DETAILED ACTION
Claims 1-10 are pending.
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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on September 5, 2024 and January 16, 2026 have been considered by the examiner.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
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:
“two-dimensional acquisition unit” in claims 1, 6, 7, 9, and 10,
“three-dimensional acquisition unit” in claims 1 and 7-10,
“extraction target region setting unit” in claim 1,
“object image extraction unit” in claim 1,
“object recognition unit” in claims 2-5,
“notification unit” in claim 4,
“self-localization unit” in claims 5 and 7, and
“scan direction designation unit” in claim 7.
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.
NOTE: It should be noted the respective dependent claims do not alter or eliminate the 35 USC 112(f) interpretation.
NOTE: Additionally, in relation to the 35 USC 112(f) interpretation as noted above, corresponding 35 USC 112(b) and 35 USC 112(a) rejections were considered for each interpretation. Upon review of the specification, it was determined that the terms did not need corresponding 35 USC 112(b) and 35 USC 112(a) rejections as noted below:
Term
Structure/Algorithm (when computer-implemented)
"two-dimensional acquisition unit"
Structure:
"In Fig. 3, the three-dimensional data acquisition unit 103 and the two-dimensional data acquisition unit 104 are physical hardware such as sensors," ([0022])
"three-dimensional acquisition unit"
Structure:
"In Fig. 3, the three-dimensional data acquisition unit 103 and the two-dimensional data acquisition unit 104 are physical hardware such as sensors," ([0022])
"extraction target region setting unit"
Structure:
"Further, elements that are illustrated in the drawings as functional blocks for performing various kinds of processing may be configured by a central processing unit (CPU)…" ([0011])
Algorithm:
"The extraction target region setting unit 12 outputs two-dimensional coordinates of a region including point cloud data in which distance information of the three-dimensional data is within a preset recognition section as extraction target region coordinates. That is, the extraction target region coordinates are two-dimensional coordinates of a portion where an object exists in a range of the recognition section." ([0017])
"The extraction target region setting processing is processing performed by the extraction target region setting unit 12 to output two-dimensional coordinates of a region including point cloud data in which distance information of the three-dimensional data is within a preset recognition section as extraction target region coordinates." ([0023])
"Then, the image processing apparatus 1 uses the extraction target region setting unit 12 to set two-dimensional coordinates of point cloud data obtained from an object at a distance of a recognition section, which is a predetermined distance from a capturing position, as extraction target region coordinates (step S 12)." ([0025])
"object image extraction unit"
Structure:
"Further, elements that are illustrated in the drawings as functional blocks for performing various kinds of processing may be configured by a central processing unit (CPU)…" ([0011])
Algorithm:
"the object image extraction unit 14 extracts, as the object image, an image of a range slightly wider than the range designated by the extraction target region coordinates in consideration of such a difference in the number of pixels when extracting the object image from the image." ([0019])
"The object image extraction processing is processing performed by the object image extraction unit 14 to extract an image of the region corresponding to the extraction target region coordinates from the image as an object image." ([0023])
"Thereafter, the image processing apparatus 1 grasps a position of an object to be detected in the two-dimensional data on the basis of the extraction target region coordinates, and cuts out an object image including the object to be detected from the two-dimensional data (step S14). Then, the object image extraction unit 14 outputs the object image, whereby the operation of outputting one object image is completed (step S15)." ([0025])
"object recognition unit"
Structure:
"Further, elements that are illustrated in the drawings as functional blocks for performing various kinds of processing may be configured by a central processing unit (CPU)…" ([0011])
Algorithm:
"The object recognition unit 21 recognizes an object included in an object image. Further, the object recognition unit 21 may recognize an object in consideration of extraction target region coordinates when recognizing the object. For example, the object recognition unit 21 can recognize an object to be recognized by comparing the object with a detection target candidate registered in advance, or can perform recognition using artificial intelligence." ([0028])
