DETAILED ACTION
This action is in response to the original filing on 08/22/2024. Claims 1-5 are pending and have been considered below.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claims 1 and 5 are objected to because of the following informalities:
Claims 1 and 5 recite ‘the type of the visual target’; however, they should recite - - a type of the visual target - -.
Appropriate correction is required.
Claim Interpretation
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.
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.
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 limitation(s) is/are: occupant assist system is configured to in claims 1-4.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/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 this/these limitation(s) 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 it/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 limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1 and 5
Step 1: Claims 1 and 5 recite a system and a method; therefore, they are directed to the statutory categories of a machine and a method.
Step 2A Prong 1: The claims recite, inter alia:
detect a target existing around the vehicle based on external environment data relating to an environment around the vehicle; detect a line-of-sight direction of the occupant based on occupant data representing a state of the occupant of the vehicle; specify a visual target viewed by the occupant based on the target and the line-of-sight direction of the occupant; based on a content of the occupant’s voice when the occupant is looking at the visual target and additional information related to the visual target, specify a requirement of the occupant for the visual target Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of specifying a visual target and specifying a requirement for the target, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of “An occupant assist system for assisting an occupant of a vehicle, wherein the occupant assist system is configured to”, and “An occupant assist method for assisting an occupant of a vehicle, comprising” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h). The claimed computer components are recited at a high level of generality and are merely invoked as tool to perform the abstract idea. The additional elements of “acquire additional information related to the visual target when the type of the visual target is a building“ amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)). The additional element of “perform an action for handling the requirement” is merely a post-solution step, a nominal addition to the claim that does not meaningfully limit the claim, and is therefore insignificant extra-solution activity (see MPEP 2106.05(g)). Even when viewed in combination, these additional element do not integrate the abstract idea into a practical application and the claims are thus directed to the abstract idea.
Step 2B: The claims do not contain significantly more than the judicial exception. The additional elements of “An occupant assist system for assisting an occupant of a vehicle, wherein the occupant assist system is configured to”, and “An occupant assist method for assisting an occupant of a vehicle, comprising” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements of “acquire additional information related to the visual target when the type of the visual target is a building” amounts to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”). The additional element of “perform an action for handling the requirement” amounts to no more than a recitation of the words "apply it" (or an equivalent) or is no more than mere instructions to implement an abstract idea or other exception on a computer (see MPEP 2106.05(f)). Nothing in the claims provides significantly more than that abstract idea. As such, the claims are ineligible.
Claims 2-4
Step 1: Claims 2-4 recite systems; therefore, they are directed to the statutory category of a machine.
Step 2: claims 2-4 merely narrow the previously recited abstract idea limitations. For the reasons described above with respect to claims 1 and 5, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea. The claims disclose similar limitations described for the independent claims above and do not provide anything more than the mental processes that are practically capable of being performed in the human mind with the assistance of pen and paper.
Claim 2 further recites the additional elements of “notify the occupant of a result that addressed the requirement”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”). The additional elements of “The occupant assist system according to claim 1, is further configured to” and “via a HMI that is capable of exchanging information between the vehicle and the occupant” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)).
Claim 3 further recites the additional elements of “when the occupant issues a voice in response to a notification of the result, specify an additional requirement based on the content of the occupant’s voice”. Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of specifying an additional requirement, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper. The additional elements of “The occupant assist system according to claim 2, is further configured to” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). The additional element of “perform an action for handling the additional requirement” is merely a post-solution step, a nominal addition to the claim that does not meaningfully limit the claim, and is therefore insignificant extra-solution activity (see MPEP 2106.05(g)).
Claim 4 further recites the additional elements of “The occupant assist system according to claim 1, wherein the requirement is a requirement related to a service provided at a store related to the visual target”. These elements amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)).
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(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.
Claims 1, 2, 4, and 5 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Suzuki et al. (US 20200251108 A1, published 08/06/2020), hereinafter Suzuki.
