CTNF 19/240,730 CTNF 95615 DETAILED ACTION 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. Claims 1-19 are pending. Information Disclosure Statement The information disclosure statement (IDS) submitted on 10/06/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Claim Objections 07-29-01 AIA Claim s 9 and 12 are objected to because of the following informalities: Claim 9 last line: “a storage unit” should be changed to read “the storage unit”. Claim 12 line 9: “a storage unit” should be changed to read “the storage unit” . Appropriate correction is required. 07-30-03-h AIA Claim Interpretation 07-30-03 AIA The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. 07-30-05 The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. 07-30-06 This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “driver information acquisition unit” in claims 1, 13, 17, and 19; “data processing unit” in claims 1-2, 5-14, 17, and 19; and “environment information acquisition unit” in claim 9. Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Double Patenting 08-33 AIA The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg , 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman , 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi , 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel , 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 1-19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-19 of U.S. Patent No. 12,351,215, hereinafter U.S. Patent ‘215. Regarding claim 1, U.S. Patent ‘215 teaches: An information processing device comprising: a driver information acquisition unit configured to acquire observation information of a driver of a vehicle (claim 1 “a central processing unit (CPU) configured to: acquire observation information of a driver of a vehicle”) ; and a data processing unit configured to input the observation information and execute data processing (claim 1 “a central processing unit (CPU) configured to: acquire observation information of a driver of a vehicle”) , wherein the data processing unit divides the observation information into conversion unnecessary data and conversion necessary data (claim 1 “divide the observation information into conversion unnecessary data and conversion necessary data”) , and executes data conversion processing of at least one of abstraction processing or encryption processing for the conversion necessary data (claim 1 “execute, as a data conversion process, at least one of: an abstraction process for the conversion necessary data to generate abstraction data, or an encryption process for the conversion necessary data to generate encryption data”) , and stores conversion data of at least one of generated abstraction data or generated encryption data in a storage unit (claim 1 “control a memory to store the at least one of the generated abstraction data or the generated encryption data”) . Claim 2 of the present invention is rejected in view of claim 2 of U.S. Patent ‘215. Claim 3 of the present invention is rejected in view of claim 3 of U.S. Patent ‘215. Claim 4 of the present invention is rejected in view of claim 4 of U.S. Patent ‘215. Claim 5 of the present invention is rejected in view of claim 5 of U.S. Patent ‘215. Claim 6 of the present invention is rejected in view of claim 5 of U.S. Patent ‘215. Claim 7 of the present invention is rejected in view of claim 7 of U.S. Patent ‘215. Claim 8 of the present invention is rejected in view of claim 8 of U.S. Patent ‘215. Claim 9 of the present invention is rejected in view of claims 1 and 9 of U.S. Patent ‘215. Claim 10 of the present invention is rejected in view of claim 10 of U.S. Patent ‘215. Claim 11 of the present invention is rejected in view of claim 11 of U.S. Patent ‘215. Claim 12 of the present invention is rejected in view of claim 12 of U.S. Patent ‘215. Regarding claim 13, U.S. Patent ’215 teaches: A mobile device (claim 13) capable of switching automatic driving and manual driving (claim 14 “a switch from automatic driving to the manual driving for the driver”) , the mobile device comprising: a driver information acquisition unit configured to acquire observation information of a driver of a vehicle (claim 13 “a central processing unit (CPU) configured to: acquire observation information of a driver of a vehicle”) ; and a data processing unit configured to input the observation information and execute data processing (claim 13 “a central processing unit (CPU) configured to: acquire observation information of a driver of a vehicle”) , wherein the data processing unit divides the observation information into conversion unnecessary data and conversion necessary data (claim 13 “divide the observation information into conversion unnecessary data and conversion necessary data”) , executes data conversion processing of at least one of abstraction processing or encryption processing for the conversion necessary data (claim 13 “execute, as a data conversion process, at least one of: an abstraction process for the conversion necessary data to generate abstraction data, or an encryption process for the conversion necessary data to generate encryption data”) , and stores conversion data of at least one of generated abstraction data or generated encryption data in a storage unit (claim 13 “control a memory to store the at least one of the generated abstraction data or the generated encryption data in association with identification information of the driver”) , and calculates a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving on a basis of the observation information (claim 13 “calculate, based on the observation information, a driver evaluation value that is an index value indicating whether the driver is in a state of being able to start manual driving”) , and stores the calculated driver evaluation value in the storage unit as the conversion unnecessary data (claim 13 “control the memory to store the calculated driver evaluation value as the conversion unnecessary data”) . Claim 14 of the present invention is rejected in view of claim 14 of U.S. Patent ‘215. Regarding claim 15, U.S. Patent ‘215 teaches: An information processing system comprising: a vehicle (claim 15 “a vehicle”) ; and an information terminal (claim 15 “an information terminal”) , wherein the vehicle acquires observation information of a driver of a vehicle (claim 15 “the vehicle is configured to: acquire observation information of a driver of the vehicle”) , divides the acquired observation information into conversion unnecessary data and conversion necessary data (claim 15 “divide the acquired observation information into conversion unnecessary data and conversion necessary data”) , and executes data conversion processing of at least one of abstraction processing or encryption processing for the conversion necessary data (claim 15 “execute, as a data conversion process, at least one of: an abstraction process for the conversion necessary data to generate abstraction data, or an encryption process for the conversion necessary data to generate encryption data”) and executes processing of storing conversion data of at least one of generated abstraction data and generated encryption data in a storage unit in association with identification information of the driver (claim 15 “control a memory to store the at least one of the generated abstraction data or the generated encryption data in association with identification information of the driver”) , and the information terminal acquires the abstraction data from the storage unit and displays the abstraction data on a display unit of the information terminal (claim 15 “the information terminal is configured to: acquire the abstraction data from the memory; control display of the abstraction data on the information terminal”) , and identifies the driver on a basis of the identification information of the driver associated with the displayed abstraction data (claim 15 “identify the driver based on the identification information of the driver associated with the displayed abstraction data”) . Claim 16 of the present invention is rejected in view of claim 16 of U.S. Patent ‘215. Regarding claim 17, U.S. Patent ‘215 teaches: An information processing method executed in an information processing device, the information processing method comprising: by a driver information acquisition unit, acquiring observation information of a driver of a vehicle (claim 17 “acquiring observation information of a driver of a vehicle”) ; and by a data processing unit, dividing the observation information into conversion unnecessary data and conversion necessary data (claim 17 “dividing the observation information into conversion unnecessary data and conversion necessary data”) ; and executing data conversion processing of at least one of abstraction processing or encryption processing for the conversion necessary data (claim 17 “executing, as a data conversion process, at least one of: abstraction processing for the conversion necessary data to generate abstraction data, or encryption processing for the conversion necessary data to generate encryption data”) , and storing conversion data of at least one of generated abstraction data or generated encryption data in a storage unit (claim 17 “controlling a memory to store the at least one of the generated abstraction data or the generated encryption data in association with identification information of the driver”) . Regarding claim 18, U.S. patent ‘215 teaches: An information processing method executed in an information processing system including a vehicle and an information terminal (claim 18 “ an information processing system including a vehicle and an information terminal”) , the information processing method comprising: by the vehicle, acquiring observation information of a driver of a vehicle (claim 18 “acquiring, by the vehicle, observation information of a driver of the vehicle”) ; dividing the acquired observation information into conversion unnecessary data and conversion necessary data (claim 18 “dividing, by the vehicle, the acquired observation information into conversion unnecessary data and conversion necessary data”) ; and executing data conversion processing of at least one of abstraction processing or encryption processing for the conversion necessary data (claim 18 “executing, by the vehicle, as a data conversion process, at least one of: abstraction processing for the conversion necessary data to generate abstraction data, or encryption processing for the conversion necessary data to generate encryption data”) and executing processing of storing conversion data of at least one of generated abstraction data and generated encryption data in a storage unit in association with identification information of the driver (claim 18 “controlling, by the vehicle, a memory to store, the at least one of the generated abstraction data or the generated encryption data in association with identification information of the driver”) ; and by the information terminal, acquiring the abstraction data from the storage unit and displaying the abstraction data on a display unit of the information terminal (claim 18 “acquiring, by the information terminal, the abstraction data from the memory; displaying, by the information terminal, the abstraction data on the information terminal”) ; and identifying the driver on a basis of the identification information of the driver associated with the displayed abstraction data (claim 18 “identifying the driver based on the identification information of the driver associated with the displayed abstraction data”) . Regarding claim 19, U.S. Patent ‘215 teaches: A program for causing information processing to be executed in an information processing device, the program for causing: a driver information acquisition unit to acquire observation information of a driver of a vehicle (claim 19 “acquiring observation information of a driver of a vehicle”) ; and a data processing unit to divide the observation information into conversion unnecessary data and conversion necessary data (claim 19 “dividing the observation information into conversion unnecessary data and conversion necessary data”) ; and to execute data conversion processing of at least one of abstraction processing or encryption processing for the conversion necessary data (claim 19 “executing, as a data conversion process, at least one of: abstraction processing for the conversion necessary data to generate abstraction data, or encryption processing for the conversion necessary data to generate encryption data”) , and to execute processing of storing conversion data of at least one of generated abstraction data or generated encryption data in a storage unit (claim 19 “controlling a memory to store the at least one of the generated abstraction data or the generated encryption data in association with identification information of the driver”) . 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. Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because “a program” is not a process, machine, manufacture, or composition of matter. See MPEP 2106.03. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15-03-aia AIA Claim s 1-9, 12, 17, and 19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Julian et al. (US 2021/0370879 A1), hereinafter Julian . Regarding claim 1, Julian teaches: An information processing device (Figs. 1 and 2, [0100]; [0102] “system 100”) comprising: a driver information acquisition unit ([0100] “The system 100 may include input sensors (which may include a forward-facing camera 102, a backward-facing camera 104 (which may be referred to as an inward-facing camera or driver-facing camera when deployed in a vehicle), a right-ward facing camera (not shown for simplicity), a left-ward facing camera (not shown for simplicity)…”) configured to acquire observation information of a driver of a vehicle ([0102] “The cameras (or image sensors) may be located at corresponding apertures, and the body 200 may be coupled to a vehicle through the mount 222. In this configuration, when the system 100 is coupled to the vehicle, the system 100 can capture a view of the driver of the vehicle as well as the visual field accessible from the point of view of the driver.”; [0104]) ; and a data processing unit ([0129] “privacy processor 450”) configured to input the observation information and execute data processing ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data.”) , wherein the data processing unit divides the observation information into conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] – Inferred data including user state is not converted and is transmitted to other devices) and conversion necessary data ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data... In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0152]; [0154]; [0167]; [0179] “As in FIG. 8, different regions (a driver seat region 818, a passenger seat region 812, a back seat region 814, and a roof region 816) and objects (driver face 802 and passenger face 804) may be pre-segmented to facilitate the specification of privacy settings.”; Figs. 5-9 show the hidden portions of the image correspond with conversion necessary data for privacy and the non-hidden portions of the image also correspond with unnecessary data) , and executes data conversion processing of at least one of abstraction processing (Figs. 6A, 8B, and 9B show abstraction processing of the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.””; [0179]; [0194]) or encryption processing for the conversion necessary data ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240] “As described above, a video may be “scrambled” with an encryption key. An encryption key may be used to encrypt video data in an enabled device prior to storage in local memory. The encrypted data may then be transmitted to a cloud server. At the cloud server, the encryption key may be used to return the video to an unmodified (or substantially unmodified) appearance.”) , and stores conversion data of at least one of generated abstraction data or generated encryption data in a storage unit ([0237] “] A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) . Regarding claim 2, Julian further teaches: wherein the data