DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Response to Amendment
Applicant’s remarks, filed 05/20/2026, regarding the objections made to the claims submitted in the non-final office action dated 03/24/2026 are withdrawn due to the amendments made to the claims.
Response to Arguments
Applicant’s arguments, see remarks filed 05/20/2026, with respect to the claims 1-15 have been fully considered but are moot because the arguments do not apply to the new combinations of the prior arts on record being used in the current rejection and the amendment necessitated new grounds of rejections.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 6, and associated dependent claims are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claims 1 and 6 recite the limitation “the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor” in Line 8-10 and Line 6-8, respectively. The office find the terms “aligned with other” rendering the claim indefinite. It is not clear what the applicant refers to as “aligned with other”, whether or not it is the plurality of regions that are aligned with each other, the plurality of regions that are aligned with other predetermined distances, or something else. For purpose of examination, the examiner is interpreting the limitation as “the reflection intensity values being accumulated for each of a plurality of regions that are aligned with each other and positioned at predetermined distances away from the imaging sensor”. The office respectfully requests the Applicant to amend claims 1 and 6 in order to clarify the claimed invention and clearly indicate where in the specification support for the amendment can be found to aid in prosecution.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 6, and 8 are rejected under 35 U.S.C. 103 as being unpatentable over BABA (US 20170294123 A1), hereinafter referenced as BABA, in view of SANO et al. (US 20200019792 A1), hereinafter referenced as SANO.
Regarding claim 1, BABA explicitly teaches an object detection device comprising (Fig. 1A, #1 called a collision mitigation apparatus. Paragraph [0023]):
an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object (Fig. 1A, illustrates an estimation circuit, called collision mitigation apparatus #1. Paragraphs [0033-0034]-BABA discloses based on one or more radar signals, the collision mitigation ECU 7 identifies an object and calculates (or determines) a linear distance from the own vehicle to the object and a horizontal azimuth angle of the object (i.e., an angular position of the object from the direction ahead of the own vehicle). Based on these calculated values, the collision mitigation ECU 7, as shown in FIG. 3, calculates or determines position coordinates (X- and Y-coordinates) of the object in the XY-plane as a detection point Pr of the object in the XY-plane.),
the first distance being measured by one or more range finders (Fig. 1A, #2 called millimeter-wave radar. Paragraph [0033]-BABA discloses the collision mitigation ECU 7 detects an object based on a radar signal transmitted from the millimeter-wave radar 2 (i.e., detection information from the millimeter-wave radar 2) (step S110). More specifically, based on one or more radar signals, the collision mitigation ECU 7 identifies an object and calculates (or determines) a linear distance from the own vehicle to the object (wherein the radar is a range finder).),
the azimuth (Fig. 4, azimuth denoted with θi. Paragraph [0045]) being estimated from an image of the object acquired by an imaging sensor (Fig. 4. Paragraph [0045]-BABA discloses the accuracy in detecting an azimuth of an object by image processing of a captured image acquired from the monocular camera 3 is likely to be higher than the accuracy in detecting an azimuth of the object by the millimeter-wave radar 2. Meanwhile, the accuracy in detecting a distance to the object by image processing of the captured image acquired from the monocular camera 3 is likely to be lower than the accuracy in detecting a distance to the object by the millimeter-wave radar 2. For example, as shown in FIG. 4, positions of upper and lower body parts of a pedestrian may be used to determine an azimuth of the pedestrian from a captured image. Thus, the azimuth θi of the pedestrian with respect to the front of the vehicle can be relatively accurately determined.);
BABA fails to explicitly teach an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and an extraction circuit which, in operation, extracts a second position of the object from the accumulation result.
However, SANO explicitly teaches an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times (Fig. 2 and 7. Paragraph [0021]-SANO discloses the surrounding sensor group 1 includes a plurality of Laser Range Finders (LRFs) 101 and 102 and a plurality of cameras 201 and 202, for example. The Laser Range Finders (LRFs) 101 and 102 are respectively configured to detect a distance and azimuth to a target by receiving light reflected from the target to which laser light is emitted. The cameras 201 and 202 are configured to capture surroundings of the vehicle V, and obtain the digital image capable of image processing. Thus, the surrounding sensor group 1 is composed of a plurality of sensors respectively configured to detect targets present in surroundings of the vehicle V.),
the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other (Fig. 8-9, illustrate regions that are aligned with each other. Paragraph [0021]-SANO discloses the Laser Range Finders (LRFs) 101 and 102 are respectively configured to detect a distance and azimuth to a target by receiving light reflected from the target to which laser light is emitted. Further in paragraph [0042]-SANO discloses the straight line extracting unit 34 approximates straight lines (N2 and N3) with respect to the target position data (72 and 73) indicating the traveling lane boundary shown in FIG. 9. The target position selection unit 35 measures the respective distances in a vehicle width direction from the vehicle V to the respective straight lines (N2 and N3).) and positioned at predetermined distances away from the imaging sensor (Fig. 2. Paragraph [0022]-SANO discloses the LRFs 101 and 102 are configured to scan laser light at a predetermined scan angle (e.g., 90 degrees) so that a track of the laser light to be emitted may, for example, form a vertical plane with respect to a road surface as a rotation axis along a front-back direction D of the vehicle V. Consequently, the LRFs 101 and 102 can detect targets, such as curbs or the like, which are present in a right-left direction of the vehicle V. The LRFs 101 and 102 are configured to sequentially output a shape of the detected target to the processing unit 3 as a detection result (wherein the angle limits the distances for which the values can be accumulated and thus the objects detected are positioned within a set of distances away from the imaging sensor).); and
an extraction circuit which, in operation, extracts a second position of the object from the accumulation result (Fig. 7, illustrates extracting multiple positions of an object. Paragraph [0040]-SANO discloses the target position selection unit 35 extracts target position data (71a to 71d, 72a to 72d, and 73a to 73d) indicating traveling lane boundary on the basis of a plurality of stored target position data, and calculates reliability of the relative position with respect to the vehicle V with respect to the extracted target position data (71a to 71d, 72a to 72d, and 73a to 73d).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of SANO of an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and an extraction circuit which, in operation, extracts a second position of the object from the accumulation result.
