CTNF 18/345,593 CTNF 98475 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Priority 02-25 AIA Acknowledgment is made of applicant's claim for foreign priority based on an application filed in China on 12 April, 2023 . It is noted, however, that applicant has not filed a certified copy of the PCT/2023/087769 application as required by 37 CFR 1.55. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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. Claims 1 - 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. When reviewing independent claim 1 , and based upon consideration of all of the relevant factors with respect to the claim as a whole, claims 1 - 20 are held to claim an abstract idea without reciting elements that amount to significantly more than the abstract idea and is/are therefore rejected as ineligible subject matter under 35 U.S.C. 101. The Examiner will analyze Claim 1 , and similar rationale applies to independent claim 8 and 14 . The rationale, under MPEP § 2106, for this finding is explained below: The claimed invention (1) must be directed to one of the four statutory categories, and (2) must not be wholly directed to subject matter encompassing a judicially recognized exception, as defined below. The following two step analysis is used to evaluate these criteria. Step 1: Is the claim directed to one of the four patent-eligible subject matter categories: process, machine, manufacture, or composition of matter? When examining the claim under 35 U.S.C. 101, the Examiner interprets that the claims is related to a machine since the claim is directed to a computing system comprising a processor, an imaging device coupled to the processor, and memory coupled to the processor. Step 2a, Prong 1: Does the claim wholly embrace a judicially recognized exception, which includes laws of nature, physical phenomena, and abstract ideas, or is it a particular practical application of a judicial exception? The Examiner interprets that the judicial exception applies since the claim 1 limitations of “analyze a scene from a plurality of input images to determine a stability score, wherein the stability score reflects a relative stability for the scene”, “determine a target imaging statistics resolution based on the stability score”, and “calculate, using generated imaging statistics corresponding to the target imaging statistics resolution, one or more of an auto exposure parameter or an auto white balance parameter wherein the auto exposure parameter is to be used for generating an input image and the auto white balance parameter is to be used for generating an output image” are directed to an abstract idea. The claim is related to mathematical concept as each limitation recites mere mathematic calculations used to produce values or comparisons. If the claim recites a judicial exception ( i.e., an abstract idea enumerated in MPEP § 2106.04(a), a law of nature, or a natural phenomenon), the claim requires further analysis in Prong Two. Step 2a, Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application? The Examiner interprets that the claim 1 limitations do not provide additional elements or combination of additional elements to a practical application since the claims are Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h). ] See, MPEP §2106.04(a), Because a judicial exception is not eligible subject matter, Bilski, 561 U.S. at 601, 95 USPQ2d at 1005-06 (quoting Chakrabarty, 447 U.S. at 309, 206 USPQ at 197 (1980)), if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"). OR Genetic Techs. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself."). For a claim reciting a judicial exception to be eligible, the additional elements (if any) in the claim must "transform the nature of the claim" into a patent-eligible application of the judicial exception, Alice Corp., 573 U.S. at 217, 110 USPQ2d at 1981, either at Prong Two or in Step 2B. If there are no additional elements in the claim, then it cannot be eligible. In such a case, after making the appropriate rejection (see MPEP § 2106.07 for more information on formulating a rejection for lack of eligibility), it is a best practice for the examiner to recommend an amendment, if possible, that would resolve eligibility of the claim. Step 2b: If a judicial exception into a practical application is not recited in the claim, the Examiner must interpret if the claim recites additional elements that amount to significantly more than the judicial exception. The Examiner interprets that the claims do not amount to significantly more since the claim merely recites the inclusion of generic computer components which execute the mathematics Furthermore, the generic computer components of the memory, processor, and imaging device recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Claims 2 – 7, 9 – 13, and 15 - 20 depending on the independent claims include all the limitation