complexity measure that satisfy a specific range."); and generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property (Paragraph [0157] "detected key-point strengths are calculated based on a Strength Measure (SM). The SM is applied to all detected key-points from act 310.").
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to include a plurality of feature; and generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 1.
Regarding claim 2, which claim 1 is incorporated, Beaumont discloses wherein the plurality of processors are further to:
determine a first instance of the plurality of instances of the frame data, the first instance of the frame data structured in the plurality of dimensions (Column 9 [lines 14-18] “In FIG. 15A, a two-dimensional array of data is illustrated. A right wrap shift is performed on the data illustrated in FIG. 15A in a manner such that the top row of data, r0, remains fixed while each row thereunder is shifted from west to east.”); and
modify, based at least on a second instance of the plurality of instances of the frame data, the first instance according to at least one dimension of the plurality of dimensions (Column [lines 18-25] “The data in row r1 is shifted west to east by one position, row r2 by two positions, etc. while the data in row r7 is shifted west to east by seven positions. Because the PEs are physically constrained in the array configuration, the data simply wraps around. However, if the PEs were not physically constrained, a first shear in an eastern direction would be performed as shown by the phantom portion 100.; Examiner interprets that the shift amount for each row (i.e. first instance) is determined based on its position relative to other rows (i.e. second instance)).
Regarding claim 3, which claim 2 is incorporated, Beaumont discloses wherein the plurality of processors are further to: provide the first instance to a first processor among the plurality of processors, the first processor configured to execute input arranged in the plurality of dimensions (Column 4 [ lines 39-42] “The active memory device 18 may contain, according to one embodiment, sixteen 64kx128 eDRAM cores. Each eDRAM core is closely connected to an array of sixteen PEs, making 256 (16x16) PEs in all.” Column 5 [lines 34-37] “The DRAM interface 52 may contain two registers, a RAM IN register and a RAM OUT register. Input from the DRAM 24 of FIG. 2 may be held in the RAM IN register while output to the DRAM 24 is held in the RAM OUT register.”).
Regarding claim 4, which claim 2 is incorporated, Beaumont discloses wherein the plurality of processors are further to: provide the second instance to a second processor (the neighboring PE in Column 6 [lines 4-8] equates to the second processor) among the plurality of processors, the second processor configured to execute input arranged in the plurality of dimensions (Column 6 [lines 4-8] “The X output is connected to the neighboring inputs of each PE’s closest neighbors in the north and west directions. To the south and east, the X output is combined with the input from the opposite direction and driven out to the neighboring PE.”).
Regarding claim 5, which claim 2 is incorporated, Beaumont discloses wherein the at least one dimension corresponds to at least one of a shift in a horizontal dimension of one or more bits or a vertical direction of the one or more bits (Column 6 [lines 32-38] “In the edge shift, the edge/col registers 56 are active as the data is shifted left to right (west to east) as shown in FIGS. 6A, 6B. The reader will recognize that an edge shift may be performed in the other direction, right to left (east to west). Alternatively, edge shifts may be performed by using the edge/row registers 54 in a north to south or south to north direction.”).
Regarding claim 6, which claim 1 is incorporated, Beaumont fails to teach wherein the plurality of processors are further to: determine a first feature of the plurality of features, the first feature structured in at least one of the plurality of dimensions; and modify, based at least on a first instance of the plurality of instances of the frame data, the first feature according to at least one dimension of the plurality of dimensions.
Hong teaches wherein the plurality of processors are further to:
determine a first feature of the plurality of features (key-points in Paragraph [0025] equates to the features), the first feature structured in at least one of the plurality of dimensions (Paragraph [0025] “determining a row co-ordinate and a column co-ordinate of the key-point; fitting strength measures of the key-point and its row neighbor key-points; Paragraph [0152] “At act 310, potential key-points in the input image data are detected, based on which image blocks have a complexity measure that satisfy a specific range.”); and
modify, based at least on a first instance of the plurality of instances of the frame data, the first feature according to at least one dimension of the plurality of dimensions (Paragraph [0025] “determining a sub-pixel row co-ordinate by solving a derivative equation of the first fitting model; converting the determined sub-pixel row co-ordinate into the co-ordinate system of the current pyramid level of the detected key-points”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to include wherein the plurality of processors are further to: determine a first feature of the plurality of features, the first feature structured in at least one of the plurality of dimensions; and modify, based at least on a first instance of the plurality of instances of the frame data, the first feature according to at least one dimension of the plurality of dimensions taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 6.