Wherein having BABA’s object detection device of an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and an extraction circuit which, in operation, extracts a second position of the object from the accumulation result.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and SANO are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while SANO the object of the present invention is to provide a self-position estimation method and a self-position estimation device for improving an estimation accuracy of the self-position by eliminating the target position data estimated to have many errors of a relative position. Please see BABA (US 20170294123 A1), Paragraph [0006], and SANO et al. (US 20200019792 A1), Paragraph [0004].
Regarding claim 3, BABA in view of SANO explicitly teach the object detection device according to claim 1,
BABA further explicitly teaches further comprising an object detection circuit which, in operation, detects a type of the object by using the image (Fig. 1A, illustrates an object detection circuit, called collision mitigation apparatus #1. Paragraph [0037-0038]-BABA discloses the collision mitigation ECU 7 applies image analysis to the captured image represented by the image signal to identify an object. This identification may be implemented by matching processing using prestored object models. An object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type.),
wherein the predetermined distances from the imaging sensor is set by an interval corresponding to the type of the object (Figs. 2-4. Paragraph [0038]-BABA discloses an object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type. The collision mitigation ECU 7 determines a Y-coordinate of the object in the XY-plane based on a vertical position of the object in the captured image, and a horizontal azimuth angle of the object (an angular position from the direction ahead of the own vehicle) based on a horizontal position of the object in the capture image (wherein the Y-coordinate and the horizontal azimuth angle comprise the interval corresponding to the type of object and wherein the collision mitigation ECU includes an imaging sensor).).
Regarding claim 6, BABA explicitly teaches an object detection method comprising (Fig. 2, illustrates the process of object detection and collision mitigation. Paragraph [0032]):
estimating a first position of an object multiple times by using a first distance to the object and an azimuth of the object (Fig. 1A. Paragraphs [0033-0034]-BABA discloses based on one or more radar signals, the collision mitigation ECU 7 identifies an object and calculates (or determines) a linear distance from the own vehicle to the object and a horizontal azimuth angle of the object (i.e., an angular position of the object from the direction ahead of the own vehicle). Based on these calculated values, the collision mitigation ECU 7, as shown in FIG. 3, calculates or determines position coordinates (X- and Y-coordinates) of the object in the XY-plane as a detection point Pr of the object in the XY-plane.),
the first distance being measured by one or more range finders (Fig. 1A, #2 called millimeter-wave radar. Paragraph [0033]-BABA discloses the collision mitigation ECU 7 detects an object based on a radar signal transmitted from the millimeter-wave radar 2 (i.e., detection information from the millimeter-wave radar 2) (step S110). More specifically, based on one or more radar signals, the collision mitigation ECU 7 identifies an object and calculates (or determines) a linear distance from the own vehicle to the object (wherein the radar is a range finder).),
the azimuth (Fig. 4, azimuth denoted with θi. Paragraph [0045]) being estimated from an image of the object acquired by an imaging sensor (Fig. 4. Paragraph [0045]-BABA discloses the accuracy in detecting an azimuth of an object by image processing of a captured image acquired from the monocular camera 3 is likely to be higher than the accuracy in detecting an azimuth of the object by the millimeter-wave radar 2. Meanwhile, the accuracy in detecting a distance to the object by image processing of the captured image acquired from the monocular camera 3 is likely to be lower than the accuracy in detecting a distance to the object by the millimeter-wave radar 2. For example, as shown in FIG. 4, positions of upper and lower body parts of a pedestrian may be used to determine an azimuth of the pedestrian from a captured image. Thus, the azimuth θi of the pedestrian with respect to the front of the vehicle can be relatively accurately determined.);
BABA fails to explicitly teach accumulating reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and extracting a second position of the object from the accumulation result.