processing unit extracts individually-identifiable data included in the observation information as the conversion necessary data ([0126] “In one aspect, the image processor 430 receives the image data or video data, and performs image processing to obtain motion vectors or extract particular features of objects in the cab FOV 304. For example, the image processor 430 extracts outlines of face, nose, mouth, eyes, or a combination of them, and obtains motion vectors of the extracted features or other part of the driver in the cab FOV 304. Hence, the image processor 430 may operate as a face detector. The image processor 430 may store the image data, video data, modified data including extracted features or motion vectors, or any combination of them at the memory 114 shown in FIG. 1.”; [0154] “a desired privacy is selected for each of multiple regions in the image.”; [0129]; [0167]; [0179]; [0194] , and executes the data conversion processing of at least one of abstraction processing or encryption processing for the individually-identifiable data (Figs. 6A, 8B, and 9B show abstraction processing of the drivers and/or passengers in the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.””; [0179]; [0194]) . Regarding claim 3, Julian further teaches: wherein the individually-identifiable data is image data including at least a part of a body of the driver (Figs. 6A, 8B, and 9B show abstraction processing of the faces of drivers and/or passengers in the images; [0164] “If more than one face is detected, the system 100 may determine that a passenger has appeared in the vehicle. Similarly, the system 100 may detect a single face, but may compare the detected face with a different image of the driver or with a representation of previously observed features of the driver's face, etc., and may determine that there is not a match. In either case, the detection of a passenger in the vehicle may trigger the application of the associated privacy setting to the indicated portion of the image.”; [0167] “If more than one face is detected, the system 100 may determine that a passenger has appeared in the vehicle. Similarly, the system 100 may detect a single face, but may compare the detected face with a different image of the driver or with a representation of previously observed features of the driver's face, etc., and may determine that there is not a match. In either case, the detection of a passenger in the vehicle may trigger the application of the associated privacy setting to the indicated portion of the image.”; [0179]; [0194]) . Regarding claim 4, Julian further teaches: wherein the individually-identifiable data is image data including a face of the driver (Figs. 6A, 8B, and 9B show abstraction processing of the faces of drivers and/or passengers in the images; [0164] “If more than one face is detected, the system 100 may determine that a passenger has appeared in the vehicle. Similarly, the system 100 may detect a single face, but may compare the detected face with a different image of the driver or with a representation of previously observed features of the driver's face, etc., and may determine that there is not a match. In either case, the detection of a passenger in the vehicle may trigger the application of the associated privacy setting to the indicated portion of the image.”; [0167] “If more than one face is detected, the system 100 may determine that a passenger has appeared in the vehicle. Similarly, the system 100 may detect a single face, but may compare the detected face with a different image of the driver or with a representation of previously observed features of the driver's face, etc., and may determine that there is not a match. In either case, the detection of a passenger in the vehicle may trigger the application of the associated privacy setting to the indicated portion of the image.”; [0179]; [0194]) . Regarding claim 5, Julian further teaches: wherein the data processing unit extracts data for which recording processing is not permitted in personal information protection regulation as the conversion necessary data ([0194] “A privacy mode of “stick-figure” may indicate that the objects identified in the corresponding region may be replaced by stick-figure representations.”) , and executes the data conversion processing of at least one of abstraction processing or encryption processing (Figs. 6A, 8B, and 9B show abstraction processing of the drivers and/or passengers in the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.””; [0179]; [0194]) . Regarding claim 6, Julian further teaches: wherein the data processing unit stores the conversion unnecessary data in the storage unit without performing the abstraction processing or the encryption processing ([0154] “In this example, the desired privacy for the driver 502 may be set to “none” (meaning that the system may leave the portion of the FOV associated with the driver unmodified), so that the driver 502 of the vehicle may be monitored by anyone having access to the video. The desired privacy of any visible windows may be set to “none” as well, so that views of the road through any of the visible windows (such as the driver side back seat window region 506, the rear window region 508, and the passenger side back seat window region 510) may be left unmodified”; [0160]; [0167]; [0234]) . Regarding claim 7, Julian further teaches: wherein the data processing unit executes the encryption processing for the conversion necessary data, using a key known only by the driver ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240]) . Regarding claim 8, Julian further teaches: wherein the data processing unit performs the abstraction processing using skeleton data, an avatar, or a virtual model, reflecting a motion of a body of the driver, as the abstraction processing for an image of the driver included in the conversion necessary data (Figs. 8B and 9B, [0194] “A privacy mode of “stick-figure” may indicate that the objects identified in the corresponding region may be replaced by stick-figure representations. One example of a “stick-figure” representation is illustrated in FIG. 9A and FIG. 9B. The original image in FIG. 9A has been transformed so that a stick-figure representation of people and relevant object edges are outlined. A stick- figure representation may be useful for ADAS and autonomous driving systems, for example, to track or monitor the attentiveness of a driver.”) . Regarding claim 9, Julian further teaches: an environment information acquisition unit configured to acquire observation information of the vehicle ([0104] “Similarly, the backward-facing camera 104 can capture images or videos of inside of the vehicle through the aperture 204 to generate corresponding image data or video data.”) and an outside ([0104] “the forward-facing camera 102 can capture images or videos of a road ahead of the vehicle through the aperture 202 to generate corresponding image data or video data.”) , wherein the data processing unit divides the observation information acquired by the environment information acquisition unit into conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] – Inferred data including user state is not converted and is transmitted to other devices) and conversion necessary data ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data... In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0152]; [0154]; [0167]; [0179] “As in FIG. 8, different regions (a driver seat region 818, a passenger seat region 812, a back seat region 814, and a roof region 816) and objects (driver face 802 and passenger face 804) may be pre-segmented to facilitate the specification of privacy settings.”; Figs. 5-9 show the hidden portions of the image correspond with conversion necessary data for privacy and the non-hidden portions of the image also correspond with unnecessary data) , and executes data conversion processing of at least one of abstraction processing (Figs. 6A, 8B, and 9B show abstraction processing of the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.””; [0179]; [0194]) or encryption processing for the conversion