Regarding claim 7, which claim 6 is incorporated, Beaumont discloses wherein the plurality of processors are further to: provide [the first feature] to a first processor among the plurality of processors (Column 4 [ lines 39-42] “The active memory device 18 may contain, according to one embodiment, sixteen 64kx128 eDRAM cores. Each eDRAM core is closely connected to an array of sixteen PEs, making 256 (16x16) PEs in all.” Column 5 [lines 34-37] “The DRAM interface 52 may contain two registers, a RAM IN register and a RAM OUT register. Input from the DRAM 24 of FIG. 2 may be held in the RAM IN register while output to the DRAM 24 is held in the RAM OUT register.”); and provide [the second feature] to a second processor (the neighboring PE in Column 6 [lines 4-8] equates to the second processor) among the plurality of processors (Column 6 [lines 4-8] “The X output is connected to the neighboring inputs of each PE’s closest neighbors in the north and west directions. To the south and east, the X output is combined with the input from the opposite direction and driven out to the neighboring PE.”).
However, Beaumont fails to teach the first feature and the second feature.
Hong teaches the first feature and the second feature (Paragraph [0128] “The other devices 138 may be devices that can be configured, for example, to process lists of detected key-points for associated image data and/or video data, for various purposes…These other devices may be an image processing device, an ASIC device or another CPU that can process the detected key-points.”; Paragraph [0152] "At act 310, potential key-points in the input image data are detected, based on which image blocks have a complexity measure that satisfy a specific range.").
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to include the first feature and the second feature taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 7.
Regarding claim 8, which claim 6 is incorporated, Beaumont discloses wherein the at least one dimension corresponds to at least one of a shift in a horizontal dimension of one or more bits or a vertical direction of the one or more bits (Column 6 [lines 32-38] “In the edge shift, the edge/col registers 56 are active as the data is shifted left to right (west to east) as shown in FIGS. 6A, 6B. The reader will recognize that an edge shift may be performed in the other direction, right to left (east to west). Alternatively, edge shifts may be performed by using the edge/row registers 54 in a north to south or south to north direction.”).
Regarding claim 9, which claim 1 is incorporated, Beaumont fails to teach wherein the plurality of processors are further to: provide, in response to the metric satisfying a condition indicative of presence of a feature in the frame data, the metric as output, wherein the condition corresponds to a local maximum associated with the visual property, and the feature is indicative of the visual property.
Hong teaches wherein the plurality of processors are further to: provide, in response to the metric satisfying a condition indicative of presence of a feature in the frame data, the metric as output (Paragraph [0173] " the key-point detector 120 outputs a list of key-points at act 206. For example, one key-point list can be output for each image."; Figure 4B), wherein the condition corresponds to a local maximum associated with the visual property, and the feature is indicative of the visual property (Paragraph [0039] "determining key-points for which the at least one measure for each of the image blocks falls within a specified range; retaining only the determined key-points with the at least one measure that is a local maxima in a sliding window when performing non-maxima suppression and identifying these retained key-points as detected key-points; and, storing the detected key-points in the memory unit.").
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to include wherein the plurality of processors are further to: provide, in response to the metric satisfying a condition indicative of presence of a feature in the frame data, the metric as output, wherein the condition corresponds to a local maximum associated with the visual property, and the feature is indicative of the visual property taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 9.
Regarding claim 10, which claim 1 incorporated, Beaumont fails to teach wherein the plurality of processors are further to: provide, in response to the metric not satisfying a condition indicative of presence of a feature in the frame data, output distinct from the metric, wherein the condition corresponds to a local maximum associated with the visual property, and the feature is indicative of the visual property.
