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 required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/09/2024 The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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: recognition result acquistion unit, setting unit, image output unit in claim 1-7.
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.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1 and 8-9 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Takatsuka et al. US PG-Pub(US 20220210317 A1).
Regarding Claim 1, Takatsuka teaches an image recognition assistance apparatus(Fig. 1) comprising: a recognition result acquisition unit (This unit is being interpreted under 35 U.S.C. 112(f) and the corresponding structure is CPU as disclosed in ¶[0041] of the specification, the corresponding structure of a CPU in the cited prior art is disclosed in ¶[0110]) configured to acquire a recognition result of a recognition target object of image recognition carried out by an image recognition apparatus on a target image output by an image output unit using a predetermined set value(¶[0166],“the calculation unit 8 has a function of class identification based on object detection (object categorization function), and performs classified image quality adaptation (parameter selection suited for a target category based on object detection) which adaptively sets parameters for the logic unit 5 according to output from the class identification unit.
[0167] For the parameter sets, appropriate parameters (image quality setting values) are generated beforehand by pre-learning and stored for each class using deep learning.
[0168] For example, for generating a parameter set of a class “human,” deep learning is performed using a large number of images of a human as learning data SD to generate the parameter set PR1 having a highest image recognition rate in view of recognition of a human as depicted in FIG. 4A.”, ¶[0167] discloses performing object detection on the image acquired and ¶[0167]-¶[0168] discloses setting a parameter based on the highest recognition rate of a human in the image.); and a setting unit (This unit is being interpreted under 35 U.S.C. 112(f) and the corresponding structure is CPU as disclosed in ¶[0041] of the specification, the corresponding structure of a CPU in the cited prior art is disclosed in ¶[0110]) configured to determine the set value with which the recognition result meets a predetermined criterion and set the determined set value in the image output unit. (¶[0560], “ the calculation unit 8 (object region recognition unit 82) performs processing in steps S160 to S164 similarly to above. Subsequently, the calculation unit 8 (threshold setting unit 85) in step S165 calculates a threshold (frame rate as threshold) for maintaining object tracking while changing the frame rate of the target class surrounded by the bounding box 20.” [0562] “In this manner, for example, a parameter based on the threshold corresponding to the target class, i.e., a lowest possible value of the frame rate for maintaining object tracking is set.”, ¶[0560] discloses setting the threshold such that the object is detected in the image and ¶[0562] discloses setting a threshold such that there is a min requirement for object tracking.)
Regarding Claim 8, claim 8 is considered a method claim substantially corresponding to claim 1. Please see the discussion of claim 1 above for a discussion of similar limitations. Furthermore, Takatsuka teaches image recognition assistance method (Fig.5), wherein a computer performs(See ¶[0110])
Regarding Claim 9, claim 9 is considered a medium claim substantially corresponding to claim 1. Please see the discussion of claim 1 above for a discussion of similar limitations. Furthermore, Takatsuka teaches a non-transitory computer readable medium storing an image recognition assistance program(See, ¶[0111]) causing a computer to execute(See, ¶[0111]:
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.
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 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Takatsuka et al. US PG-Pub(US 20220210317 A1) in view of Dayana et al. US PG-Pub(US 20220394171 A1).
Regarding Claim 2, Takatsuka teaches the image recognition assistance apparatus according to claim 1,
Takatsuka does not explicitly teach wherein the image output unit outputs an image obtained by adjusting an image quality of the captured image by using the set value to the image recognition apparatus as the target image, the recognition result acquisition unit acquires a recognition rate of a recognition target object in the target image that has been recognized and a recognition target area including the recognition target object as the recognition result, and the setting unit determines, when the recognition rate is smaller than a predetermined value, an adjustment value to be used to adjust the image quality of the recognition target area of the captured image as the set value so that the recognition rate becomes equal to or larger than a predetermined value.