necessary data included in the observation information acquired by the environment information acquisition unit ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240] “As described above, a video may be “scrambled” with an encryption key. An encryption key may be used to encrypt video data in an enabled device prior to storage in local memory. The encrypted data may then be transmitted to a cloud server. At the cloud server, the encryption key may be used to return the video to an unmodified (or substantially unmodified) appearance.”) , and stores conversion data of at least one of generated abstraction data or generated encryption data in a storage unit ([0237] “] A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) . Regarding claim 12, Julian further teaches: wherein the data processing unit stores the conversion unnecessary data acquired from the observation information, and the conversion data of at least one of the abstraction data or the encryption data of the conversion necessary data in at least one of a storage unit in the vehicle ([0237] “A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) or an external server in association with identification information of the driver ([0234]; [0238]; [0239]) . Regarding claim 17, Julian teaches: An information processing method executed in an information processing device (Figs. 1 and 2, [0100]; [0102] “system 100”) , the information processing method comprising: by a driver information acquisition unit ([0100] “The system 100 may include input sensors (which may include a forward-facing camera 102, a backward-facing camera 104 (which may be referred to as an inward-facing camera or driver-facing camera when deployed in a vehicle), a right-ward facing camera (not shown for simplicity), a left-ward facing camera (not shown for simplicity)…”) , acquiring observation information of a driver of a vehicle ([0102] “The cameras (or image sensors) may be located at corresponding apertures, and the body 200 may be coupled to a vehicle through the mount 222. In this configuration, when the system 100 is coupled to the vehicle, the system 100 can capture a view of the driver of the vehicle as well as the visual field accessible from the point of view of the driver.”; [0104]) ; and by a data processing unit ([0129] “privacy processor 450”) , dividing the observation information into conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] – Inferred data including user state is not converted and is transmitted to other devices) and conversion necessary data ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data... In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0152]; [0154]; [0167]; [0179] “As in FIG. 8, different regions (a driver seat region 818, a passenger seat region 812, a back seat region 814, and a roof region 816) and objects (driver face 802 and passenger face 804) may be pre-segmented to facilitate the specification of privacy settings.”; Figs. 5-9 show the hidden portions of the image correspond with conversion necessary data for privacy and the non-hidden portions of the image also correspond with unnecessary data) ; and executing data conversion processing of at least one of abstraction processing (Figs. 6A, 8B, and 9B show abstraction processing of the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.””; [0179]; [0194]) or encryption processing for the conversion necessary data ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240] “As described above, a video may be “scrambled” with an encryption key. An encryption key may be used to encrypt video data in an enabled device prior to storage in local memory. The encrypted data may then be transmitted to a cloud server. At the cloud server, the encryption key may be used to return the video to an unmodified (or substantially unmodified) appearance.”) , and storing conversion data of at least one of generated abstraction data or generated encryption data in a storage unit ([0237] A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) . Regarding claim 19, Julian teaches: A program for causing information processing to be executed in an information processing device ([0041] “Various embodiments disclosed herein are related to a computer program product for modifying a video.”) , the program for causing: a driver information acquisition unit ([0100] “The system 100 may include input sensors (which may include a forward-facing camera 102, a backward-facing camera 104 (which may be referred to as an inward-facing camera or driver-facing camera when deployed in a vehicle), a right-ward facing camera (not shown for simplicity), a left-ward facing camera (not shown for simplicity)…”) to acquire observation information of a driver of a vehicle ([0102] “The cameras (or image sensors) may be located at corresponding apertures, and the body 200 may be coupled to a vehicle through the mount 222. In this configuration, when the system 100 is coupled to the vehicle, the system 100 can capture a view of the driver of the vehicle as well as the visual field accessible from the point of view of the driver.”; [0104]) ; and a data processing unit ([0129] “privacy processor 450”) to divide the observation information into conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] – Inferred data including user state is not converted and is transmitted to other devices) and conversion necessary data ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data... In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0152]; [0154]; [0167]; [0179] “As in FIG. 8, different regions (a driver seat region 818, a passenger seat region 812, a back seat region 814, and a roof region 816) and objects (driver face 802 and passenger face 804) may be pre-segmented to facilitate the specification of privacy settings.”; Figs. 5-9 show the hidden portions of the image correspond with conversion necessary data for privacy and the non-hidden portions of the image correspond with unnecessary data) ; and to execute data conversion processing of at least one of abstraction processing (Figs. 6A, 8B, and 9B show abstraction processing of the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.””; [0179]; [0194]) or encryption processing for the conversion necessary data ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240] “As described above, a video may be “scrambled” with an encryption key. An encryption key may be used to encrypt video data in an enabled device prior to storage in local memory. The encrypted data may then be transmitted to a cloud server. At the cloud server, the encryption key may be used to return the video to an unmodified (or substantially unmodified) appearance.”) , and to execute processing of storing conversion data of at least one of generated abstraction data or generated encryption data in a storage unit ([0237] A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) . 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 10-11 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Julian, in view of Tayama (US 2019/0155279 A1), hereinafter Tayama . Regarding claim 10, Julian teaches: the data processing unit calculates a driver evaluation value based on a basis of the observation information ([0096] “In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] “For example, the driver behavior analyzer 445 determines the driver's motion or reaction in response to nearby traffic condition. For another example, the driver behavior analyzer 445 determines a user state of drowsiness, distracted driving, cell phone usage, attentiveness, or a combination of them based on the extracted features or motion vectors from the image processor 430.”) , and stores the calculated driver evaluation value in the storage unit as the conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”) . Julian does not specifically teach the vehicle is a vehicle capable of switching automatic driving and manual driving, and the data processing unit calculates a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving. However, in the same field of endeavor, Tayama teaches a vehicle capable of switching automatic