However, SANO explicitly teaches accumulating reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times (Fig. 2 and 7. Paragraph [0021]-SANO discloses the surrounding sensor group 1 includes a plurality of Laser Range Finders (LRFs) 101 and 102 and a plurality of cameras 201 and 202, for example. The Laser Range Finders (LRFs) 101 and 102 are respectively configured to detect a distance and azimuth to a target by receiving light reflected from the target to which laser light is emitted. The cameras 201 and 202 are configured to capture surroundings of the vehicle V, and obtain the digital image capable of image processing. Thus, the surrounding sensor group 1 is composed of a plurality of sensors respectively configured to detect targets present in surroundings of the vehicle V.),
the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other (Fig. 8-9, illustrate regions that are aligned with each other. Paragraph [0021]-SANO discloses the Laser Range Finders (LRFs) 101 and 102 are respectively configured to detect a distance and azimuth to a target by receiving light reflected from the target to which laser light is emitted. Further in paragraph [0042]-SANO discloses the straight line extracting unit 34 approximates straight lines (N2 and N3) with respect to the target position data (72 and 73) indicating the traveling lane boundary shown in FIG. 9. The target position selection unit 35 measures the respective distances in a vehicle width direction from the vehicle V to the respective straight lines (N2 and N3).) and positioned at predetermined distances away from the imaging sensor (Fig. 2. Paragraph [0022]-SANO discloses the LRFs 101 and 102 are configured to scan laser light at a predetermined scan angle (e.g., 90 degrees) so that a track of the laser light to be emitted may, for example, form a vertical plane with respect to a road surface as a rotation axis along a front-back direction D of the vehicle V. Consequently, the LRFs 101 and 102 can detect targets, such as curbs or the like, which are present in a right-left direction of the vehicle V. The LRFs 101 and 102 are configured to sequentially output a shape of the detected target to the processing unit 3 as a detection result (wherein the angle limits the distances for which the values can be accumulated and thus the objects detected are positioned within a set of distances away from the imaging sensor).); and
extracting a second position of the object from the accumulation result (Fig. 7, illustrates extracting multiple positions of an object. Paragraph [0040]-SANO discloses the target position selection unit 35 extracts target position data (71a to 71d, 72a to 72d, and 73a to 73d) indicating traveling lane boundary on the basis of a plurality of stored target position data, and calculates reliability of the relative position with respect to the vehicle V with respect to the extracted target position data (71a to 71d, 72a to 72d, and 73a to 73d).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA of an object detection method comprising: estimating a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of SANO of accumulating reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and extracting a second position of the object from the accumulation result.
Wherein having BABA’s object detection device having accumulating reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and extracting a second position of the object from the accumulation result.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and SANO are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while SANO the object of the present invention is to provide a self-position estimation method and a self-position estimation device for improving an estimation accuracy of the self-position by eliminating the target position data estimated to have many errors of a relative position. Please see BABA (US 20170294123 A1), Paragraph [0006], and SANO et al. (US 20200019792 A1), Paragraph [0004].
Regarding claim 8, BABA in view of SANO explicitly teach the object detection method according to claim 6,
BABA further explicitly teaches further comprising detecting a type of the object by using the image (Fig. 2. Paragraph [0037-0038]-BABA discloses the collision mitigation ECU 7 applies image analysis to the captured image represented by the image signal to identify an object. This identification may be implemented by matching processing using prestored object models. An object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type.),
wherein the predetermined distance from the imaging sensor is set by an interval corresponding to the type of the object (Figs. 2-4. Paragraph [0038]-BABA discloses an object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type. The collision mitigation ECU 7 determines a Y-coordinate of the object in the XY-plane based on a vertical position of the object in the captured image, and a horizontal azimuth angle of the object (an angular position from the direction ahead of the own vehicle) based on a horizontal position of the object in the capture image (wherein the Y-coordinate and the horizontal azimuth angle comprise the interval corresponding to the type of object and wherein the collision mitigation ECU includes an imaging sensor).).
Claims 2, 4, 7, and 9 are rejected under 35 U.S.C. 103 as being unpatentable over BABA (US 20170294123 A1), hereinafter referenced as BABA, in view of SANO et al. (US 20200019792 A1), hereinafter referenced as SANO, and further in view of IIDA et al. (US 20170243372 A1), hereinafter referenced as IIDA.
Regarding claim 2, BABA in view of SANO explicitly teach the object detection device according to claim 1,
BABA further explicitly teaches further comprising an object detection circuit which, in operation, detects a type of the object by using the image (Fig. 1A, illustrates an object detection circuit, called collision mitigation apparatus #1. Paragraph [0037-0038]-BABA discloses the collision mitigation ECU 7 applies image analysis to the captured image represented by the image signal to identify an object. This identification may be implemented by matching processing using prestored object models. An object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type.),
BABA fails to explicitly teach wherein the one or more range finders are plural.
However, SANO explicitly teaches wherein the one or more range finders are plural (Fig. 1, #101 and 102 called Laser Range Finder. Paragraph [0021]-SANO explicitly teaches the surrounding sensor group 1 includes a plurality of Laser Range Finders (LRFs) 101 and 102 and a plurality of cameras 201 and 202, for example.), and
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of SANO of wherein the one or more range finders are plural.
