DETAILED ACTION
Claims 1–15 are still pending in the instant application.
This Office Action is in response to Applicant’s arguments filed on 08/17/2026.
THIS OFFICE ACTION IS MADE FINAL.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/25/2026 was filed. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
The 112b rejection has been withdrawn as Applicant resolved the antecedent basis issues.
Examiner thanks Applicant filed an amendment to expedite patent prosecution to overcome the prior art rejection. Applicant contends that the prior art fails to teach the limitation, “the first and second regions include a third region where the first and second regions overlap one another, but are not identical.” (emphasis added) However, Examiner asserts that Applicant’s reliance on the inclusion of “a third region” does not patentably distinguish in light of specification:1
Whenever two separate images or feature maps capture different yet adjacent parts of a field of view, any common area shared between them obviously forms an intersection—i.e., a third region. If there were no overlapping third region, the device could not perform a spatially coordinated element-by-element combination across boundaries.
Correspondence to the Specification: The Specification demonstrates that this overlap area not as a novel structural feature, rather as the operational domain where fusion occurs—noting that element-by-element addition is executed specifically “in the region of overlap” using coordinate tracking or starting values.2
Furthermore, following the extensive searches, Examiner concluded that Applicant’s arguments are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. (emphasis added)
Double Patenting
Claims 1 and 11–13 of this application are not patentably indistinct from claims 1 and 12–14 of Application No. 18/716,053. Pursuant to 37 CFR 1.78(f), when two or more applications filed by the same applicant or assignee contain patentably indistinct claims, elimination of such claims from all but one application may be required in the absence of good and sufficient reason for their retention during pendency in more than one application. Applicant is required to either cancel the patentably indistinct claims from all but one application or maintain a clear line of demarcation between the applications. The grounds of rejection set forth in the non-final are incorporated herein.
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 pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under pre-AIA 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1–12 are rejected under pre-AIA 35 U.S.C. § 103(a) as being unpatentable over Kamal et al. (U.S. 11,158,026 B1) in view of Gautam et al. (U.S. 10,706,335 B2) and further in view of Bai (U.S. 11,328,392 B2).
Regarding claim 1, Kamal discloses a method for fusing image data from at least one image acquisition sensor having the following steps:
a) receiving input image data, wherein the input image data comprises:
a first image which comprises a first region of a scene, and (Per Fig. 1A, Kamal discloses a first image 100. Kamal col. 5 lines 14–30. [a]n example of a first image 100 having a first field of view and a second image 110 having a second field of view are shown.)
a second image which comprises a second region of the scene, (Per Fig. 1A, Kamal discloses a second image 110 in a second field of view. Ibid.) wherein the first and second regions include a third region3 where the first and second regions overlap one another, but are not identical; (Per Fig. 1C, Kamal discloses a correspondence map 140 where an overlapping region 142 is represented in the first and second fields of view. Ibid. col. 6 line 45 – col. 7 line 4. [t]he inner region (i.e., inside box 141) corresponds to the overlapping region 142 of the first and second fields of view, and the outer region (i.e., outside box 141) corresponds to the non-overlapping region 143 of the first and second fields of view.)
d) computing a fused feature map (A fused feature map construed as a correspondence map to match a respective pixel in the second image to a corresponding pixel in the first image. See his col. 6 lines 33–44.) through element-by-element addition of the first and second output feature maps, wherein computing the fused feature map is based on positions of the first and second regions with respect to one another, such that elements4 (elements construed as an inner region 141 and an outer region 141 in a fusion operation. See his col. 13 lines 38–54 and Fig. 3.) in the third region are added. (Per Fig. 1C, Kamal discloses an alpha map 316 where an inner region and an outer region are analyzed to calculate contributions of pixels. Ibid. Then, along the border between the overlapping and non-overlapping regions of alpha map 316, there is a transition to whiter pixels (i.e., indicating a greater contribution from the warped second image to the output image), until the alpha map specifies the contribution to the fused image coming fully from the warped second image in the non-overlapping region (i.e., in the outermost region of alpha map 316).)