Hong teaches wherein the plurality of processors are further to: provide, in response to the metric not satisfying a condition indicative of presence of a feature in the frame data, output distinct from the metric, wherein the condition corresponds to a local maximum associated with the visual property, and the feature is indicative of the visual property (Paragraph [0039] "determining key-points for which the at least one measure for each of the image blocks falls within a specified range; retaining only the determined key-points with the at least one measure that is a local maxima in a sliding window when performing non-maxima suppression and identifying these retained key-points as detected key-points; and, storing the detected key-points in the memory unit."; Examiner interprets that the non-maxima suppression equates to an output distinct from the metric as the key-points that are suppressed do not satisfy a condition.).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to wherein the plurality of processors are further to: provide, in response to the metric not satisfying a condition indicative of presence of a feature in the frame data, output distinct from the metric, wherein the condition corresponds to a local maximum associated with the visual property, and the feature is indicative of the visual property taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 10.
Regarding claim 11, which claim 1 is incorporated, Beaumont fails to teach wherein the plurality of processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system implemented using a robot; an aerial system; a medical system; a boating system; a smart area monitoring system; a system for performing deep learning operations; a system for performing simulation operations; a system for generating or presenting virtual reality (VR) content, augmented reality (AR) content, or mixed reality (MR) content; a system for performing digital twin operations; a system implemented using an edge device; a system incorporating one or more virtual machines (VMs); a system for generating synthetic data; a system implemented at least partially in a data center; a system for performing conversational artificial intelligence (AI) operations; a system for performing generative AI operations; a system implementing language models; a system implementing vision language models (VLMs); a system implementing large language models (LLMs); a system implementing multi-modal language models; a system for hosting one or more real-time streaming applications; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; or a system implemented at least partially using cloud computing resources.
Hong teaches wherein the plurality of processors are comprised in at least one of:
a control system for an autonomous or semi-autonomous machine;
a perception system for an autonomous or semi-autonomous machine (Paragraph [0182] “for autonomous driving, which may use SLAM systems, once corresponding key-points are determined for one or more images, 3D information of the surrounding environment of a vehicle can be generated.”);
a system implemented using a robot (Paragraph [0181] “the key-point detection methods described herein can be used with Simultaneous Localization and Mapping (SLAM) which is one of the most important tasks in robotics to concurrently localize the pose of a robot and reconstruct the 3D environment surrounding it”);
an aerial system;
a medical system;
a boating system;
a smart area monitoring system;
a system for performing deep learning operations;
a system for performing simulation operations;
a system for generating or presenting virtual reality (VR) content, augmented reality (AR) content, or mixed reality (MR) content;
a system for performing digital twin operations;
a system implemented using an edge device;
a system incorporating one or more virtual machines (VMs);
a system for generating synthetic data;
a system implemented at least partially in a data center;
a system for performing conversational artificial intelligence (AI) operations;
a system for performing generative AI operations;
a system implementing language models;
a system implementing vision language models (VLMs);
a system implementing large language models (LLMs);
a system implementing multi-modal language models;
a system for hosting one or more real-time streaming applications;
a system for performing light transport simulation;
a system for performing collaborative content creation for 3D assets; or
a system implemented at least partially using cloud computing resources.
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to include wherein the plurality of processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system implemented using a robot; an aerial system; a medical system; a boating system; a smart area monitoring system; a system for performing deep learning operations; a system for performing simulation operations; a system for generating or presenting virtual reality (VR) content, augmented reality (AR) content, or mixed reality (MR) content; a system for performing digital twin operations; a system implemented using an edge device; a system incorporating one or more virtual machines (VMs); a system for generating synthetic data; a system implemented at least partially in a data center; a system for performing conversational artificial intelligence (AI) operations; a system for performing generative AI operations; a system implementing language models; a system implementing vision language models (VLMs); a system implementing large language models (LLMs); a system implementing multi-modal language models; a system for hosting one or more real-time streaming applications; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; or a system implemented at least partially using cloud computing resources taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 11.