Wherein having BABA’s object detection device having wherein the one or more range finders are plural.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and SANO are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while SANO the object of the present invention is to provide a self-position estimation method and a self-position estimation device for improving an estimation accuracy of the self-position by eliminating the target position data estimated to have many errors of a relative position. Please see BABA (US 20170294123 A1), Paragraph [0006], and SANO et al. (US 20200019792 A1), Paragraph [0004].
BABA in view of SANO fail to explicitly teach the estimation circuit is which, in operation, when the type of the object does not correspond to a predetermined object, extracts the second position of the object by using second distances measured by the one or more range finders.
However, IIDA explicitly teaches the estimation circuit is which, in operation, when the type of the object does not correspond to a predetermined object (Fig. 2. Paragraph [0109]-IIDA discloses even when the type of the object 200, for example, the type of the pallet, is unknown, and/or the size of the opening 210, the position of the opening 210 in the flat portion 201, or the like is unknown, it is possible to identify the position of the opening 210, the position and posture of the object 200, and the like.), extracts the second position (Fig. 2. Paragraph [0105]-IIDA discloses when the corresponding point value is greater than or equal to the predetermined threshold value (S206: Y), the object state identifier 136 converts the corresponding point into a stable point (S208) (wherein the stable point is a second position).) of the object by using second distances measured by the one or more range finders (Fig. 2, illustrates the use of multiple range finders, #102 called sensor. Paragraph [0048]-IIDA discloses the sensor 102 is not particularly limited so long as it is a device that is able to obtain actual measured values which are three-dimensional data at a plurality of points on the flat portion 201 of the object 200 that includes the opening 210. Examples of the sensor 102 include a sensor that includes two cameras and obtains an actual measured value using a parallax between two two-dimensional images, a time-of-flight (TOF) camera which measures the distance to a target for each pixel by measuring, for each imaging pixel, the length of time from when a light-emitting diode (LED) provided around the camera emits infrared light to when the camera observes the light reflected off the target, and a distance sensor that measures the coordinates of a plurality of points and the distances to the plurality of points based on scanned and reflected laser light. In the present preferred embodiment, suppose that the sensor 102 is preferably a TOF camera (wherein sensors 102 in Fig. 2 are plural range finders and second distances are three-dimensional data obtained by sensors 102).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of IIDA of the estimation circuit is which, in operation, when the type of the object does not correspond to a predetermined object, extracts the second position of the object by using second distances measured by the one or more range finders.
Wherein having BABA’s object detection device having the estimation circuit is which, in operation, when the type of the object does not correspond to a predetermined object, extracts the second position of the object by using second distances measured by the one or more range finders.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance/state determination of an object. Since both BABA and IIDA are object detection/identification devices, wherein BABA there is a need to more accurately determine the position of the object, while IIDA it is possible to improve the accuracy of identifying the state of the object. Please see BABA (US 20170294123 A1), Paragraph [0006], and IIDA et al. (US 20170243372 A1), Paragraph [0021].
Regarding claim 4, BABA in view of SANO explicitly teach the object detection device according to claim 1,
BABA in view of SANO fail to explicitly teach wherein the extraction circuit is which, in operation, extracts the second position of the object when a cumulative value of the first position of the object exceeds a threshold value.
However, IIDA explicitly teaches wherein the extraction circuit is which, in operation, extracts the second position (Fig. 2, illustrates the extraction circuit, #103 called the object state identification apparatus. Paragraph [0105]-IIDA discloses the object state identifier 136 converts the corresponding point into a stable point (S208) (wherein the stable point is a second position). Further in paragraph [0104]-IIDA discloses when the corresponding point value is less than a predetermined threshold value (S206: N), the object state identifier 136 determines a virtual plane and extracts a stable point (S207).) of the object when a cumulative value of the first position of the object exceeds a threshold value (Fig. 11. Paragraph [0105]-IIDA discloses when the corresponding point value is greater than or equal to the predetermined threshold value (S206: Y) (wherein the corresponding point value is a cumulative value of the first position and a threshold value is a threshold value).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of IIDA of wherein the extraction circuit is which, in operation, extracts the second position of the object when a cumulative value of the first position of the object exceeds a threshold value.
Wherein having BABA’s object detection device having wherein the extraction circuit is which, in operation, extracts the second position of the object when a cumulative value of the first position of the object exceeds a threshold value.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance/state determination of an object. Since both BABA and IIDA are object detection/identification devices, wherein BABA there is a need to more accurately determine the position of the object, while IIDA it is possible to improve the accuracy of identifying the state of the object. Please see BABA (US 20170294123 A1), Paragraph [0006], and IIDA et al. (US 20170243372 A1), Paragraph [0021].
Regarding claim 7, BABA in view of SANO explicitly teach the object detection method according to claim 6,
BABA further explicitly teaches further comprising detecting a type of the object by using the image (Fig. 1A, illustrates an object detection circuit, called collision mitigation apparatus #1. Paragraph [0037-0038]-BABA discloses the collision mitigation ECU 7 applies image analysis to the captured image represented by the image signal to identify an object. This identification may be implemented by matching processing using prestored object models. An object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type.),
BABA in view of SANO fail to explicitly teach wherein, when the type of the object does not correspond to a predetermined object, the extracting of the second position is performed by using second distances measured by the one or more range finders.