driving and manual driving ([0016] “The present invention provides an automatic driving system for vehicles capable of switching between an automatic drive mode in which an own vehicle is caused to travel with automatic driving in accordance with a scheduled travel behavior along a scheduled travel route set in advance and a manual drive mode in which a driver performs driving manually.”) , and a data processing unit calculates a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving ([0051] “The driver's state determining unit 22 determines a degree of arousal of the driver, that is, a degree of sleepiness being whether or not the driver is asleep. The driver's state determining unit 22 extracts, from the face image data, biometric information such as a degree of eye-opening (i.e., eye opening degree), a blinking behavior (e.g., the number of times and a duration of instantaneous opening-closing of eyes), variation of a pupil diameter, eye motion, an eye-closed duration and a ratio thereof, indications regarding driver eye behaviors, a position of the head, and posture and variation thereof.”; [0054]; [0055] “Using the face image data of the driver obtained from the face image camera 28 and the body pressure data of the driver obtained from the body pressure sensors 30a , 31a at the driver's seat 26 , the driver's state determining unit 22 determines an arousal state of the driver, that is, whether the driver is aroused to a degree that manual driving can be performed or is asleep, and a degree of sleepiness.”; [0057]) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian to include the vehicle as a vehicle capable of switching automatic driving and manual driving, and to calculate a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving, as taught by Tayama, in order to prevent a risk of shifting to manual driving by own determination even though the driver is not in a state of being capable of performing manual driving, as suggested by Tayama in par. [0020]. Regarding claim 11, Julian further teaches the data processing unit calculates a driver arousal level evaluation value ... on a basis of the observation information ([0096] “In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] “For example, the driver behavior analyzer 445 determines the driver's motion or reaction in response to nearby traffic condition. For another example, the driver behavior analyzer 445 determines a user state of drowsiness, distracted driving, cell phone usage, attentiveness, or a combination of them based on the extracted features or motion vectors from the image processor 430.”) , and stores the calculated driver arousal level evaluation value in the storage unit as the conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”) . Julian does not specifically teach the data processing unit calculates a driver arousal level evaluation value that is an index value indicating whether or not the driver is in an arousal state of being able to start the manual driving. However, Tayama teaches a data processing unit calculates a driver arousal level evaluation value that is an index value indicating whether or not the driver is in an arousal state of being able to start the manual driving ([0051] “The driver's state determining unit 22 determines a degree of arousal of the driver, that is, a degree of sleepiness being whether or not the driver is asleep. The driver's state determining unit 22 extracts, from the face image data, biometric information such as a degree of eye-opening (i.e., eye opening degree), a blinking behavior (e.g., the number of times and a duration of instantaneous opening-closing of eyes), variation of a pupil diameter, eye motion, an eye-closed duration and a ratio thereof, indications regarding driver eye behaviors, a position of the head, and posture and variation thereof.”; [0054]; [0055] “Using the face image data of the driver obtained from the face image camera 28 and the body pressure data of the driver obtained from the body pressure sensors 30a , 31a at the driver's seat 26 , the driver's state determining unit 22 determines an arousal state of the driver, that is, whether the driver is aroused to a degree that manual driving can be performed or is asleep, and a degree of sleepiness.”; [0057]) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian, in view of Tayama, to calculate a driver arousal level evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving, as taught by Tayama, in order to prevent a risk of shifting to manual driving by own determination even though the driver is not in a state of being capable of performing manual driving, as suggested by Tayama in par. [0020]. Regarding claim 13, Julian teaches: A mobile device ([0077] “Throughout the disclosure, the disclosed system and method are described to be applied to an automobile such as a vehicle.”) ..., the mobile device comprising: a driver information acquisition unit ([0100] “The system 100 may include input sensors (which may include a forward-facing camera 102, a backward-facing camera 104 (which may be referred to as an inward-facing camera or driver-facing camera when deployed in a vehicle), a right-ward facing camera (not shown for simplicity), a left-ward facing camera (not shown for simplicity)…”) configured to acquire observation information of a driver of a vehicle ([0102] “The cameras (or image sensors) may be located at corresponding apertures, and the body 200 may be coupled to a vehicle through the mount 222. In this configuration, when the system 100 is coupled to the vehicle, the system 100 can capture a view of the driver of the vehicle as well as the visual field accessible from the point of view of the driver.”; [0104]) ; and a data processing unit ([0129] “privacy processor 450”) configured to input the observation information and execute data processing ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data.”) , wherein the data processing unit ([0129] “privacy processor 450”) , divides the observation information into conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] – Inferred data including user state is not converted and is transmitted to other devices) and conversion necessary data ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data... In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0152]; [0154]; [0167]; [0179] “As in FIG. 8, different regions (a driver seat region 818, a passenger seat region 812, a back seat region 814, and a roof region 816) and objects (driver face 802 and passenger face 804) may be pre-segmented to facilitate the specification of privacy settings.”; Figs. 5-9 show the hidden portions of the image correspond with conversion necessary data for privacy and the non-hidden portions of the image also correspond with unnecessary data) , executes data conversion processing of at least one of abstraction processing (Figs. 6A, 8B, and 9B show abstraction processing of the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0179]; [0194]) or encryption processing for the conversion necessary data ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240] “As described above, a video may be “scrambled” with an encryption key. An encryption key may be used to encrypt video data in an enabled device prior to storage in local memory. The encrypted data may then be transmitted to a cloud server. At the cloud server, the encryption key may be used to return the video to an unmodified (or substantially unmodified) appearance.”) , and stores conversion data of at least one of generated abstraction data or generated encryption data in a storage unit ([0237] “] A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) , and calculates a driver evaluation value ... on a basis of the observation information ([0096] “In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] “For example, the driver behavior analyzer 445 determines the driver's motion or reaction in response to nearby traffic condition. For another example, the driver behavior analyzer 445 determines a user state of drowsiness, distracted driving, cell phone usage, attentiveness, or a combination of them