Kamal fails to specifically disclose the steps b), c) and e).
In related art, Gautam discloses a method for fusing image data from at least one image acquisition sensor having the following steps:
c) computing a first output feature map by a first convolution of the first feature map and computing a second output feature map by a second convolution of the second feature map. (Per Fig. 3, Gautam discloses a first feature map 302 input to a first residual layer 306; and a second feature map 322 input to a second residual layer 326. Gautam col. 12 lines 51–59. [f]irst feature map 302 is input to a set of residual layers 306 (denoted as “H”) and also in parallel into a set of convolutional/residual layers 304 (denoted as “F”). Similarly, second feature map 322 is input to a set of residual layers 326 (“H”) and also into a set of convolutional/residual layers 304 (“F”).)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Gautam into the teachings of Kamal to identify a given object within an image. Ibid. col. 1 lines 25–30.
However, Kamal as modified by Gautam, discloses the claimed invention, but fails to specifically disclose b) and e).
In related art, Bai discloses b) determining a first feature map with a first height and width based on the first image and determining a second feature map with a second height and width based on the second image; (Per Fig. 10D, Bai discloses a first clipped map with a first set width w-a and a height h-b, and a second clipped map with a second set width and a height. Bai col. 30 lines 40–67. [t]o obtain a first clipped map, an image with the first set width may be clipped from the right side and an image with the second set width may be clipped from the lower side of the object map to obtain a second clipped map,)
e) outputting the fused feature map. (Per Fig. 10D, Bai discloses a final object map after reconstructing the images. Ibid. col. 31 lines 37–47. [t]he post-processing flow after image inpainting is taken as an example for description in this example, that is, the object map is an inpainting result,)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Bai into the teachings of Kamal and Gautam to obtain an image with a super-resolution where scaling ratio is the same size before scaling. Ibid. col. 37 lines 57–67.
Regarding claim 2, Kamal as modified by Gautam and Bai, discloses the method, further comprising acquiring the first and the second image by the same image acquisition sensor. (Per Fig. 1, Gautam discloses object detector(s). Gautam col. 5 lines 39–54. [o]bject detectors can be classified into two types: (1) single-stage object detectors, and (2) two-stage object detectors.)
Regarding claim 3, Kamal as modified by Gautam and Bai, discloses the method, wherein the first and second images correspond to different levels of one or more image pyramids of an original image acquired by the at least one image acquisition sensor. (Per Fig. 10C, Bai discloses multiple layers based on an image. Bai col. 28 lines 33–56. [a]fter obtaining the fusion feature maps of multiple layers based on the image to be processed and the corresponding mask image,)
Regarding claim 4, Kamal as modified by Gautam and Bai, discloses the method, wherein the first region is an overview of the scene and the second region is a partial region of the overview region of the scene. (Per Fig. 9 at step 906, Gautam discloses a second image from a second perspective—i.e., not identical to the first perspective of the first image. Guatam col. 19 lines 40–45. [a]nd the second image from the second perspective by cross-referencing data related to the first image and the second image between the first and second perspectives with the object detector.)
Regarding claim 5, Kamal as modified by Gautam and Bai, discloses the method, wherein the first image has a first resolution and the second image has a second resolution is higher than the first resolution. (Per Fig. 6 at step S614, Bai discloses image super-resolution processing. Bai col. 18 lines 7–38. [u]sing super-resolution processing technology according to the scaling ratio ô, and the restored image may be fused with the original image at operation S617 to obtain the reconstructed original image.)
Regarding claim 6, Kamal as modified by Gautam and Bai, discloses the method, wherein two monocular cameras having an overlapping acquisition range are deployed as the at least one image acquisition sensor. (Gautam discloses cameras to detect a scene in a 3D space. Gautam col. 2 lines 28–35. [a] scene may comprise an area of which images are captured by one or more cameras.)
Regarding claim 7, it has been rejected in the same manner as claim 6.