Regarding claim 12, Beaumont discloses [a system-on-a-chip (SoC)], comprising:
[at least one graphics processing unit (GPU)]; and
a plurality of processors to (Column 1 [lines 38-44] “memory processors 14, can be instructed to perform tasks on its data without the data being transferred to the CPU 12 or to any other part of the system over a system bus 16. The memory processors 14 are a processing resource distributed throughout the main memory 10. The processing resource is most often partitioned into many similar processing elements (PEs).”):
determine a plurality of instances (rows of data values in Column 9 [lines 14-21] equates to the plurality of instances) of frame data each modified according to at least one of the plurality of dimensions (Column 9 [lines 14-21] “In FIG. 15A, a two-dimensional array of data is illustrated. A right wrap shift is performed on the data illustrated in FIG. 15A in a manner such that the top row of data, r0, remains fixed while each row thereunder is shifted from west to east. The data in row r1 is shifted west to east by one position, row r2 by two positions, etc. while the data in row r7 is shifted west to east by seven positions.”);
generate, based at least in part on the plurality of instances of the frame data, [a plurality of features] each respectively corresponding to the instances of the frame data (Column 8 [lines 10-17] “As the instructions are executed and the shifting proceeds, each PE will be presented with different array values. For example, if a wrap shift is performed a number of times equal to the number of PEs in a row, each PE in the row will see every value held by all of the other PEs in the row. A PE can conditionally select any of the values it sees as its final output value by conditionally loading that value, which is representative of an output result matrix.” Examiner interprets the values as being generated through the shifting process and selected as a final output by conditionally loading those value.); and
[generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property].
However, Beaumont fails to teach a system-on-a-chip (SoC)], comprising: at least one graphics processing unit (GPU), a plurality of feature; and generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property.
Hong teaches a system-on-a-chip (SoC), comprising: at least one graphics processing unit (GPU) (Paragraph [0110] “The CPU and the GPU can be contained in a single chip.”), a plurality of feature (the key-points in Paragraph [0152] equate to plurality of feature) (Paragraph [0152] "At act 310, potential key-points in the input image data are detected, based on which image blocks have a complexity measure that satisfy a specific range."); and generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property Paragraph [0157] "detected key-point strengths are calculated based on a Strength Measure (SM). The SM is applied to all detected key-points from act 310.").
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to include a system-on-a-chip (SoC)], comprising: at least one graphics processing unit (GPU), a plurality of feature; and generate, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 12.
Regarding claim 13 (drawn to a system-on-a-chip (SoC)), claim 13 is rejected the same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to the claim 13, and all the other limitations similar to claim 2 are not repeated herein, but incorporated by reference.
Regarding claim 14 (drawn to a system-on-a-chip (SoC)), claim 14 is rejected the same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to the claim 14, and all the other limitations similar to claim 3 are not repeated herein, but incorporated by reference.
Regarding claim 15 (drawn to a system-on-a-chip (SoC)), claim 15 is rejected the same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to the claim 15, and all the other limitations similar to claim 4 are not repeated herein, but incorporated by reference.
Regarding claim 16 (drawn to a system-on-a-chip (SoC)), claim 16 is rejected the same as claim 5 and the arguments similar to that presented above for claim 5 are equally applicable to the claim 16, and all the other limitations similar to claim 5 are not repeated herein, but incorporated by reference.
Regarding claim 17 (drawn to a system-on-a-chip (SoC)), claim 17 is rejected the same as claim 6 and the arguments similar to that presented above for claim 6 are equally applicable to the claim 17, and all the other limitations similar to claim 6 are not repeated herein, but incorporated by reference.
Regarding claim 18 (drawn to a system-on-a-chip (SoC)), claim 18 is rejected the same as claim 7 and the arguments similar to that presented above for claim 7 are equally applicable to the claim 18, and all the other limitations similar to claim 7 are not repeated herein, but incorporated by reference.