"the object recognition unit 21 recognizes, as the object, at least one of a signal (for example, an obstruction warning indicator) disposed in a capturing range of a two-dimensional data acquisition unit, a rock, a fallen tree, or a person existing in a restricted area set for the capturing range of the two-dimensional data acquisition unit." ([0029])
"In step S21, the object recognition unit 21 recognizes an object using the object image output in step S15. Then, if the recognized object is a signal (YES branch in step S22), the object recognition unit 21 recognizes a light emission pattern from an image corresponding to the signal, and notifies a driver of a recognition result of the light emission pattern using the notification unit 22 (steps S22 to S24). On the other hand, if the recognized object is other than the signal (NO branch in step S22), the object recognition unit 21 issues a warning to the driver when the object corresponds to a foreign substance for which a warning needs to be issued (YES branch in step S25, step S26), and ends the operation without issuing a warning when the object is a thing that does not require any warning (NO branch in step S25)." ([0032])
"The object recognition unit 33 switches a candidate list in which an object to be recognized is described according to the self-localization information. The image processing apparatus 3 is mounted on a moving body, and it can be considered that a type of object that needs to be recognized varies depending on a geographical position of the moving body. Thus, the object recognition unit 33 can shorten a processing time by switching the candidate list in which things to be recognized are listed on the basis of the self-localization information." ([0038])
"In step S33, the object recognition unit 33 grasps a position of an object to be detected in two-dimensional data on the basis of the self-localization information and extraction target region coordinates, and cuts out an object image including the object to be detected from the two-dimensional data." ([0041])
"notification unit"
Structure:
"Further, elements that are illustrated in the drawings as functional blocks for performing various kinds of processing may be configured by a central processing unit (CPU)…" ([0011])
Algorithm:
"The notification unit 22 notifies information regarding the object recognized by the object recognition unit 21." ([0028])
"The notification unit 22 notifies a person or a device that receives a notification, such as a driver, of a recognition result on the basis of the object or the light emission pattern recognized by the object recognition unit 21. Here, various devices such as a railway operation control system and a vehicle brake can be considered as the device that receives the notification." ([0029])
"self-localization unit"
Structure:
"Further, elements that are illustrated in the drawings as functional blocks for performing various kinds of processing may be configured by a central processing unit (CPU)…" ([0011])
Algorithm:
"The self-localization unit 31 estimates a current position of the own apparatus and outputs self-localization information. The self-localization unit 31 outputs, for example, position information acquired using an apparatus such as a GPS and a current position of a vehicle on which the image processing apparatus 3 is mounted as the self-localization information." ([0036])
"scan direction designation unit"
Structure:
"Further, elements that are illustrated in the drawings as functional blocks for performing various kinds of processing may be configured by a central processing unit (CPU)…" ([0011])
Algorithm:
"The scan direction designation unit 32 designates a direction in which two-dimensional data is to be acquired and a direction in which three-dimensional data is to be acquired. More specifically, the scan direction designation unit 32 grasps a current geographical position of the own apparatus from the self-localization information, and gives an orientation control instruction to the three-dimensional data acquisition unit 11 and the two-dimensional data acquisition unit 13 such that the three-dimensional data acquisition unit 11 and the two-dimensional data acquisition unit 13 are oriented in a capturing direction associated with the grasped position." ([0037])
"Further, in a case where a direction of an object to be detected can be estimated by a recognition result of the object recognition unit 33, the scan direction designation unit 32 designates the direction in which two-dimensional data is to be acquired and the direction in which three-dimensional data is to be acquired using the result thereof." ([0037])
"Then, in the image processing apparatus 3, the scan direction designation unit 32 designates scan directions of the three-dimensional data acquisition unit 11 and the two-dimensional data acquisition unit 13 using the self-localization information (step S32)." ([0040])
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Ichiki (U.S. Publication No. US 20230267746 A1) ("Ichiki") in view of Handa U.S. Publication No. US 20230152441 A1) ("Handa").