Regarding claim 8, Kamal as modified by Gautam and Bai, discloses the method, wherein the first and second output feature maps have a same height and width in the region of overlap. (Per Fig. 10D, Bai discloses a first clipped map with a first set width w-a and a height h-b, and a second clipped map with a second set width and a height. Bai col. 30 lines 40–67. [t]o obtain a first clipped map, an image with the first set width may be clipped from the right side and an image with the second set width may be clipped from the lower side of the object map to obtain a second clipped map,)
Regarding claim 9, Kamal as modified by Gautam and Bai, discloses the method, wherein a height and width of the fused feature map are determined by a rectangle which surrounds the first and the second output feature maps. (Through Figs. 6–7, Bai discloses candidate region based on the image features of the image. Bai col. 17 line 19 – col. 18 line 6. [a]nd the image may be clipped at operation S612 or operation S613 according to the region corresponding to the rectangular box in the original image to obtain the image to be processed including the object region to be removed.)
Regarding claim 10, it has been rejected in the same manner as claim 9.
Regarding claim 11, Kamal as modified by Gautam and Bai, discloses the method, wherein the fused feature map is generated in an encoder of an artificial neural network which is configured to determine ADAS/AD-relevant information. (Per Fig. 1, Bai discloses an encoding stage to extract a feature map of an image. Bai col. 7 line 38 – col. 8 line 3. The encoding stage is mainly used to extract the feature map of the preprocessed image, i.e. the image to be processed.)
Regarding claim 12, it has been rejected in the same manner as claim 11.
Claims 13–15 are rejected under 35 U.S.C. § 103 as being unpatentable over Gautam et al. (U.S. 10,706,335 B2) in view of Bai et al. (U.S. 11,328,392 B2).
Regarding claim 13, Gautam discloses a system for fusing image data from at least one image acquisition sensor, (Fig. 1, 100 a computing system) comprising an input interface, (Fig. 1, 104 data storage) a data processing unit (Fig. 1, 102 a processor) and an output interface, (Fig. 1, 104 data storage) wherein a) the input interface is configured to receive input image data, wherein the input image data comprise:
a) the input interface is configured to receive input image data, wherein the input image data comprise:
a first image which comprises a first region of a scene, (Per Fig. 9 at step 902, Gautam’s object detector discloses a first image within a first perspective of a scene—i.e., a first region of a scene. Gautam col. 19 lines 31–35. [a] first image from a first positional angle, wherein the first image is from a first perspective of a scene.) and a second image which comprises a second region of the scene, wherein the first and second regions overlap one another (wherein the first and second regions overlap one another construed as cross-referencing data), but are not identical; (Per Fig. 9 at step 906, Gautam discloses a second image from a second perspective—i.e., not identical to the first perspective of the first image. Ibid. col. 19 lines 40–45. [a]nd the second image from the second perspective by cross-referencing data related to the first image and the second image between the first and second perspectives with the object detector.)
c) compute a first output feature map by a first convolution of the first feature map and computing a second output feature map by a second convolution of the second feature map. (Per Fig. 3, Gautam discloses a first feature map 302 input to a first residual layer 306; and a second feature map 322 input to a second residual layer 326. Ibid. col. 12 lines 51–59. [f]irst feature map 302 is input to a set of residual layers 306 (denoted as “H”) and also in parallel into a set of convolutional/residual layers 304 (denoted as “F”). Similarly, second feature map 322 is input to a set of residual layers 326 (“H”) and also into a set of convolutional/residual layers 304 (“F”).)
However, Gautam fails to specifically disclose b) determine a first feature map with a first height and width based on the first image and determining a second feature map with a second height and width based on the second image; d) compute a fused feature map through element-by-element addition of the first and second output feature maps, wherein computing the fused feature map is based on positions of the first and the second regions with respect to one another, such that the elements in the region of overlap are added; and e) output the fused feature map.