based on the extracted features or motion vectors from the image processor 430.”) , and stores the calculated driver evaluation value in the storage unit as the conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”) . Julian does not specifically teach the mobile device is a device capable of switching automatic driving and manual driving, and the data processing unit calculates a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving. However, in the same field of endeavor, Tayama teaches a mobile device capable of switching automatic driving and manual driving ([0016] “The present invention provides an automatic driving system for vehicles capable of switching between an automatic drive mode in which an own vehicle is caused to travel with automatic driving in accordance with a scheduled travel behavior along a scheduled travel route set in advance and a manual drive mode in which a driver performs driving manually.”) , and a data processing unit calculates a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving ([0051] “The driver's state determining unit 22 determines a degree of arousal of the driver, that is, a degree of sleepiness being whether or not the driver is asleep. The driver's state determining unit 22 extracts, from the face image data, biometric information such as a degree of eye-opening (i.e., eye opening degree), a blinking behavior (e.g., the number of times and a duration of instantaneous opening-closing of eyes), variation of a pupil diameter, eye motion, an eye-closed duration and a ratio thereof, indications regarding driver eye behaviors, a position of the head, and posture and variation thereof.”; [0054]; [0055] “Using the face image data of the driver obtained from the face image camera 28 and the body pressure data of the driver obtained from the body pressure sensors 30a , 31a at the driver's seat 26 , the driver's state determining unit 22 determines an arousal state of the driver, that is, whether the driver is aroused to a degree that manual driving can be performed or is asleep, and a degree of sleepiness.”; [0057]) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian to include the vehicle as a vehicle capable of switching automatic driving and manual driving, and to calculate a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving, as taught by Tayama, in order to prevent a risk of shifting to manual driving by own determination even though the driver is not in a state of being capable of performing manual driving, as suggested by Tayama in par. [0020]. Regarding claim 14, the teachings of Julian and Tayama have been discussed above with respect to claim 13. Julian does not specifically teach the data processing unit calculates notification timing of a manual driving recovery request notification that is a recovery request notification from the automatic driving to the manual driving for the driver on a basis of the observation information. However, Tayama teaches wherein the data processing unit calculates notification timing of a manual driving recovery request notification that is a recovery request notification from the automatic driving to the manual driving for the driver ([0025] “the method further includes providing a notification to encourage the driver to confirm readiness using a display device and/or a speaker of the own vehicle after the driver is determined as being not ready for manual driving.”) on a basis of the observation information ([0021]; [0028] “In another embodiment, the method further includes measuring elapsed time from starting of the determining of the travel behavior of the own vehicle, and switching from the automatic drive mode to the manual drive mode is cancelled when the elapsed time exceeds a specific time period.”; [0094] “Examples of the above include a case that the driver does not perform driving operation, that is, steering operation, accelerating operation, or braking operation even after a specific period of time has passed from the switching to manual driving.” – The specific period of time is calculated for cancelling the switching from the automatic driving to the manual driving after the specific period of time has elapsed, and the specific period of time would have included the notification time when notifying the driver of the switching from the automatic driving to the manual driving.) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian, in view of Tayama, to calculate notification timing of a manual driving recovery request notification that is a recovery request notification from the automatic driving to the manual driving for the driver on a basis of the observation information, as taught by Tayama, in order to perform countermeasures for safe traveling in a case that the driver is not ready for performing manual driving after a specific period of time has elapsed, as suggested by Tayama in par. [0094] . 07-21-aia AIA Claim s 15 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Julian, in view of Aguirre De Carcer et al. (US 2009/0079555 A1), hereinafter Aguirre De Carcer . Regarding claim 15, Julian teaches: An information processing system comprising: a vehicle ([0077] “Throughout the disclosure, the disclosed system and method are described to be applied to an automobile such as a vehicle.”) ; and an information terminal ([0238]-[0240] “cloud server”) , wherein the vehicle acquires observation information of a driver of a vehicle ([0102] “The cameras (or image sensors) may be located at corresponding apertures, and the body 200 may be coupled to a vehicle through the mount 222. In this configuration, when the system 100 is coupled to the vehicle, the system 100 can capture a view of the driver of the vehicle as well as the visual field accessible from the point of view of the driver.”; [0104]) , divides the acquired observation information into conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] – Inferred data including user state is not converted and is transmitted to other devices) and conversion necessary data ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data... In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0152]; [0154]; [0167]; [0179] “As in FIG. 8, different regions (a driver seat region 818, a passenger seat region 812, a back seat region 814, and a roof region 816) and objects (driver face 802 and passenger face 804) may be pre-segmented to facilitate the specification of privacy settings.”; Figs. 5-9 show the hidden portions of the image correspond with conversion necessary data for privacy and the non-hidden portions of the image also correspond with unnecessary data) , and executes data conversion processing of at least one of abstraction processing (Figs. 6A, 8B, and 9B show abstraction processing of the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0179]; [0194]) or encryption processing for the conversion necessary data ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240] “As described above, a video may be “scrambled” with an encryption key. An encryption key may be used to encrypt video data in an enabled device prior to storage in local memory. The encrypted data may then be transmitted to a cloud server. At the cloud server, the encryption key may be used to return the video to an unmodified (or substantially unmodified) appearance.”) and executes processing of storing conversion data of at least one of generated abstraction data and generated encryption data in a storage unit ([0237] “] A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) in association with identification information of the driver ([0121] “Examples of a client profile of a driver include a driver identification, associated IDMS identification, driver history, driver behavior, device attribute, and personal attribute. The driver identification identifies the driver, where the IDMS identification identifies an IDMS device associated with the driver.”) , and the information terminal acquires the abstraction data from the storage unit ([0239] “For example, unmodified video (privacy set to “none”) may be stored at a local memory, but scrambled video may be stored on a cloud server.”) ..., and identifies the driver on a basis of the identification information of the driver associated with the abstraction data ([0121]-[0122] disclose transmitting client profiles to a remote server; [0233]; [0238]; [0239]; [0240]) . Julian does not explicitly teach the information terminal includes a display unit for displaying information of the driver. However, in the same field of endeavor, Aguirre De Carcer teaches a display unit of an information terminal for displaying information of a driver ([0034] “a user interface provided by the server 40 allows remote user to interact with the mobile device 20…”; [0035]; [0038] “For example, server 40 may further include: a vehicle data receiving module 41; an external data receiving module 42; a recommendation module 43; a user interface module 44 ; processors 45; transmission module 46; and a memory module 47. It is appreciated that the above modules are in physical, wireless and/or logical communication with one another and may be implemented in the form of hardware and/or software instructions.”) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian to include a display unit for the information terminal for displaying information of a driver, as taught by Aguirre De Carcer, wherein the information is the generated abstraction data as taught in Julian, in order to allow a remote driver to interact or view information of the driver. Regarding claim 18, Julian teaches: An information processing method executed in an information processing system including a vehicle ([0077] “Throughout the disclosure, the disclosed system and method are described to be applied to an automobile such as a vehicle.”) and an information terminal ([0238]-[0240] “cloud server”) , the information processing method comprising: by the vehicle acquiring observation information of a driver of a vehicle ([0102] “The cameras (or image sensors) may be located at corresponding apertures, and the body 200 may be coupled to a vehicle through the mount 222. In this configuration, when the system 100 is coupled to the vehicle, the system 100 can capture a view of the driver of the vehicle as well as the visual field accessible from the point of view of the driver.”; [0104]) , dividing the acquired observation information into conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] – Inferred data including user state is not converted and is transmitted to other devices) and conversion necessary data ([0129] “The privacy processor 450 is a component that applies privacy screening to the image data or the video data. The privacy processor 450 may receive image data or video data, and modifies the received data to hide a portion of the FOV in the image data or the video data... In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0152]; [0154]; [0167]; [0179] “As in FIG. 8, different regions (a driver seat region 818, a passenger seat region 812, a back seat region 814, and a roof region 816) and objects (driver face 802 and passenger face 804) may be pre-segmented to facilitate the specification of privacy settings.”; Figs. 5-9 show the hidden portions of the image correspond with conversion necessary data for privacy and the non-hidden portions of the image also correspond with unnecessary data) , and executing data conversion processing of at least one of abstraction processing (Figs. 6A, 8B, and 9B show abstraction processing of the images; [0129] “In another approach, the privacy processor 450 applies privacy screening to a predetermined region of the FOV. The privacy processor 450 may apply privacy screening to blur, disable, or convert into a “stick-figure” a portion of the FOV in the image data.”; [0179]; [0194]) or encryption processing for the conversion necessary data ([0191] “In some embodiments, an encryption key may be used that corresponds to a password chosen by a relevant person. For example, a driver may have created a key which may be used to encrypt or decrypt video associated with an inward facing camera. In the aftermath of an accident, a driver may choose to share the encryption key with another party, such as a fleet manager, law enforcement authorities, and the like.”; [0240] “As described above, a video may be “scrambled” with an encryption key. An encryption key may be used to encrypt video data in an enabled device prior to storage in local memory. The encrypted data may then be transmitted to a cloud server. At the cloud server, the encryption key may be used to return the video to an unmodified (or substantially unmodified) appearance.”) and executing processing of storing conversion data of at least one of generated abstraction data and generated encryption data in a storage unit ([0237] “] A “local” storage setting may indicate that the image data (which may be a modified version of the image data, such as “scrambled”) should be stored locally in a device memory.”) in association with identification information of the driver ([0121] “Examples of a client profile of a driver include a driver identification, associated IDMS identification, driver history, driver behavior, device attribute, and personal attribute. The driver identification identifies the driver, where the IDMS identification identifies an IDMS device associated with the driver.”) , and by the information terminal, acquiring the abstraction data from the storage unit ([0239] “For example, unmodified video (privacy set to “none”) may be stored at a local memory, but scrambled video may be stored on a cloud server.”) , and identifying the driver on a basis of the identification information of the driver associated with the abstraction data ([0121]-[0122] disclose transmitting client profiles to a remote server; [0233]; [0238]; [0239]; [0240]) . Julian does not explicitly teach the information terminal includes a display unit for displaying information of the driver. However, in the same field of endeavor, Aguirre De Carcer teaches a display unit of an information terminal for displaying information of a driver ([0034] “a user interface provided by the server 40 allows remote user to interact with the mobile device 20…”; [0035]; [0038] “For example, server 40 may further include: a vehicle data receiving module 41; an external data receiving module 42; a recommendation module 43; a user interface module 44 ; processors 45; transmission module 46; and a memory module 47. It is appreciated that the above modules are in physical, wireless and/or logical communication with one another and may be implemented in the form of hardware and/or software instructions.”) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian to include a display unit for the information terminal for displaying information of a driver, as taught by Aguirre De Carcer, wherein the information is the generated abstraction data as taught in Julian, in order to allow a remote driver to interact or view information of the driver . 