of the independent claim. The Examiner finds that claim 2 – 7, 9 – 13, and 15 - 20 does not state significantly more since the claim only recites “wherein the instructions, when executed cause the computing system to generate a multi-scale statistics set, the multi-scale statistics set including a plurality of sets of imaging statistics, each set of imaging statistics of the plurality of sets of imaging statistics corresponding to a different resolution of a predetermined set of resolutions”, “determine a provisional resolution based on the stability score”, and “select the target imaging statistics resolution from the predetermined set of resolutions based on a distance parameter determined between the provisional resolution and each of the predetermined set of resolutions” in claims 2, 9, and 15 ; “selecting, from the plurality of sets of imaging statistics, a set of imaging statistics corresponding to the target imaging statistics resolution.” in claims 3, 10, and 16 ; “wherein the predetermined set of resolutions include a first resolution corresponding to a downscaling ratio of 1:64, a second resolution corresponding to a downscaling ratio of 1:32, and a third resolution corresponding to a downscaling ratio of 1:16”, in claims 4, 11, and 17 ; “compute the target imaging statistics resolution based on the stability score and a maximum imaging statistics resolution for the computing system” in claims 5, 12, and 18 ; “calculate, using the generated imaging statistics corresponding to the target imaging statistics resolution, an auto focus parameter, wherein the auto focus parameter is used for generating the input image” in claims 6, 13, and 19 ; and “wherein the stability score is to be determined based on comparing imaging statistics for two images in a sequence” in claims 7, 13, and 20 . Thus, claims 2 – 7, 9 – 13, and 15 - 20 recite the same abstract idea and therefore are not drawn to the eligible subject matter as they are directed to the abstract idea without significantly more. Therefore, the Examiner interprets that the claims are rejected under 35 U.S.C. 101. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1, 5 – 8, 12 – 14, and 18 - 20 are rejected under 35 U.S.C. 103 as being unpatentable over Ain-Kedem et al (U.S. Patent Publication No. 2018/035941 A1, hereinafter “Ain”) in view of Larkin et al (U.S. Patent Publication No. 2024/0147086 A1, hereinafter “Larkin”) . Regarding claim 1 , Ain teaches a computing system comprising: a processor (¶ 0021: The material disclosed herein may also be implemented as instructions stored on a machine-readable medium, which may be read and executed by one or more processors.) ; an imaging device coupled to the processor (¶ 0021: For instance, various architectures employing, for example, multiple integrated circuit (IC) chips and/or packages, and/or various computing devices and/or consumer electronic (CE) devices such as set top boxes, smartphones, cameras, laptop computers, tablets, and so forth, may implement the techniques and/or arrangements described herein.) ; and memory coupled to the processor, the memory to store instructions which, when executed by the processor, cause the computing system to (¶ 0021: The material disclosed herein may also be implemented as instructions stored on a machine-readable medium, which may be read and executed by one or more processors.) : analyze a scene from a plurality of input images to determine a stability score (¶ 0040: Referring to FIG. 2 for example, a video processing sequence 200 has captured frames of a video sequence including image data input from frame FN-1 (202) to frame FN+2 (208) and is shown in on-the fly mode… In this example, the system collects data to form a full single frame's worth of statistics by collecting data from parts of both a first frame FN-1 (202) and a second or current (or next) frame FN (204) during a 3A stat calc. period 210 that overlaps the input and processing time of both frames FN-1 and FN) , wherein the stability score reflects a relative stability for the scene (¶ 0032: Other general statistics that may be generated whether for use for 3A operations or other functions may include luminance and/or chrominance averages, luminance and/or chrominance high frequency and texture content, motion content from frame to frame, any other color content values, picture statistical data regarding deblocking control (for example, information controlling deblocking and/or non-deblocking), RGBS grid, filter response grid, and RGB histograms to name a few examples.) ; determine a target imaging statistics resolution based on the stability score; and calculate, using generated imaging statistics corresponding to the target imaging statistics resolution, one or more of an auto exposure parameter or an auto white balance parameter (¶ 0092: Relevant herein, automatic exposure control (AEC) uses algorithms to adjust