Dayana teaches wherein the image output unit outputs an image obtained by adjusting an image quality of the captured image by using the set value to the image recognition apparatus as the target image(¶[0082] discloses when the object is not detected than a notification is sent to the focus/lens controller to capture another image such that the quality is higher.), the recognition result acquisition unit acquires a recognition rate of a recognition target object in the target image that has been recognized and a recognition target area including the recognition target object as the recognition result, (0054] “The image capturing system can calculate the confidence based on an image captured from a first lens position. If the confidence indicates an object of interest is present in the image, the image processing system can detect the object of interest from the first lens position. The image capturing system can maintain the lens in the first lens position, and no lens adjustment to a second lens position is necessary.”. ¶[0054] discloses determining a confidence based on the image captured from the camera system.)and the setting unit determines, when the recognition rate is smaller than a predetermined value, an adjustment value to be used to adjust the image quality of the recognition target area of the captured image as the set value so that the recognition rate becomes equal to or larger than a predetermined value (¶[0082], “the object detector 408 is unable to determine with a certainty threshold that an object of interest is or is not present in the image (e.g., if the confidence value is above a lower threshold but below an upper threshold), the object detector 408 can notify the focus/lens controller 406 of such uncertainty to cause the focus/lens controller 406 to adjust a configuration of the camera 420,”, ¶[0082] discloses when the recognition rate is below a threshold a user is notified and the configuration of the camera is adjusted. )
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Takatsuka with Dayana in order to adjust the image quality based on recognition results. One skilled in the art would have been motivated to modify Takatsuka in this manner in order to low power variable focus and, more specifically, low power variable focus for object detection. (Dayana, ¶[0001])
Regarding Claim 3, the combination of Takatsuka and Dayana teach the image recognition assistance apparatus according to claim 2, where Dayana further teaches wherein the setting unit specifies a candidate for an adjustment value used to adjust a target image whose recognition rate has become equal to or greater than a predetermined value, and determines the adjustment value based on the specified candidate for the adjustment value. (¶[0054], “ the image processing system can detect the object of interest without lens adjustment, rather by maintaining the lens in the first lens position. This contributes to the overall power consumption reduction. If the confidence is below the upper threshold and above a lower threshold, the image capturing system can capture another image from a second lens position, and can calculate a confidence based on the image captured from the second lens position. If the confidence indicates the object of interest is present in the image captured from the second lens position, the image processing system can detect the object of interest from the second lens position. If the confidence is below the upper threshold and above the lower threshold, the image capturing system can capture another image from a third lens position, and calculate another confidence based on the captured image. The image capturing system can serially check a number of detection confidences at different lens positions until the object is detected (while meeting the thresholds) or in case the confidence is blow an upper threshold and below a lower threshold a determination can be made that the object is not present.”, discloses using a threshold for when the confidence isn’t higher than the threshold than adjusting the camera system to image the object.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Takatsuka with Dayana in order to adjust the image quality based on recognition results. One skilled in the art would have been motivated to modify Takatsuka in this manner in order to low power variable focus and, more specifically, low power variable focus for object detection. (Dayana, ¶[0001])
Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Takatsuka et al. US PG-Pub(US 20220210317 A1) in view of Dayana et al. US PG-Pub(US 20220394171 A1) in view of Price et al. US PG-Pub(US 20220198773 A1).
Regarding Claim 4, while the combination of Takatsuka and Dayana teach the image recognition assistance apparatus according to claim 2, they do not explicitly teach wherein the setting unit determines, when the number of times that the recognition rate has become smaller than a predetermined value in image recognition after the recognition rate has become equal to or greater than the predetermined value is equal to or greater than a predetermined number, an adjustment value to be used to adjust an image quality type other than an image quality type adjusted most recently as the set value.
Price teaches wherein the setting unit determines, when the number of times that the recognition rate has become smaller than a predetermined value in image recognition after the recognition rate has become equal to or greater than the predetermined value is equal to or greater than a predetermined number (¶[0072], “than proceeding to step 622 again, system 100 may enter a “timeout” state after excessive delay in identifying an object within the quality threshold based on, for example, a determination that it performed a sufficient number of iterations, that it has spent more than a threshold amount of time processing an image without producing a valid identification, and so on. Upon determining that a “timeout” state has occurred, system 100 may cease processing and/or return a notification (e.g., to a mobile device) indicating that the object cannot be identified to sufficient accuracy.”, ¶[0072] discloses if the device can’t determine the object within a number of iterations than it enters a timeout state.) an adjustment value to be used to adjust an image quality type other than an image quality type adjusted most recently as the set value. (¶[0067], “At step 622, when the first identification confidence is below the quality threshold (or outside the threshold range), system 100 may modify an attribute of the image with a preprocessing augmentation tool. System 100 may modify an attribute of the received image by means discussed in FIG. 4. In some embodiments, system 100 may modify the received image numerous times, or alternatively, system 100 may modify several attributes once or numerous times by means discussed.”, ¶[0067] discloses adjusting the image quality of the received image.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Takatsuka and Dayana with Price in order to adjust the image quality based on the number of fail recognitions. One skilled in the art would have been motivated to modify Takatsuka and Dayana in this manner in order for improving object recognition, such as image recognition, object detection, and image segmentation. (Price, ¶[0001])
Regarding Claim 5, while the combination of Takatsuka and Dayana teach the image recognition assistance apparatus according to claim 3, they do not explicitly teach wherein the setting unit sets, when the number of specified candidates for the adjustment value is two or greater, a range of the adjustment value where the recognition rate becomes equal to or greater than a predetermined value in the image output unit using the two or more specified candidates for the adjustment value. (¶[0086] discloses performing a number of iterations such that the object can be detected and the time to detect the object can be reduced.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Takatsuka and Dayana with Price in order to adjust the image quality based on the number of fail recognitions. One skilled in the art would have been motivated to modify Takatsuka and Dayana in this manner in order for improving object recognition, such as image recognition, object detection, and image segmentation. (Price, ¶[0001])
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Takatsuka et al. US PG-Pub(US 20220210317 A1) in view of Yoshida et al. US PG-Pub(US 20230076396 A1).