Regarding claim 1, Ichiki discloses an image processing apparatus (Fig. 3, element 201; [0115-0118], wherein images are obtained and processed in the information processing system 201 (i.e. image processing apparatus)) comprising:
a two-dimensional data acquisition unit that acquires an image that is two-dimensional data (Fig. 3, element 211; [0117-0118] and [0133], wherein a camera 211 (i.e. two-dimensional data acquisition unit) captures an image (i.e. two-dimensional data));
a three-dimensional data acquisition unit that acquires three-dimensional data for at least a partial region of a range captured as the image (Fig. 3, element 212; [0119] and [0132-0134], wherein a LiDAR 212 (i.e. three-dimensional data acquisition unit) senses and scans a region (at least part of the sensing range overlaps an imaging range of the camera) in front of the vehicle and generates point cloud data indicating the direction and distance of each measurement point (i.e. three-dimensional data));
an extraction target region setting unit that outputs two-dimensional coordinates of a region including point cloud data ([0122-0125], [0178-0181], and [0192-0195], wherein an object region detecting unit 221 detects an object region on the basis of the point cloud data, and associates each detected object region with a corresponding region within the captured image by calculating two-dimensional coordinates of that region in the camera coordinate system (i.e. extraction target region coordinates)) in which distance information of the three-dimensional data is within a preset recognition section ([0150], [0171-0175], [0182], and [0193-0194], wherein the object region detection unit 221 detects the object region based on distributions of elevation angles and distances to the measurement points within each region, identifying ranges within which an object is present at a predetermined distance (i.e. distance information of the three-dimensional data is within a preset recognition section), and that the detection result defines the region in the captured image from which object recognition is to be performed) as extraction target region coordinates.
Ichiki additionally teaches an object image extraction unit that extracts a target object region from the image (Fig. 21-22; [0190-0196] and [0211], wherein the object recognition unit 222 sets a recognition range R31 in the captured image on the basis of the target object region detection result with predetermined margins ([0193-0194]). The recognition range defines the portion of the captured image that is extracted). However, Ichiki fails to specifically teach an object image extraction unit that extracts an image of the region corresponding to the extraction target region coordinates from the image as an object image (emphasis added). Handa, on the other hand, teaches extracting an image portion of the detection target candidate from the image data and transferring the extracted image to the identification section. More specifically and as it relates to the applicant’s claims, Handa discloses an object image extraction unit that extracts an image of the region corresponding to the extraction target region coordinates from the image as an object image ([0047] and [0115-0116], wherein an image portion of the detection target candidate (i.e. extraction target region coordinates) is extracted from the image data and the extracted image is transferred to the identification section).
Handa is combinable with Ichiki because they are from the same art of image processing.
The suggestion/motivation for doing so would have been to reduce the load of the information processing device (Handa, [0062]).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate an object image extraction unit that extracts an image of the region corresponding to the extraction target region coordinates from the image as an object image, as taught by Handa, into the image processing apparatus, as taught by Ichiki, to obtain the invention as specified in claim 1.
Regarding claim 8, Ichiki and Handa disclose the image processing apparatus according to claim 1. Ichiki additionally discloses wherein the three-dimensional data acquisition unit outputs point cloud data that is a set of measurement points whose values change according to a magnitude of a distance (Fig. 3, element 212; [0119] and [0132-0134], wherein a LiDAR 212 (i.e. three-dimensional data acquisition unit generates point cloud data indicating the direction and distance of each measurement point (i.e. set of measurement points), which changes depending on the time required for the reception of the reflected light (i.e. values change according to a magnitude of a distance)).
Regarding claim 9, Ichiki discloses a non-transitory computer readable medium recording an image processing program (Fig. 29; [0066] and [0232-0236], wherein the processing program is installed on a computer including ROM and the program may be recorded on a removable medium such as a magnetic disk or optical disk (i.e. non-transitory computer readable medium recording an image processing program)) for causing an arithmetic unit to execute:
two-dimensional data acquisition processing of acquiring an image that is two-dimensional data acquired by a two-dimensional data acquisition unit; (Fig. 3, element 211; [0117-0118] and [0133], wherein a camera 211 (i.e. two-dimensional data acquisition unit) captures an image (i.e. two-dimensional data));
three-dimensional data acquisition processing of acquiring three-dimensional data output by a three-dimensional data acquisition unit for at least a partial region of a range captured as the image; (Fig. 3, element 212; [0119] and [0132-0134], wherein a LiDAR 212 (i.e. three-dimensional data acquisition unit) senses and scans a region (at least part of the sensing range overlaps an imaging range of the camera) in front of the vehicle and generates point cloud data indicating the direction and distance of each measurement point (i.e. three-dimensional data));
extraction target region setting processing of outputting two-dimensional coordinates of a region including point cloud data ([0122-0125], [0178-0181], and [0192-0195], wherein an object region detecting unit 221 detects an object region on the basis of the point cloud data, and associates each detected object region with a corresponding region within the captured image by calculating two-dimensional coordinates of that region in the camera coordinate system (i.e. extraction target region coordinates)) in which distance information of the three-dimensional data is within a preset recognition section ([0150], [0171-0175], [0182], and [0193-0194], wherein the object region detection unit 221 detects the object region based on distributions of elevation angles and distances to the measurement points within each region, identifying ranges within which an object is present at a predetermined distance (i.e. distance information of the three-dimensional data is within a preset recognition section), and that the detection result defines the region in the captured image from which object recognition is to be performed) as extraction target region coordinates.