However, IIDA explicitly teaches wherein, when the type of the object does not correspond to a predetermined object (Fig. 2. Paragraph [0109]-IIDA discloses even when the type of the object 200, for example, the type of the pallet, is unknown, and/or the size of the opening 210, the position of the opening 210 in the flat portion 201, or the like is unknown, it is possible to identify the position of the opening 210, the position and posture of the object 200, and the like.), the extracting of the second position (Fig. 2. Paragraph [0105]-IIDA discloses when the corresponding point value is greater than or equal to the predetermined threshold value (S206: Y), the object state identifier 136 converts the corresponding point into a stable point (S208) (wherein the stable point is a second position).) is performed by using second distances measured by the one or more range finders (Fig. 2, illustrates the use of multiple range finders, #102 called sensor. Paragraph [0048]-IIDA discloses the sensor 102 is not particularly limited so long as it is a device that is able to obtain actual measured values which are three-dimensional data at a plurality of points on the flat portion 201 of the object 200 that includes the opening 210. Examples of the sensor 102 include a sensor that includes two cameras and obtains an actual measured value using a parallax between two two-dimensional images, a time-of-flight (TOF) camera which measures the distance to a target for each pixel by measuring, for each imaging pixel, the length of time from when a light-emitting diode (LED) provided around the camera emits infrared light to when the camera observes the light reflected off the target, and a distance sensor that measures the coordinates of a plurality of points and the distances to the plurality of points based on scanned and reflected laser light. In the present preferred embodiment, suppose that the sensor 102 is preferably a TOF camera (wherein sensors 102 in Fig. 2 are plural range finders and second distances are three-dimensional data obtained by sensors 102).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection method comprising: estimating a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of IIDA of wherein, when the type of the object does not correspond to a predetermined object, the extracting of the second position is performed by using second distances measured by the one or more range finders.
Wherein having BABA’s object detection device having wherein, when the type of the object does not correspond to a predetermined object, the extracting of the second position is performed by using second distances measured by the one or more range finders.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance/state determination of an object. Since both BABA and IIDA are object detection/identification devices, wherein BABA there is a need to more accurately determine the position of the object, while IIDA it is possible to improve the accuracy of identifying the state of the object. Please see BABA (US 20170294123 A1), Paragraph [0006], and IIDA et al. (US 20170243372 A1), Paragraph [0021].
Regarding claim 9, BABA in view of SANO explicitly teach the object detection method according to claim 6,
BABA in view of SANO fail to explicitly teach wherein the extracting of the second position is performed when a cumulative value of the first position of the object exceeds a threshold value.
However, IIDA explicitly teaches wherein the extracting of the second position (Fig. 2, illustrates the extraction circuit, #103 called the object state identification apparatus. Paragraph [0105]-IIDA discloses the object state identifier 136 converts the corresponding point into a stable point (S208) (wherein the stable point is a second position). Further in paragraph [0104]-IIDA discloses when the corresponding point value is less than a predetermined threshold value (S206: N), the object state identifier 136 determines a virtual plane and extracts a stable point (S207).) is performed when a cumulative value of the first position of the object exceeds a threshold value (Fig. 11. Paragraph [0105]-IIDA discloses when the corresponding point value is greater than or equal to the predetermined threshold value (S206: Y) (wherein the corresponding point value is a cumulative value of the first position and a threshold value is a threshold value).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection method comprising: estimating a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of IIDA of wherein the extracting of the second position is performed when a cumulative value of the first position of the object exceeds a threshold value.
Wherein having BABA’s object detection device having wherein the extracting of the second position is performed when a cumulative value of the first position of the object exceeds a threshold value.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance/state determination of an object. Since both BABA and IIDA are object detection/identification devices, wherein BABA there is a need to more accurately determine the position of the object, while IIDA it is possible to improve the accuracy of identifying the state of the object. Please see BABA (US 20170294123 A1), Paragraph [0006], and IIDA et al. (US 20170243372 A1), Paragraph [0021].
Claims 5 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over BABA (US 20170294123 A1), hereinafter referenced as BABA, in view of SANO et al. (US 20200019792 A1), hereinafter referenced as SANO, and further in view of YANAGAWA et al. (US 20180232582 A1), hereinafter referenced as YANAGAWA.
Regarding claim 5, BABA in view of SANO explicitly teach the object detection device according to claim 1,
BABA further explicitly teaches wherein the estimation circuit is which, in operation, further estimates a third position of the object by using the image (Figs. 3-4. Paragraph [0041]-BABA discloses in step S130, the collision mitigation ECU 7 determines the Y-coordinate and the horizontal azimuth angle (angular position) of the object in the XY-plane as the detection point Pi of the object in the XY-plane, as shown in FIG. 3. The detection point Pi of the object is set, for example, in the center in the object's width direction. The detection point Pi of the object represents a relative position of the object with respect to the reference point Po. In the following, the object detected in step S130 (the object detected based on the captured image from the monocular camera 3) will be referred to as an “image object” (wherein a third position is detection point Pi and wherein the estimation circuit is the collision mitigation ECU 7).), and
BABA in view of SANO fail to explicitly teach the extraction circuit is which, in operation, extracts, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result.