Regarding claim 1, Suzuki teaches the claim comprising:
An occupant assist system for assisting an occupant of a vehicle, wherein the occupant assist system is configured to: detect a target existing around the vehicle based on external environment data relating to an environment around the vehicle (Suzuki Figs. 1-15; [0060], The outside camera 118 generates data of images obtained by imaging the surroundings of the vehicle M (hereinafter referred to as second image data) and outputs the generated second image data to the agent controller 120; [0063], The acquirer 122 acquires the first image data from the inside camera 104 or acquires the second image data from the outside camera 118. The acquirer 122 acquires speech data from the microphones 106, acquires data such the direction or speed of the vehicle M from the vehicle sensor 114, or acquires position data of the vehicle M from the GNSS receiver 116; [0085], FIG. 8 is a diagram illustrating a process which is performed by the estimator 220. In the example illustrated in FIG. 8, it is assumed that the vehicle M is traveling along a lane L1 out of lanes L1 and L2 illustrated in the drawing and objects OB1 to OB4 are present near the vehicle M. FIG. 9 is a diagram illustrating an example of a passenger compartment in the traveling scene illustrated in FIG. 8. In the example illustrated in FIG. 9, it is assumed that an occupant P drives the vehicle M; [0104], the acquirer 122 acquires first image data which is captured by the inside camera 104 and second image data which is captured by the outside camera 118 (Step S102). Then, the communication controller 128 transmits the speech data, the first image data, the second image data, and position data to the server device 200 via the agent communicator 102 (Step S104).);
detect a line-of-sight direction of the occupant based on occupant data representing a state of the occupant of the vehicle; specify a visual target viewed by the occupant based on the target and the line-of-sight direction of the occupant; acquire additional information related to the visual target when the type of the visual target is a building (Suzuki Figs. 1-15; [0087], the estimator 220 performs an analysis process such as template matching on the first image data and detects one or both of a direction of a face and a direction of eyes of the occupant P from the first image data. For example, the estimator 220 extracts outline information of a head part from the first image data, performs matching with a predetermined template on the basis of arrangement information of parts (eyes, a nose, and a mouse) included in the extracted outline area, and derives a direction of a face. The estimator 220 detects a direction of eyes from a positional relationship between a reference point and a moving point in the eyes of the occupant P which is included in the first data); [0093], the estimator 220 estimates an object which is located in the estimated first direction or the estimated second direction. For example, the estimator 220 acquires POI information near the current position of the vehicle M with reference to the map information 236 on the basis of position data of the vehicle M (the position P1 in FIG. 8); [0096-0097], When a state in which there is no change after the sight direction (the first direction) of the occupant P or the direction indicated by the occupant P (the second direction) has been estimated is maintained for a first predetermined time or more, the estimator 220 stores information on the object in the direction in the server storage 230. The case of “there is no change” may include change within a predetermined range. When unclear wording is included in speech data from the occupant P which is acquired within a second predetermined time (for example, several seconds) after the sight direction or the indicated direction has changed, the estimator 220 estimates the object stored in the server storage 230 as an object corresponding to the wording. Accordingly, for example, when the occupant P utters “what is the past building?” after the occupant has watched the object OB4 in FIG. 8 for the first predetermined time or more, the “past building” can be estimated to be the object OB4 in which the line of sight of the occupant P stays long. Accordingly, the speech recognizer 216 can estimate an object corresponding to unclear wording in various scenes and more accurately recognize the whole meaning of speech content; [0098], When there are a plurality of candidate objects in the first direction or the second direction, the estimator 220 may select one more or objects which are highly associated with the occupant P out of the plurality of candidate objects with reference to the personal profile 238 stored in the server storage 230; [0099], FIG. 11 is a diagram illustrating selection of an object based on the personal profile 238. In the example illustrated in FIG. 11, it is assumed that the occupant P utters “what is that store with the brown wall?.” Then, the estimator 220 acquires “BBB Pasta (an Italian restaurant),” “CCC Bookstore,” and “DDD Shoes (a shoe store)” as candidate objects for unclear wording “that” on the basis of the position data of the vehicle M and the first direction or the second direction; [0100], the interest of the occupant P is “eating out” and “reading” and the taste of the occupant P is “Italian.” Accordingly, the estimator 220 selects BBB Pasta (an Italian restaurant) which is highly associated with the interest or taste of the occupant P as the object corresponding to the unclear wording “the.”; [0101], The estimator 220 may set priority levels of objects on the basis of the personal profile 238. In the example illustrated in FIG. 11, the estimator 220 sets the priority level of “BBB Pasta” which is most highly associated with the occupant P to be higher than those of other objects);