Ichiki additionally teaches extracting a target object image from the image (Fig. 21-22; [0190-0196] and [0211], wherein the object recognition unit 222 sets a recognition range R31 in the captured image on the basis of the target object region detection result with predetermined margins ([0193-0194]). The recognition range defines the portion of the captured image that is extracted). However, Ichiki fails to specifically teach object image extraction processing of extracting an image of the region corresponding to the extraction target region coordinates from the image as an object image (emphasis added). Handa, on the other hand, teaches extracting an image portion of the detection target candidate from the image data and transferring the extracted image to the identification section. More specifically and as it relates to the applicant’s claims, Handa discloses object image extraction processing of extracting an image of the region corresponding to the extraction target region coordinates from the image as an object image ([0047] and [0115-0116], wherein an image portion of the detection target candidate (i.e. extraction target region coordinates) is extracted from the image data and the extracted image is transferred to the identification section).
Handa is combinable with Ichiki because they are from the same art of image processing.
The suggestion/motivation for doing so would have been to reduce the load of the information processing device (Handa, [0062]).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate an object image extraction unit that extracts an image of the region corresponding to the extraction target region coordinates from the image as an object image, as taught by Handa, into the image processing apparatus, as taught by Ichiki, to obtain the invention as specified in claim 9.
Regarding claim 10, Ichiki discloses an image processing method (Fig. 3 and 5; Abstract; [0008], wherein the information processing method starts with acquiring a captured image) for causing an arithmetic unit to execute:
two-dimensional data acquisition processing of acquiring an image that is two-dimensional data acquired by a two-dimensional data acquisition unit; (Fig. 3, element 211; [0117-0118] and [0133], wherein a camera 211 (i.e. two-dimensional data acquisition unit) captures an image (i.e. two-dimensional data));
three-dimensional data acquisition processing of acquiring three-dimensional data output by a three-dimensional data acquisition unit for at least a partial region of a range captured as the image; (Fig. 3, element 212; [0119] and [0132-0134], wherein a LiDAR 212 (i.e. three-dimensional data acquisition unit) senses and scans a region (at least part of the sensing range overlaps an imaging range of the camera) in front of the vehicle and generates point cloud data indicating the direction and distance of each measurement point (i.e. three-dimensional data));
extraction target region setting processing of outputting two-dimensional coordinates of a region including point cloud data ([0122-0125], [0178-0181], and [0192-0195], wherein an object region detecting unit 221 detects an object region on the basis of the point cloud data, and associates each detected object region with a corresponding region within the captured image by calculating two-dimensional coordinates of that region in the camera coordinate system (i.e. extraction target region coordinates)) in which distance information of the three-dimensional data is within a preset recognition section ([0150], [0171-0175], [0182], and [0193-0194], wherein the object region detection unit 221 detects the object region based on distributions of elevation angles and distances to the measurement points within each region, identifying ranges within which an object is present at a predetermined distance (i.e. distance information of the three-dimensional data is within a preset recognition section), and that the detection result defines the region in the captured image from which object recognition is to be performed) as extraction target region coordinates.