However, YANAGAWA explicitly teaches the extraction circuit is which, in operation, extracts, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result (Fig. 3, illustrates an extraction circuit, called control unit #15. Paragraph [0103]-YANAGAWA discloses the third data generation unit 155 can generate the second data D2 for each object O in a case in which a plurality of objects O are present in the surroundings of the moving body system 1 by extracting, as the third position information, the first position information of a location at a close distance on the first coordinates, the signal detection information of which includes distances within a predetermined range and generating the third data D3 (wherein the second position is third position information, wherein the third position is the first position information, and wherein a predetermined range is a predetermined range).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of YANAGAWA of the extraction circuit is which, in operation, extracts, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result.
Wherein having BABA’s object detection device having the extraction circuit is which, in operation, extracts, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and YANAGAWA are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while YANAGAWA improves the processing speed of the information processing by reducing the amount of calculation necessary for the processing related to the presence of the object while maintaining the measurement accuracy when detecting the object during the execution of the information processing. Please see BABA (US 20170294123 A1), Paragraph [0006], and YANAGAWA et al. (US 20180232582 A1), Paragraph [0031].
Regarding claim 10, BABA in view of SANO explicitly teach the object detection method according to claim 6,
BABA further explicitly teaches further comprising estimating a third position of the object by using the image (Figs. 3-4. Paragraph [0041]-BABA discloses in step S130, the collision mitigation ECU 7 determines the Y-coordinate and the horizontal azimuth angle (angular position) of the object in the XY-plane as the detection point Pi of the object in the XY-plane, as shown in FIG. 3. The detection point Pi of the object is set, for example, in the center in the object's width direction. The detection point Pi of the object represents a relative position of the object with respect to the reference point Po. In the following, the object detected in step S130 (the object detected based on the captured image from the monocular camera 3) will be referred to as an “image object” (wherein a third position is detection point Pi and wherein the estimation circuit is the collision mitigation ECU 7).),
BABA in view of SANO fail to explicitly teach wherein the extracting of the second position is performed by extracting, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result.
However, YANAGAWA explicitly teaches wherein the extracting of the second position is performed by extracting, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result (Fig. 3, illustrates an extraction circuit, called control unit #15. Paragraph [0103]-YANAGAWA discloses the third data generation unit 155 can generate the second data D2 for each object O in a case in which a plurality of objects O are present in the surroundings of the moving body system 1 by extracting, as the third position information, the first position information of a location at a close distance on the first coordinates, the signal detection information of which includes distances within a predetermined range and generating the third data D3 (wherein the second position is third position information, wherein the third position is the first position information, and wherein a predetermined range is a predetermined range).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection method comprising: estimating a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of YANAGAWA of wherein the extracting of the second position is performed by extracting, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result.
Wherein having BABA’s object detection device having wherein the extracting of the second position is performed by extracting, as the second position of the object, a position falling within a predetermined range including the third position in the accumulation result.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and YANAGAWA are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while YANAGAWA improves the processing speed of the information processing by reducing the amount of calculation necessary for the processing related to the presence of the object while maintaining the measurement accuracy when detecting the object during the execution of the information processing. Please see BABA (US 20170294123 A1), Paragraph [0006], and YANAGAWA et al. (US 20180232582 A1), Paragraph [0031].
Claims 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over BABA (US 20170294123 A1), hereinafter referenced as BABA, in view of SANO et al. (US 20200019792 A1), hereinafter referenced as SANO, and further in view of TAKIZAWA et al. (JP 2006284293 A), hereinafter referenced as TAKIZAWA.
Regarding claim 11, BABA in view of SANO explicitly teach the object detection device according to claim 1,
BABA further explicitly teaches further comprising an object detection circuit which, in operation, detects a type of the object using the image (Fig. 1A, illustrates an object detection circuit, called collision mitigation apparatus #1. Paragraph [0037-0038]-BABA discloses the collision mitigation ECU 7 applies image analysis to the captured image represented by the image signal to identify an object. This identification may be implemented by matching processing using prestored object models. An object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type.),
BABA in view of SANO fail to explicitly teach wherein, in a case that the object detection circuit determines that the type of the object is a pedestrian, the accumulation circuit lowers a threshold that is compared with an accumulated value of reflection intensity.
However, TAKIZAWA explicitly teaches wherein, in a case that the object detection circuit determines that the type of the object is a pedestrian, the accumulation circuit lowers a threshold that is compared with an accumulated value of reflection intensity (Paragraph [0029]-TAKIZAWA discloses the threshold value changing means of this embodiment is configured such that the threshold value is set to a standard value when a low-reflection object having a low reflection intensity such as a pedestrian appears in the search range and the acquisition target object becomes a low-reflection object. The threshold value Ia is lowered to the threshold value Ib.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of TAKIZAWA of wherein, in a case that the object detection circuit determines that the type of the object is a pedestrian, the accumulation circuit lowers a threshold that is compared with an accumulated value of reflection intensity.