and, based on a content of the occupant’s voice when the occupant is looking at the visual target and additional information related to the visual target, specify a requirement of the occupant for the visual target and perform an action for handling the requirement (Suzuki Figs. 1-15; [0086], For example, when the occupant P utters “What is that building?” during traveling on the lane L1, a process of recognizing speech contents is performed by the speech recognizer 216. The determiner 218 determines whether wording corresponding to wording included in the unclear information 232 is included in wording included in the text data recognized by the speech recognizer 216. In the example, “that” corresponds to wording in the unclear information 232. Accordingly, the determiner 218 determines that unclear wording is included in the speech contents. When it is determined that unclear wording is included in the speech contents, the estimator 220 performs analysis of the first image data and acquires a sight direction (a first direction) of the occupant P. A sight direction is, for example, a direction derived from one or both of a direction of a face and a direction of eyes of the occupant P; [0094], on the basis of the semantic information “what is the object OB2?,” the agent data generator 222 generates speech data or an image as agent data on the basis of control details correlated with the semantic information with reference to the response information 234. Then, the agent data generator 222 transmits the generated data to the agent device 100 of the vehicle M. Accordingly, in response to an inquiry of the occupant P “what is that building?,” for example, synthetic speech “AAA building” is output from the speaker 108 or an image of the AAA building is displayed on the display 110; [0096], when the occupant P utters “what is that store with the brown roof?,” the estimator 220 estimates “brown” and “roof” which are wording subsequent to “that” which is determined to be unclear wording as the feature information and estimates an object having high similarity to the feature information from the surrounding image included in the second image data. The estimator 220 acquires information on objects in the first direction and the second direction from the position P1 of the vehicle M with reference to the map information 236 and extracts an object with a brown roof from the feature information of the objects; [0097], when the occupant P utters “what is the past building?” after the occupant has watched the object OB4 in FIG. 8 for the first predetermined time or more, the “past building” can be estimated to be the object OB4 in which the line of sight of the occupant P stays long. Accordingly, the speech recognizer 216 can estimate an object corresponding to unclear wording in various scenes and more accurately recognize the whole meaning of speech content; see also [0098-0102])
Regarding claim 5, claim 5 contains substantially similar limitations to those found in claim 1. Consequently, claim 1 is rejected for the same reasons.
Regarding claim 2, Suzuki teaches all the limitations of claim 1, further comprising:
The occupant assist system according to claim 1, is further configured to notify the occupant of a result that addressed the requirement via a HMI that is capable of exchanging information between the vehicle and the occupant (Suzuki Figs. 1-15; [0094], on the basis of the semantic information “what is the object OB2?,” the agent data generator 222 generates speech data or an image as agent data on the basis of control details correlated with the semantic information with reference to the response information 234. Then, the agent data generator 222 transmits the generated data to the agent device 100 of the vehicle M. Accordingly, in response to an inquiry of the occupant P “what is that building?,” for example, synthetic speech “AAA building” is output from the speaker 108 or an image of the AAA building is displayed on the display 110; [0105], the agent communicator 102 receives agent data corresponding to the speech data from the server device 200 (Step S106). The output controller 126 provides information to the occupant by outputting information based on the received agent data using the speakers 108 or the displays 110 (Step S108); see also [0086], [0096-0097])
Regarding claim 4, Suzuki teaches all the limitations of claim 1, further comprising:
The occupant assist system according to claim 1, wherein the requirement is a requirement related to a service provided at a store related to the visual target (Suzuki Figs. 1-15; [0094], on the basis of the semantic information “what is the object OB2?,” the agent data generator 222 generates speech data or an image as agent data on the basis of control details correlated with the semantic information with reference to the response information 234. Then, the agent data generator 222 transmits the generated data to the agent device 100 of the vehicle M. Accordingly, in response to an inquiry of the occupant P “what is that building?,” for example, synthetic speech “AAA building” is output from the speaker 108 or an image of the AAA building is displayed on the display 110; [0098], When there are a plurality of candidate objects in the first direction or the second direction, the estimator 220 may select one more or objects which are highly associated with the occupant P out of the plurality of candidate objects with reference to the personal profile 238 stored in the server storage 230; [0099], FIG. 11 is a diagram illustrating selection of an object based on the personal profile 238. In the example illustrated in FIG. 11, it is assumed that the occupant P utters “what is that store with the brown wall?.” Then, the estimator 220 acquires “BBB Pasta (an Italian restaurant),” “CCC Bookstore,” and “DDD Shoes (a shoe store)” as candidate objects for unclear wording “that” on the basis of the position data of the vehicle M and the first direction or the second direction; [0100], the interest of the occupant P is “eating out” and “reading” and the taste of the occupant P is “Italian.” Accordingly, the estimator 220 selects BBB Pasta (an Italian restaurant) which is highly associated with the interest or taste of the occupant P as the object corresponding to the unclear wording “the.”; [0101], The estimator 220 may set priority levels of objects on the basis of the personal profile 238. In the example illustrated in FIG. 11, the estimator 220 sets the priority level of “BBB Pasta” which is most highly associated with the occupant P to be higher than those of other objects; see also [0086], [0096-0097])
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Suzuki in view of Ishikawa et al. (US 20180136002 A1, published 05/17/2018).