Ichiki additionally teaches extracting a target object image from the image (Fig. 21-22; [0190-0196] and [0211], wherein the object recognition unit 222 sets a recognition range R31 in the captured image on the basis of the target object region detection result with predetermined margins ([0193-0194]). The recognition range defines the portion of the captured image that is extracted). However, Ichiki fails to specifically teach object image extraction processing of extracting an image of the region corresponding to the extraction target region coordinates from the image as an object image (emphasis added). Handa, on the other hand, teaches extracting an image portion of the detection target candidate from the image data and transferring the extracted image to the identification section. More specifically and as it relates to the applicant’s claims, Handa discloses object image extraction processing of extracting an image of the region corresponding to the extraction target region coordinates from the image as an object image ([0047] and [0115-0116], wherein an image portion of the detection target candidate (i.e. extraction target region coordinates) is extracted from the image data and the extracted image is transferred to the identification section).
Handa is combinable with Ichiki because they are from the same art of image processing.
The suggestion/motivation for doing so would have been to reduce the load of the information processing device (Handa, [0062]).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate an object image extraction unit that extracts an image of the region corresponding to the extraction target region coordinates from the image as an object image, as taught by Handa, into the image processing apparatus, as taught by Ichiki, to obtain the invention as specified in claim 10.
Allowable Subject Matter
Claims 2-7 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 2, the primary reason for indication of allowable subject matter is that the prior art fails to teach or reasonably suggest an object recognition unit that recognizes an object included in the object image, in combination with the other elements of the claim.
The closest prior art, Ichiki (U.S. Publication No. US 20230267746 A1), teaches recognizing traffic lights or people on the basis of a target object region and its coordinates. However, more specifically, Ichiki does not teach the “structure” (i.e. algorithm) of “switching the candidate list in which things to be recognized are listed on the basis of the self-localization information” (See [0038] of the specification) associated with the 112(f) limitations for an “object recognition unit”.
Further, it should be noted that claim 2 is interpreted under 35 U.S.C. 112(f) thus, “Therefore, the broadest reasonable interpretation of a claim limitation that invokes 35 U.S.C. 112(f) is the structure, material or act described in the specification as performing the entire claimed function and equivalents to the disclosed structure, material or act. As a result, section 112(f) limitations will, in some cases, be afforded a more narrow interpretation than a limitation that is not crafted in “means plus function” format (See MPEP 2181).”
Claims 3-6 are dependent upon dependent claim 2, with indication of allowable subject matter. Therefore, claims 3-6 also have indication of allowable subject matter.
Regarding claim 7, the primary reason for indication of allowable subject matter is that the prior art fails to teach or reasonably suggest a scan direction designation unit that designates a direction in which the two-dimensional data is to be acquired and a direction in which the three-dimensional data is to be acquired, wherein the two-dimensional data acquisition unit and the three-dimensional data acquisition unit acquire data in the directions designated by the scan direction designation unit, in combination with the other elements of the claim.
The closest prior arts, Ichiki (U.S. Publication No. US 20230267746 A1) and Shashua et al. (U.S. Publication No. US 20170010618 A1) teach the following:
Ichiki teaches a self-position estimation unit that outputs the estimated self-position of the vehicle. Ichiki also teaches a scanning control unit that controls the scanning direction of the camera and LiDAR sensor. Shashua teaches turning the car so that the sensors’ capturing direction is oriented relative to a local coordinate system associated with the vehicle. However, more specifically, Ichiki and Shashua does not teach the “structure” (i.e. algorithm) of “[grasping] a current geographical position of the own apparatus from the self-localization information, and gives an orientation control instruction to the three-dimensional data acquisition unit and the two-dimensional data acquisition unit” (See [0037] of the specification) associated with the 112(f) limitations for a “scanning control unit”.
Further, it should be noted that claim 7 is interpreted under 35 U.S.C. 112(f) thus, “Therefore, the broadest reasonable interpretation of a claim limitation that invokes 35 U.S.C. 112(f) is the structure, material or act described in the specification as performing the entire claimed function and equivalents to the disclosed structure, material or act. As a result, section 112(f) limitations will, in some cases, be afforded a more narrow interpretation than a limitation that is not crafted in “means plus function” format (See MPEP 2181).”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RACHEL Y DANG whose telephone number is (571)438-9519. The examiner can normally be reached Monday - Thursday: 7am - 4:30pm.
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/RACHEL Y DANG/Examiner, Art Unit 2661
/JOHN VILLECCO/Supervisory Patent Examiner, Art Unit 2661
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