Wherein having BABA’s object detection device having an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and an extraction circuit which, in operation, extracts a second position of the object from the accumulation result.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and TAKIZAWA relate to object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while TAKIZAWA since the low-reflection object can be reliably captured and tracked without losing sight, the recognition result of the pedestrian or the like of the recognition processing unit 4 is improved, and automatic braking control of the vehicle 1 using this result, etc. Can also improve traffic safety. Please see BABA (US 20170294123 A1), Paragraph [0006], and TAKIZAWA et al. (JP 2006284293 A), Paragraph [0044].
Regarding claim 12, BABA in view of SANO explicitly teach the object detection method according to claim 6, further comprising:
BABA further explicitly teaches detecting a type of the object using the image (Fig. 1A, illustrates an object detection circuit, called collision mitigation apparatus #1. Paragraph [0037-0038]-BABA discloses the collision mitigation ECU 7 applies image analysis to the captured image represented by the image signal to identify an object. This identification may be implemented by matching processing using prestored object models. An object model is prepared for each object type, such as a vehicle, a pedestrian, or the like, which allows not only determination of the presence of an object, but also identification of its object type.); and
BABA in view of SANO fail to explicitly teach in a case that the type of the object is determined to be a pedestrian, lowering a threshold that is compared with an accumulated value of reflection intensity.
However, TAKIZAWA explicitly teaches in a case that the type of the object is determined to be a pedestrian, lowering a threshold that is compared with an accumulated value of reflection intensity (Paragraph [0029]-TAKIZAWA discloses the threshold value changing means of this embodiment is configured such that the threshold value is set to a standard value when a low-reflection object having a low reflection intensity such as a pedestrian appears in the search range and the acquisition target object becomes a low-reflection object. The threshold value Ia is lowered to the threshold value Ib.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection method comprising: estimating a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of TAKIZAWA of an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and an extraction circuit which, in operation, extracts a second position of the object from the accumulation result.
Wherein having BABA’s object detection device having an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and an extraction circuit which, in operation, extracts a second position of the object from the accumulation result.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and TAKIZAWA relate to object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while TAKIZAWA since the low-reflection object can be reliably captured and tracked without losing sight, the recognition result of the pedestrian or the like of the recognition processing unit 4 is improved, and automatic braking control of the vehicle 1 using this result, etc. Can also improve traffic safety. Please see BABA (US 20170294123 A1), Paragraph [0006], and TAKIZAWA et al. (JP 2006284293 A), Paragraph [0044].
Claims 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over BABA (US 20170294123 A1), hereinafter referenced as BABA, in view of SANO et al. (US 20200019792 A1), hereinafter referenced as SANO, and further in view of FUJIWARA et al. (US 20210231799 A1), hereinafter referenced as FUJIWARA.
Regarding claim 13, BABA in view of SANO explicitly teach the object detection device according to claim 1,
BABA in view of SANO fail to explicitly teach wherein each of the plurality of regions has a determined width along an axis extending from the image sensor.
However, FUJIWARA explicitly teaches wherein each of the plurality of regions has a determined width along an axis extending from the image sensor (Fig. 5, illustrates a plurality of regions with widths along an axis extending from the image sensor (wherein the axis is indicated by D11 and D12 and DO1 and DO2 indicate determined widths). Paragraph [0025]-FUJIWARA discloses in consideration with the detection ranges of the sonars 21 and the azimuth regions of the objects detected by the camera (D11 for O1, D12 for O2), with regard to distance information for which no tangent can be calculated (drawn), the object determination section 30 determines that different objects are detected, and calculates (draws) a line segment (LSA1 for O1) connecting both intersection points (JAa1 and JAa2 for O1) of the arc (AD2a for O1) and boundaries of the azimuth region D11 detected by the camera 11, and a line segment (LSA2 for O) connecting both intersection points (JAb1 and JAb2 for O2) of the arc (AD2b for O2) and boundaries of the azimuth region D12 detected by the camera 11. Then, the object determination section 30 determines the line segments as positions and widths of the objects.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of FUJIWARA of wherein each of the plurality of regions has a determined width along an axis extending from the image sensor.
Wherein having BABA’s object detection device having an accumulation circuit which, in operation, accumulates reflection intensity values obtained by the one or more range finders at the first positions of the object estimated the multiple times, the reflection intensity values being accumulated for each of a plurality of regions that are aligned with other and positioned at predetermined distances away from the imaging sensor; and an extraction circuit which, in operation, extracts a second position of the object from the accumulation result.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and FUJIWARA are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while FUJIWARA the combination of the advantages of the camera 11 and the sonar 21 enables the object detection device 1 to simply and accurately detect the position and width of the object. Please see BABA (US 20170294123 A1), Paragraph [0006], and FUJIWARA et al. (US 20210231799 A1), Paragraph [0032].
Regarding claim 14, BABA in view of SANO and further in view of FUJIWARA explicitly teach the object detection device according to claim 13,
BABA in view of SANO fail to explicitly teach wherein the determined width is set based on a type of the object.