In related art, Bai discloses the data processing unit configured to: (Fig. 19, 4001 a processor)
b) determine a first feature map with a first height and width on the basis of the first image and determining a second feature map with a second height and width on the basis of the second image; (Per Fig. 10D, Bai discloses a first clipped map with a first set width w-a and a height h-b, and a second clipped map with a second set width and a height. Bai col. 30 lines 40–67. [t]o obtain a first clipped map, an image with the first set width may be clipped from the right side and an image with the second set width may be clipped from the lower side of the object map to obtain a second clipped map,)
d) compute a fused feature map through element-by-element addition (element-by-element addition construed as element values of element points) of the first and second output feature maps, (Per Fig. 10D, Bai discloses element values in a location of two weight maps. Ibid. col. 31 lines 1–22. The first weight map and the second weight map may be randomly generated images, such as a noise image in which the element values only include 0 and 1 in the randomly generated image.) wherein computing the fused feature map is based on positions of the first and the second regions with respect to one another, such that the elements in the region of overlap are added; and (Per Fig. 10D, Bai discloses a fused map where the element points are represented. Ibid. col. 31 lines 25–34. [t]he element value of the element point in the fused map can be obtained based on the element values of the element points in the first clipped map and the second clipped map…)
e) output the fused feature map. (Per Fig. 10D, Bai discloses a final object map after reconstructing the images. Ibid. col. 31 lines 37–47. [t]he post-processing flow after image inpainting is taken as an example for description in this example, that is, the object map is an inpainting result,)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Bai into the teachings of Gautam to obtain an image with a super-resolution where scaling ratio is the same size before scaling. Ibid. col. 37 lines 57–67.
Regarding claim 14, Gautam as modified by Bai, discloses wherein the system comprises a convolutional neural network having an encoder and at least one decoder and wherein the input interface, the data processing unit and the output interface are implemented in the encoder such that the encoder is configured to generate the fused feature map and wherein the at least one decoder is configured to realize an ADAS/AD detection function at least based on the fused feature map. (Per Fig. 1, Bai discloses an encoding stage to extract a feature map of an image. Bai col. 7 line 38 – col. 8 line 3. The encoding stage is mainly used to extract the feature map of the preprocessed image, i.e. the image to be processed.)
Regarding claim 15, Gautam as modified by Bai, discloses the method, further comprising acquiring the first and the second image by the same image acquisition sensor. (Per Fig. 1, Gautam discloses object detector(s). Gautam col. 5 lines 39–54. [o]bject detectors can be classified into two types: (1) single-stage object detectors, and (2) two-stage object detectors.)
Conclusion
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 BENEDICT LEE whose telephone number is (571)270-0390. The examiner can normally be reached 10:00-17:00 (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen R. Koziol can be reached at (408) 918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BENEDICT E LEE/Examiner, Art Unit 2665
/Stephen R Koziol/Supervisory Patent Examiner, Art Unit 2665
1 See MPEP § 2111, Claim Interpretation; Broadest Reasonable Interpretation. In re Prater, 415 F.2d 1393, 1404-05, 162 USPQ 541, 550-51 (CCPA 1969), the Court explained that "reading a claim in light of the specification, to thereby interpret limitations explicitly recited in the claim, is a quite different thing from ‘reading limitations of the specification into a claim,’ to thereby narrow the scope of the claim by implicitly adding disclosed limitations which have no express basis in the claim."
2 In Applicant’s Spec. ¶61 step d), he establishes that the overlap as an operational domain (“region of overlap”) where element-by-element addition occurs based on relative positioning. ¶163 confirms that managing the overlapping third region is handled through coordinate adjustment parameters (e.g., starting values
x
s
,
y
s
) rather than unique structural limitations in the feature extraction architecture.
3 Examiner dissents that Applicant specifically discloses “a third region”—i.e., another region—in light of Spec. ¶64 and ¶163. See Applicant’s remarks p. 1 and Examiner’s arguments pp. 2–3.
4 Examiner referred to Applicant’s Spec. ¶46 and cannot fathom what “elements” truly means in a fused map.
Prosecution Insights