the exposure parameters to capture images and to provide adjustments for the brightness parameters for the display of an image, whether on a live preview screen of the digital camera, or other recorded display, and storage or encoding of the image or video for later viewing.; ¶ 0095: Then, the AWB control performs adjustment calculations that provide new white balance (WB) gains 539 during a time period (T_AWBetc_execution) 486 after the second latency. As mentioned above, A WB algorithms such as color correlation, gamut mapping, grey-edge, and/or grey-world AWB methods can be used to determine the white point and RGB gains.) , wherein the auto exposure parameter is to be used for generating an input image and the auto white balance parameter is to be used for generating an output image (¶ 0002: The digital image processing devices use AWB in order to provide accurate colors for pictures reproduced from captured images. A WB is a process that finds or defines the color white in a picture called the white point.; ¶ 0004: Automatic exposure control is used to automatically compute and adjust the correct exposure necessary to capture and generate a good quality image.; Examiner’s note: It would be understood by one skilled in the art that exposure, being the measurement of light collected by a camera when taking an image, would be used for generating an image, whereas white balance is used after the image is taken to adjust the color parameters of the captured image.) . Ain does not explicitly teach determine a target imaging statistics resolution based on the stability score; and calculate, using generated imaging statistics corresponding to the target imaging statistics resolution. However, Larkin does teach determine a target imaging statistics resolution based on the stability score (¶ 0052: the statistics data is used to detect an event in a scene, and to trigger an action e.g. in response to an event being detected.; ¶ 0063: An event may be detected, for example by identifying any differences between the statistics data for the latest frame and the one or more previous frames.; ¶ 0081: For example, the image sensor data output from the image sensor when the apparatus is operating in low-power mode may be reduced in size and/or resolution in comparison to the image sensor data output from the image sensor when the apparatus is operating in a relatively high-power mode.) ; and calculate, using generated imaging statistics corresponding to the target imaging statistics resolution, one or more of an auto exposure parameter or an auto white balance parameter (¶ 0036 – 0039: Examples of different types of statistics data generated by the one or more statistics data modules 8 include: Auto-Exposure (AE)… Auto-Focus (AF)… Auto White Balance (AWB).; ¶ 110: At S308 one or more statistics data modules of a processing component (e.g. an ISP) are used to process the image sensor data to generate statistics data which are derived, at least in part, from the image sensor data.) Ain and Larkin are considered to be analogous art as both pertain to generating imaging parameters based on camera image data. Therefore, it would have been obvious to one of ordinary skill in the art to combine the method of camera control and image processing (as taught by Ain) and the method for processing image data (as taught by Larkin) before the effective filing date of the claimed invention. The motivation for this combination of references would be the system of Larkin operates in a low-power mode to conserve resources, and when an event is detected, utilizes more intensive imaging parameters thus reducing energy consumption (See ¶ 0043). This motivation for the combination of Ain and Larkin is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III). Regarding claim 5 , the Ain and Larkin combination teaches the computing system of claim 1. Additionally, Larkin teaches wherein to determine the target imaging statistics resolution based on the stability score, the instructions, when executed, cause the computing system to compute the target imaging statistics resolution based on the stability score and a maximum imaging statistics resolution for the computing system (¶ 0108: At S304 an image sensor monitors a scene and generates initial sensor data. Such sensor data may be relatively large in size/resolution e.g. an array comprising 2 kx2 k initial sensor pixel values.; ¶ 0109: At S306 the image sensor modifies the initial sensor data (e.g. by reducing the size and/or resolution of the sensor data (e.g. by way of binning, cropping, sampling processes)) and outputs image sensor data.) . Regarding claim 6 , the Ain and Larkin combination teaches the computing system of claim 1. Additionally, Larkin teaches wherein the instructions, when executed, cause the computing system to calculate, using the generated imaging statistics corresponding to the target imaging