07-21-aia AIA Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Julian, in view of Aguirre De Carcer, and further in view of Tayama . Regarding claim 16, Julian teaches: the vehicle calculates a driver evaluation value based on a basis of the observation information ([0096] “In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”; [0128] “For example, the driver behavior analyzer 445 determines the driver's motion or reaction in response to nearby traffic condition. For another example, the driver behavior analyzer 445 determines a user state of drowsiness, distracted driving, cell phone usage, attentiveness, or a combination of them based on the extracted features or motion vectors from the image processor 430.”) , and stores the calculated driver evaluation value in the storage unit as the conversion unnecessary data ([0096] “In some examples of Active Privacy, a privacy setting may be enabled such that at least some vision-based functions may still be performed by the device. In one example, an inference may be automatically generated based on the captured video prior to the application of the Active Privacy modification. In this example, an enabled system may produce inferred information. In some embodiments, the system may not transmit the video data, but may provide the inferred data to other devices. In an IDMS, for example, inferred data may relate to a user state of drowsiness, distracted driving, cell phone usage, and the like.”) , and the information terminal acquires the driver evaluation value from the storage unit ([0121]-[0122] disclose transmitting client profiles to a remote server; [0233]; [0238]; [0239]; [0240]) . Julian does not explicitly teach the information terminal includes a display unit for displaying information of the driver. However, in the same field of endeavor, Aguirre De Carcer teaches a display unit of an information terminal for displaying information of a driver ([0034] “a user interface provided by the server 40 allows remote user to interact with the mobile device 20…”; [0035]; [0038] “For example, server 40 may further include: a vehicle data receiving module 41; an external data receiving module 42; a recommendation module 43; a user interface module 44 ; processors 45; transmission module 46; and a memory module 47. It is appreciated that the above modules are in physical, wireless and/or logical communication with one another and may be implemented in the form of hardware and/or software instructions.”) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian, in view of Aguirre De Carcer to display information of a driver on a display unit of the information terminal, as taught by Aguirre De Carcer, wherein the information is the calculated driver evaluation value as taught in Julian, in order to allow a remote driver to interact or view information of the driver. Neither Julian nor Aguirre De Carcer specifically teaches the vehicle is a vehicle capable of switching automatic driving and manual driving, and the data processing unit calculates a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving. However, in the same field of endeavor, Tayama teaches a vehicle capable of switching automatic driving and manual driving ([0016] “The present invention provides an automatic driving system for vehicles capable of switching between an automatic drive mode in which an own vehicle is caused to travel with automatic driving in accordance with a scheduled travel behavior along a scheduled travel route set in advance and a manual drive mode in which a driver performs driving manually.”) , and the vehicle calculates a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving ([0051] “The driver's state determining unit 22 determines a degree of arousal of the driver, that is, a degree of sleepiness being whether or not the driver is asleep. The driver's state determining unit 22 extracts, from the face image data, biometric information such as a degree of eye-opening (i.e., eye opening degree), a blinking behavior (e.g., the number of times and a duration of instantaneous opening-closing of eyes), variation of a pupil diameter, eye motion, an eye-closed duration and a ratio thereof, indications regarding driver eye behaviors, a position of the head, and posture and variation thereof.”; [0054]; [0055] “Using the face image data of the driver obtained from the face image camera 28 and the body pressure data of the driver obtained from the body pressure sensors 30a , 31a at the driver's seat 26 , the driver's state determining unit 22 determines an arousal state of the driver, that is, whether the driver is aroused to a degree that manual driving can be performed or is asleep, and a degree of sleepiness.”; [0057]) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Julian, in view of Aguirre De Carcer, to include the vehicle as a vehicle capable of switching automatic driving and manual driving, and to calculate a driver evaluation value that is an index value indicating whether or not the driver is in a state of being able to start the manual driving, as taught by Tayama, in order to prevent a risk of shifting to manual driving by own determination even though the driver is not in a state of being capable of performing manual driving, as suggested by Tayama in par. [0020] . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Matusek et al. (US 2017/0220816 A1) teaches an apparatus configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. Noto et al. (US 2019/0129417 A1) teaches determining whether or not the driver is in a driving capable state in which the driver can perform driving operation before transferring authority from automated driving to manual driving. Any inquiry concerning this communication or earlier communications from the examiner should be directed to NHI Q BUI whose telephone number is (571)272-3962. The examiner can normally be reached Monday - Friday: 10:00 AM - 6:00PM EST. 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, KHOI TRAN can be reached at (571) 272-6919. 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. /NHI Q BUI/ Primary Examiner, Art Unit 3656 Application/Control Number: 19/240,730 Page 2 Art Unit: 3656 Application/Control Number: 19/240,730 Page 3 Art Unit: 3656 Application/Control Number: 19/240,730 Page 4 Art Unit: 3656 Application/Control Number: 19/240,730 Page 5 Art Unit: 3656 Application/Control Number: 19/240,730 Page 6 Art Unit: 3656 Application/Control Number: 19/240,730 Page 7 Art Unit: 3656 Application/Control Number: 19/240,730 Page 8 Art Unit: 3656 Application/Control Number: 19/240,730 Page 9 Art Unit: 3656 Application/Control Number: 19/240,730 Page 10 Art Unit: 3656 Application/Control Number: 19/240,730 Page 11 Art Unit: 3656 Application/Control Number: 19/240,730 Page 12 Art Unit: 3656 Application/Control Number: 19/240,730 Page 13 Art Unit: 3656 Application/Control Number: 19/240,730 Page 14 Art Unit: 3656 Application/Control Number: 19/240,730 Page 15 Art Unit: 3656 Application/Control Number: 19/240,730 Page 16 Art Unit: 3656 Application/Control Number: 19/240,730 Page 17 Art Unit: 3656 Application/Control Number: 19/240,730 Page 18 Art Unit: 3656 Application/Control Number: 19/240,730 Page 19 Art Unit: 3656 Application/Control Number: 19/240,730 Page 20 Art Unit: 3656 Application/Control Number: 19/240,730 Page 21 Art Unit: 3656 Application/Control Number: 19/240,730 Page 22 Art Unit: 3656 Application/Control Number: 19/240,730 Page 23 Art Unit: 3656 Application/Control Number: 19/240,730 Page 24 Art Unit: 3656 Application/Control Number: 19/240,730 Page 25 Art Unit: 3656 Application/Control Number: 19/240,730 Page 26 Art Unit: 3656 Application/Control Number: 19/240,730 Page 27 Art Unit: 3656 Application/Control Number: 19/240,730 Page 28 Art Unit: 3656 Application/Control Number: 19/240,730 Page 29 Art Unit: 3656 Application/Control Number: 19/240,730 Page 30 Art Unit: 3656 Application/Control Number: 19/240,730 Page 31 Art Unit: 3656 Application/Control Number: 19/240,730 Page 32 Art Unit: 3656 Application/Control Number: 19/240,730 Page 33 Art Unit: 3656 Application/Control Number: 19/240,730 Page 34 Art Unit: 3656 Application/Control Number: 19/240,730 Page 35 Art Unit: 3656 Application/Control Number: 19/240,730 Page 36 Art Unit: 3656 Application/Control Number: 19/240,730 Page 37 Art Unit: 3656 Application/Control Number: 19/240,730 Page 38 Art Unit: 3656 Application/Control Number: 19/240,730 Page 39 Art Unit: 3656 Application/Control Number: 19/240,730 Page 40 Art Unit: 3656 Application/Control Number: 19/240,730 Page 42 Art Unit: 3656 Application/Control Number: 19/240,730 Page 43 Art Unit: 3656 Application/Control Number: 19/240,730 Page 44 Art Unit: 3656 Application/Control Number: 19/240,730 Page 45 Art Unit: 3656 Application/Control Number: 19/240,730 Page 46 Art Unit: 3656 Application/Control Number: 19/240,730 Page 47 Art Unit: 3656 Application/Control Number: 19/240,730 Page 48 Art Unit: 3656 Application/Control Number: 19/240,730 Page 49 Art Unit: 3656 Application/Control Number: 19/240,730 Page 50 Art Unit: 3656 Application/Control Number: 19/240,730 Page 51 Art Unit: 3656 Application/Control Number: 19/240,730 Page 52 Art Unit: 3656 Application/Control Number: 19/240,730 Page 53 Art Unit: 3656
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