However, FUJIWARA explicitly teaches wherein the determined width is set based on a type of the object (Fig. 5, illustrates widths determined based on the type of object as object O1 and O2 are different objects with different widths DO1 and DO2. Paragraph [0025]-FUJIWARA discloses in consideration with the detection ranges of the sonars 21 and the azimuth regions of the objects detected by the camera (D11 for O1, D12 for O2), with regard to distance information for which no tangent can be calculated (drawn), the object determination section 30 determines that different objects are detected, and calculates (draws) a line segment (LSA1 for O1) connecting both intersection points (JAa1 and JAa2 for O1) of the arc (AD2a for O1) and boundaries of the azimuth region D11 detected by the camera 11, and a line segment (LSA2 for O) connecting both intersection points (JAb1 and JAb2 for O2) of the arc (AD2b for O2) and boundaries of the azimuth region D12 detected by the camera 11. Then, the object determination section 30 determines the line segments as positions and widths of the objects.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of FUJIWARA of wherein the determined width is set based on a type of the object
Wherein having BABA’s object detection device having wherein the determined width is set based on a type of the object
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and FUJIWARA are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while FUJIWARA the combination of the advantages of the camera 11 and the sonar 21 enables the object detection device 1 to simply and accurately detect the position and width of the object. Please see BABA (US 20170294123 A1), Paragraph [0006], and FUJIWARA et al. (US 20210231799 A1), Paragraph [0032].
Regarding claim 15, BABA in view of SANO and further in view of FUJIWARA explicitly teach the object detection device according to claim 13,
Although BABA and SANO explicitly teach the azimuth, BABA in view of SANO fail to explicitly teach wherein the axis corresponds to the azimuth.
However, FUJIWARA explicitly teaches wherein the axis corresponds to the azimuth (Fig. 5, illustrates an axis corresponding to the azimuth called azimuth D11 and D12. Paragraph [0025]-FUJIWARA discloses in consideration with the detection ranges of the sonars 21 and the azimuth regions of the objects detected by the camera (D11 for O1, D12 for O2), with regard to distance information for which no tangent can be calculated (drawn), the object determination section 30 determines that different objects are detected, and calculates (draws) a line segment (LSA1 for O1) connecting both intersection points (JAa1 and JAa2 for O1) of the arc (AD2a for O1) and boundaries of the azimuth region D11 detected by the camera 11, and a line segment (LSA2 for O) connecting both intersection points (JAb1 and JAb2 for O2) of the arc (AD2b for O2) and boundaries of the azimuth region D12 detected by the camera 11. Then, the object determination section 30 determines the line segments as positions and widths of the objects.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of BABA in view of SANO of an object detection device comprising: an estimation circuit which, in operation, estimates a first position of an object multiple times by using a first distance to the object and an azimuth of the object, the first distance being measured by one or more range finders, the azimuth being estimated from an image of the object acquired by an imaging sensor; with the teachings of FUJIWARA of wherein the axis corresponds to the azimuth.
Wherein having BABA’s object detection device having wherein the axis corresponds to the azimuth.
The motivation behind the modification would have been to obtain an object detection device that enhances the accuracy of position/distance determination of an object and the speed at which objects are detected. Since both BABA and FUJIWARA are object detection devices, wherein BABA there is a need to more accurately determine the position of the object, while FUJIWARA the combination of the advantages of the camera 11 and the sonar 21 enables the object detection device 1 to simply and accurately detect the position and width of the object. Please see BABA (US 20170294123 A1), Paragraph [0006], and FUJIWARA et al. (US 20210231799 A1), Paragraph [0032].
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant’s disclosure.
OHKADO et al. (US 20200401825 A1) - An object detection device includes: a camera ECU that measures the bearing of an object by detecting the object from an image captured by a camera and identifying the direction toward the object; a sonar that measures the distance to the object existing around the vehicle; and a position identification unit that identifies the position of the object by combining the measured bearing data and distance data on a grid map that is based on a polar coordinate system and identifying the grid cell where the object exists on the grid map…Abstract, Fig. 2A-2B.
ICHIKI (US 20230267746 A1) - The present technology relates to an information processing device, an information processing method, and a program capable of reducing a load of object recognition using sensor fusion. The information processing device includes an object region detection unit that detects an object region indicating ranges in an azimuth direction and an elevation angle direction in which there is an object within a sensing range of the distance measurement sensor on the basis of three-dimensional data indicating a direction of and a distance to each measurement point measured by a distance measurement sensor, and associates information within a captured image captured by a camera whose imaging range at least partially overlaps the sensing range with the object region. This technology can be applied, for example, to a system that performs object recognition…Abstract, Fig. 5.
HARADA et al. (US 11087149 B2) - An ECU is applied to a vehicle system that is provided with lateral sensors which acquire distance information expressing a distance to an object that is located at a position on a lateral side of a vehicle. When distance information on the object is acquired by the lateral sensors, a judgement is made by the ECU as to whether or not the object is a predetermined moving object that moves relative to the vehicle. The ECU determines that the object is a target to be subjected to contact avoidance processing for avoiding contact with the object, based on a result of judging whether or not the object for which the distance information is acquired is a moving object…Abstract, Fig. 2.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ETHAN N WOLFSON whose telephone number is (571)272-1898. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm.
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/ETHAN N WOLFSON/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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