Regarding claim 3, Suzuki teaches all the limitations of claim 2. However, Suzuki fails to expressly disclose The occupant assist system according to claim 2, is further configured to, when the occupant issues a voice in response to a notification of the result, specify an additional requirement based on the content of the occupant’s voice and perform an action for handling the additional requirement. In the same field of endeavor, Ishikawa teaches:
The occupant assist system according to claim 2, is further configured to, when the occupant issues a voice in response to a notification of the result, specify an additional requirement based on the content of the occupant’s voice and perform an action for handling the additional requirement (Ishikawa Figs. 1-7; [0061], the landmark recording module 408 carries out the process of recording a landmark within an image and its associated metadata in response to an intentional operation made by the user (i.e., a user selection trigger); [0062], Once the landmark recording module 408 receives a trigger, the landmark recording module 408 identifies landmarks within the image data received from the image recording module 404 and tags the landmarks with route metadata (i.e., the landmark is registered). In some embodiments, the landmark recording module 408 uses known image recognition techniques to identify candidate landmarks within the image data. In some embodiments, the landmark recording module 408 presents the candidate landmarks to the user for confirmation. In some embodiments, the landmark recording module 408 elicits voice-based confirmations from the user during the candidate landmark approval process. For example, the landmark recording module 408 can ask the user, “It is this yellow building on the right, isn't it?.”; [0064], when an utterance “that sign” is made, a candidate of a sign that serves as a landmark is selected from target objects near the direction of the line of sight of the driver and the candidate landmark is presented to the driver. In some embodiments, the tendency of a user to select landmarks of a particular type or of a particular quality (e.g., route metadata) can be learned using machine learning techniques and a candidate landmark of that type can be preferentially presented. In this manner, the landmark recording module 408 can adapt to particular users to improve the selection of personalized landmarks. For example, signs are preferentially presented as candidate landmarks to a driver who frequently selects signs as route landmarks, and buildings having particular colors, hue, and brightness characteristics are preferentially presented to a driver who frequently selects buildings having those particular colors, hue, and brightness as landmarks; [0076], As shown at block 506, the user approves the presentation of candidate landmarks (e.g., “Yes, present landmarks.”). In response, at block 508 the landmark recording module 408 presents the first candidate landmark on a display of the presentation module 422 according to one or more embodiments; [0077], As shown at block 510, the user rejects the first candidate landmark (e.g., “That's not so visible. Are there other candidates?”). In response, at block 512 the landmark recording module 408 presents a second candidate landmark on the display (e.g., “How about this sign?”); [0079], As shown at block 518, the user accepts the third candidate landmark (e.g., “Ah, I remember this. I'll take it.”). In response, at block 520 the landmark recording module 408 presents candidate metadata to the user (“Yellow, two-story building.”); [0080], As shown at block 522 the user accepts the candidate metadata (“Yes, that is correct.”). In response, at block 524 the landmark recording module 408 tags the third candidate landmark with the accepted route metadata, stores the landmark in the image and landmark database 406, and informs the user (“The yellow, two-story building has been saved as a landmark.”) according to one or more embodiments.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated The occupant assist system according to claim 2, is further configured to, when the occupant issues a voice in response to a notification of the result, specify an additional requirement based on the content of the occupant’s voice and perform an action for handling the additional requirement as suggested in Ishikawa into Suzuki. Doing so would be desirable because driving assistant systems and computer-implemented methods for improving landmark-based route guidance are provided (see Ishikawa abs.). These aspects of the invention constitute technical features that yield the technical effect of tagging a route with adaptive landmarks that avoids the need for manually populating a database with landmark data and the technical effect of using a machine learning technique to progressively improve landmark selection by identifying and storing preferred landmark types for future use. As a result of these technical features and technical effects, a driving assistant system in accordance with embodiments of the present invention represents an improvement to existing landmark-based route guidance. It should be appreciated that the above examples of technical features, technical effects, and improvements to technology are merely illustrative embodiments of the invention and are not exhaustive (see Ishikawa [0022]). The system of Ishikawa can improve gaze-based landmark selection (see Ishikawa [0064]). The system of Ishikawa would improve the system of Suzuki by enabling the user to provide voice confirmations of landmark identification, when there may be multiple possible landmarks (see Ishikawa [0062-0063] and Suzuki [0098]), thereby providing a simple and user friendly method of ensuring the user’s desired landmark is selected
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Maeng (US 20210110815 A1) see Figs. 1-7 and [0177].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN T REPSHER III whose telephone number is (571)272-7487. The examiner can normally be reached Monday - Friday, 8AM-5PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer Welch can be reached at (571) 272-7212. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOHN T REPSHER III/ Primary Examiner, Art Unit 2143
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