Regarding claim 19, which claim 12 is incorporated, Beaumont discloses wherein the plurality of processors is further to: provide, in response to the metric satisfying a condition indicative of presence of a feature in the frame data, the metric as output; and provide, in response to the metric not satisfying a condition indicative of presence of a feature in the frame data, output distinct from the metric (Paragraph [0039] "determining key-points for which the at least one measure for each of the image blocks falls within a specified range; retaining only the determined key-points with the at least one measure that is a local maxima in a sliding window when performing non-maxima suppression and identifying these retained key-points as detected key-points; and, storing the detected key-points in the memory unit." Examiner interprets that the non-maxima suppression equates to an output distinct from the metric as the key-points that are suppressed do not satisfy a condition.).
Regarding claim 20, Beaumont discloses a method performed by a plurality of processors (Column 1 [lines 38-44] “memory processors 14, can be instructed to perform tasks on its data without the data being transferred to the CPU 12 or to any other part of the system over a system bus 16. The memory processors 14 are a processing resource distributed throughout the main memory 10. The processing resource is most often partitioned into many similar processing elements (PEs).”), comprising:
determining a plurality of instances (rows of data values in Column 9 [lines 14-21] equates to the plurality of instances) of frame data each individually modified according to at least one dimension of a plurality of dimensions (Column 9 [lines 14-21] “In FIG. 15A, a two-dimensional array of data is illustrated. A right wrap shift is performed on the data illustrated in FIG. 15A in a manner such that the top row of data, r0, remains fixed while each row thereunder is shifted from west to east. The data in row r1 is shifted west to east by one position, row r2 by two positions, etc. while the data in row r7 is shifted west to east by seven positions.”), the plurality of instances of frame data each provided to respective processors of the plurality of processors that are each configured to execute input arranged in the plurality of dimensions (Column 9 [lines 4-11] “Thus, although all of the PEs are responding to the same command, e.g., an east to west wrap shift, each of the PEs is capable of selecting different data at different points during the execution of the instruction thereby enabling various types of data manipulations, e.g., transpose, reflection. Furthermore, by determining which PEs are active, additional flexibility is provided so that subsets of data can be manipulated.”);
generating based at least in part on the plurality of instances of the frame data, [a plurality of features] each respectively corresponding to an instance of frame data from the plurality of instances of the frame data (Column 8 [lines 10-17] “As the instructions are executed and the shifting proceeds, each PE will be presented with different array values. For example, if a wrap shift is performed a number of times equal to the number of PEs in a row, each PE in the row will see every value held by all of the other PEs in the row. A PE can conditionally select any of the values it sees as its final output value by conditionally loading that value, which is representative of an output result matrix.” Examiner interprets the values as being generated through the shifting process and selected as a final output by conditionally loading those value.); and
[generating, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property].
However, Beaumont fails to teach a plurality of features; and generating, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property.
Hong teaches a plurality of features (the key-points in Paragraph [0152] equate to plurality of feature) (Paragraph [0152] "At act 310, potential key-points in the input image data are detected, based on which image blocks have a complexity measure that satisfy a specific range."); and generating, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property (Paragraph [0157] "detected key-point strengths are calculated based on a Strength Measure (SM). The SM is applied to all detected key-points from act 310.").
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Beaumont’s reference to include a plurality of features; and generating, based at least in part on the plurality of features, a metric of the first frame data in the plurality of dimensions, the metric indicative of a visual property taught by Hong’s reference. The motivation for doing so would have been to improve the performance of a key-point detector as suggested by Hong (see Hong, Paragraph [0233]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Hong with Beaumont to obtain the invention specified in claim 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kaneko et al. (US 5,430,885 A) discloses a multi-processor image signal processing system, enabling parallel processing of different regions of image data.
Panneer et al. (US 2024/0311951 A1) discloses a graphic processor that performs frame prediction by comparing command buffer execution times with stored timestamps to bypass rendering operation that cannot be completed before a target display update.
Cui et al. (US 2024/0346811 A1) discloses a feature aggregation method that extract an image feature representation, selectas image features elements that are divided along predetermined dimensions and determines an aggregated image feature based on the elements.
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/UROOJ FATIMA/ Examiner, Art Unit 2676
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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