statistics resolution, an auto focus parameter, wherein the auto focus parameter is used for generating the input image (¶ 0036 – 0039: Examples of different types of statistics data generated by the one or more statistics data modules 8 include: Auto-Exposure (AE)… Auto-Focus (AF)… Auto White Balance (AWB).; ¶ 110 : At S308 one or more statistics data modules of a processing component (e.g. an ISP) are used to process the image sensor data to generate statistics data which are derived, at least in part, from the image sensor data.; Examiner’s note: It would be understood by one skilled in the art that focus is a camera parameter that would be used for generating an image.) . Regarding claim 7 , the Ain and Larkin combination teaches the computing system of claim 1. Additionally, Ain teaches wherein the stability score is to be determined based on comparing imaging statistics for two images in a sequence (¶ 0040: Referring to FIG. 2 for example, a video processing sequence 200 has captured frames of a video sequence including image data input from frame FN-1 (202) to frame FN+2 (208) and is shown in on-the fly mode… In this example, the system collects data to form a full single frame's worth of statistics by collecting data from parts of both a first frame FN-1 (202) and a second or current (or next) frame FN (204) during a 3A stat calc. period 210 that overlaps the input and processing time of both frames FN-1 and FN; ¶ 0032: Other general statistics that may be generated whether for use for 3A operations or other functions may include luminance and/or chrominance averages, luminance and/or chrominance high frequency and texture content, motion content from frame to frame (emphasis added)) . Regarding claim 8 , claim 8 has been analyzed with regard to claim 1 and is rejected for the same reasons of obviousness as used above as well as in accordance with Ain’s further teaching on: A semiconductor apparatus comprising: one or more substrates; and logic coupled to the one or more substrates, wherein the logic is implemented at least partly in one or more of configurable logic or fixed-functionality hardware logic (¶ 0076: It will be understood that a CPU and/or other processor(s) could perform such processing rather than, or in addition to, the ISP. It also will be appreciated that the registers may be registers of more than one ISP, and/or registers of another type of processor (CPU, and so forth). The ISP may be part of a system on a chip (SoC) or other architectures, a number of which are mentioned elsewhere herein.) , the logic to: Regarding claim 12 , claim 12 has been analyzed with regard to respective claim 5 and is rejected for the same reasons of obviousness as used above. Regarding claim 13 , claim 13 has been analyzed with regard to respective claims 6 and 7 and is rejected for the same reasons of obviousness as used above. Regarding claim 14 , claim 14 has been analyzed with regard to claim 1 and is rejected for the same reasons of obviousness as used above as well as in accordance with Ain’s further teaching on: At least one computer readable storage medium comprising a set of executable program instructions which, when executed by a computing device, cause the computing device to (¶ 0021: The material disclosed herein may also be implemented as instructions stored on a machine-readable medium, which may be read and executed by one or more processors.) : Regarding claim 18 , claim 18 has been analyzed with regard to respective claim 5 and is rejected for the same reasons of obviousness as used above. Regarding claim 19 , claim 19 has been analyzed with regard to respective claim 6 and is rejected for the same reasons of obviousness as used above. Regarding claim 20 , claim 20 has been analyzed with regard to respective claim 7 and is rejected for the same reasons of obviousness as used above. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW JONES whose telephone number is (703)756-4573. The examiner can normally be reached Monday - Friday 8:00-5:00 EST, off Every Other Friday. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached at (571) 272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ANDREW B. JONES/Examiner, Art Unit 2667 /MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667 Application/Control Number: 18/345,593 Page 2 Art Unit: 2667 Application/Control Number: 18/345,593 Page 3 Art Unit: 2667 Application/Control Number: 18/345,593 Page 4 Art Unit: 2667 Application/Control Number: 18/345,593 Page 5 Art Unit: 2667 Application/Control Number: 18/345,593 Page 6 Art Unit: 2667 Application/Control Number: 18/345,593 Page 7 Art Unit: 2667 Application/Control Number: 18/345,593 Page 8 Art Unit: 2667 Application/Control Number: 18/345,593 Page 9 Art Unit: 2667 Application/Control Number: 18/345,593 Page 10 Art Unit: 2667 Application/Control Number: 18/345,593 Page 12 Art Unit: 2667
Prosecution Insights