Regarding Claim 6, while Takatsuka teaches the image recognition assistance apparatus according to claim 1, they do not explicitly teach wherein the setting unit determines a shutter speed in an image-capturing device serving as the image output unit as the set value with which the recognition result satisfies a predetermined criterion and sets the determined set value in the image-capturing device, and the target image is a captured image captured and output by the image-capturing device using the set shutter speed.
Yoshida teaches wherein the setting unit determines a shutter speed in an image-capturing device serving as the image output unit as the set value with which the recognition result satisfies a predetermined criterion and sets the determined set value in the image-capturing device, (¶[0094] “At this time, the controller 180 determines whether the amount of increase of the motion vector related value at the block size of FIG. 9(c), with respect to the motion vector related value at the block size of FIG. 9(b), is less than or equal to a threshold value. It is assumed here that the amount of increase of the motion vector related value is less than or equal to the threshold value. In this case, the controller 180 determines the shutter speed used when imaging thereafter, based on the motion vector related value at the block size of FIG. 9(c). On the contrary, if the amount of increase of the motion vector related value is not less than or equal to the threshold value, the controller 180 sets, as the target area for the next motion vector detection processing”, ¶[0094] discloses determining a shutter speed of the camera and setting a value based on the shutter speed.)and the target image is a captured image captured and output by the image-capturing device using the set shutter speed.(¶[0127], “The object detecting unit 320 detects an image of a target object such as a person or an animal contained in a captured image represented by image data digitized by the AD converter 140, in the same manner as in the third embodiment. The calculating unit 330 executes the processes described in the flowchart of FIG. 8, based on the detection result from the motion detector 310 and the detection result from the object detecting unit, to determine the shutter speed. The calculating unit 330 outputs the determined shutter speed to the controller 180 of the digital camera 100B”, ¶[0127] discloses detecting the object in the image and outputting a determined shutter speed of the captured image.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Takatsuka with Yoshida in order to determine the shutter speed of the imaging device. One skilled in the art would have been motivated to modify Takatsuka in this manner in order to reduce the blurring of a moving subject when detecting the motion vectors to determine the shutter speed. (Yoshida, ¶[0003])
Regarding Claim 7, the combination of Takatsuka and Yoshida teach the image recognition assistance apparatus according to claim 6, where Yoshida further teaches wherein the setting unit calculates a motion vector amount based on a first captured image and a second captured image captured by the image-capturing device before the first captured image is captured(¶[0074], “ the digital camera 100 (an example of the shutter speed determination device) of this embodiment comprises: the motion detector 310 performing motion vector detection processing, on a block-to-block basis of a specified block size, for image data obtained by capturing a subject image”, ¶[0074] discloses determining a motion vector using image frame data of a subject captured.), and the setting unit determines the shutter speed in accordance with the motion vector amount. (¶[0074], “ the controller 180 (an example of a control unit) causing the motion detector 310 to repeatedly execute the detection processing while reducing the block size, to find, each time executing the detection processing, a motion vector related value that changes in the same direction as the direction in which the magnitude of the motion vector changes, the controller 180 determining a shutter speed used when capturing the subject image thereafter, based on the found motion vector related value.”, ¶[0074] discloses determining the shutter speed by using the motion vector calculated.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Takatsuka with Yoshida in order to determine the shutter speed of the imaging device. One skilled in the art would have been motivated to modify Takatsuka in this manner in order to reduce the blurring of a moving subject when detecting the motion vectors to determine the shutter speed. (Yoshida, ¶[0003])
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAN D HOANG whose telephone number is (571)272-4344. The examiner can normally be reached Monday-Friday 8-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JOHN M VILLECCO can be reached at 571-272-7319. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HAN HOANG/Primary Examiner, Art Unit 2661
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