Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) was filed on 11/21/2024. 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 limitations are: “image classification module…” in claims 1-3.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they 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 these limitations 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 § 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 1-20 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claims 1-20, the claims recite a “low-light image” It is unclear from the context of the claim of what is an image that is “low-light” . One of ordinary skill in the art would ask “What if someone perceives an image as having low lighting and another person as having sufficient or a lot of lighting?”, “Isn’t “low lighting” subject to a personal opinion?” “Does low lighting mean that the bottom part of the image contain lighting?” “Does “low-light” represent a lower lighting color temperature?”. Therefore one of ordinary skill in the art would not be able to apprise the scope of the claim for reasons regarding clarity.
Regarding claims 1-20, the claims recite a “normal image” It is unclear from the context of the claim of what is an image that is “normal” . One of ordinary skill in the art would ask “What if someone perceives an image as being normal and another person as being abnormal?”, “What does specifically “normal” mean?“, “Isn’t “normal” subject to a personal opinion?” “What does a “normal” image represent? Is it the content? Is it the lighting? “Is it the objects?”, “Does “normal” represent better lighting?” “What is the difference between normal and original?”, “What is the scope of something that is normal?”. Therefore one of ordinary skill in the art would not be able to apprise the scope of the claim for reasons regarding clarity.
Regarding claims 1-20, the claims recite an “original image” It is unclear from the context of the claim of what is an image that is “original” . One of ordinary skill in the art would ask “What if someone perceives an image as being original and another person as being unoriginal?”, “Isn’t “original” subject to a personal opinion?” “What does a “original” image represent? Is it the content? Is it the lighting? “Is it the objects?” “Is it an image that has never been acquired before?”, “Does “original” represent better lighting?” “What is the difference between normal and original?”, “What is the scope of something that is original?”. Therefore one of ordinary skill in the art would not be able to apprise the scope of the claim for reasons regarding clarity.
Regarding claim 3, the claim recites “low-light” and “low-luminance” pixels. It is unclear from the context of the claim of what is an image that is “low-luminance” . One of ordinary skill in the art would ask “What if someone perceives an image as having low lighting and another person as having sufficient or a lot of lighting?”, “Isn’t “low luminance” subject to a personal opinion?” “Does low luminance mean bottom part of the image in which pixels contain lighting?”, “Is it the quantity of pixels on the lower part of the image which contain lighting?” “Does “low-luminance” represent a lower lighting color temperature?”. Therefore one of ordinary skill in the art would not be able to apprise the scope of the claim for reasons regarding clarity.
Regarding claims 4-10 and 14-20, the claims recite a “low-light enhancement image” It is unclear from the context of the claim of what is an image that is “low-light enhancement” . One of ordinary skill in the art would ask “What if someone perceives an image as having low lighting enhancement and another person as having sufficient or a lot of lighting?”, “Isn’t “low lighting” subject to a personal opinion?” “Does low lighting mean that the bottom part of the image contain lighting?” “Does “low-light” represent a lower lighting color temperature?”. Therefore one of ordinary skill in the art would not be able to apprise the scope of the claim for reasons regarding clarity.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(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 1-4 and 10-14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Jung et. al. (KR 10-2593677 B1) .
As per claim 1, Jung teaches “An apparatus for detecting an object of an image, the apparatus comprising:
an image classification module that distinguishes an input image as a low-light image or a normal image based on a specified criterion; and” (See page 2 paragraph 9 “An object detection image preprocessing device according to the present invention for achieving the above object includes: an image acquisition unit that acquires and outputs a frame image;…” See also page 3 paragraph 3 “If the illuminance included in the image quality status information of the frame image is less than a preset standard illuminance, an illuminance control unit performs low light image enhancement processing and changes the illuminance to a preset recommended illuminance;” When the Quality improvement unit detects that the illuminance is less than a threshold it is interpreted as low-light, if it passes the threshold it is interpreted as a “normal image”. See also page 5 paragraphs 4-7. Jung)
“a processor that overlaps anchor boxes of a plurality of images generated by performing at least one image process on an original image, which is a low-light image distinguished by the image classification module, and then performs an object detection algorithm on the overlapping anchor boxes.” (See page 5 paragraph 13, the anchor boxes defined, are overlapping and used for object detection as seen on fig. 4 “Specifically, the object detection unit 50 defines anchor boxes 511 of different sizes for detecting objects from the frame image as shown in 501 of FIG. 4, and applies each of the defined anchor boxes 511 to create an anchor A target object of a size corresponding to the box is detected, and target object information including the number of target objects detected for each anchor box (511-1, 511-2, 511-3, and 511 4) is generated. The size of the anchor box 511 may be defined as 64 pixels, 32 pixels, 16 pixels, 8 pixels, etc.” See also page 5 paragraphs 4-7 “The image quality state detection unit 40 includes a resolution detection unit 41, a blurring detection unit 42, and an illumination detection unit 43, and detects the image quality status of the frame image input from the image improvement control unit 100. Generate image quality status information according to the image quality status.” Jung)
Claim 11 is rejected under the same analysis as claim 1.
As per claim 2, Jung teaches “the apparatus of claim 1, wherein the processor, in order to distinguish whether the input image is a low-light image or a normal image, distinguishes whether the input image is a low-light image or a normal image based on a luminance value of each pixel included in the input image through the image classification module.” (See page 3 paragraph 3 “If the illuminance included in the image quality status information of the frame image is less than a preset standard illuminance, an illuminance control unit performs low light image enhancement processing and changes the illuminance to a preset recommended illuminance;” When the Quality improvement unit detects that the illuminance is less than a threshold it is interpreted as low-light, if it passes the threshold it is interpreted as a “normal image”. See also page 5 paragraphs 4-7 and 10-11. “The illuminance detection unit 43 detects the average illuminance of the frame image. That is, the image quality status detection unit 40 generates image quality status information including the resolution of the frame image, the presence and location of blurring, and the average illuminance.” It is well known to one of ordinary skill in the art that the average illuminance is based on the luminance value of individual pixels in the image. Jung)
Claim 12 is rejected under the same analysis as claim 2.
As per claim 3, Jung teaches “the apparatus of claim 1, wherein the image classification module distinguishes the low-light image from the normal image according to whether the number of pixels designated as low-luminance in the input image is greater than or equal to a threshold value.” (See page 3 paragraph 3 “If the illuminance included in the image quality status information of the frame image is less than a preset standard illuminance, an illuminance control unit performs low light image enhancement processing and changes the illuminance to a preset recommended illuminance;” When the Quality improvement unit detects that the illuminance of the pixels is less than a threshold it is interpreted as low-light, if it passes the threshold it is interpreted as a “normal image”. See also page 5 paragraphs 4-7. It is well known to one of ordinary skill in the art that the average illuminance is based on the luminance value of individual pixels in the image. The average contains the number of pixels along with the luminance. Jung)
Claim 13 is rejected under the same analysis as claim 3.
As per claim 4, Jung teaches “the apparatus of claim 1, wherein the processor, in order to overlap the anchor boxes, generates anchor boxes for a low-light enhancement image generated by applying a low-light enhancement algorithm to the original image.” (The images are first enhanced and then the anchor boxes are generated. See page 2 paragraph 9 “An object detection image preprocessing device according to the present invention for achieving the above object includes: an image acquisition unit that acquires and outputs a frame image;…” See also page 3 paragraph 3 “If the illuminance included in the image quality status information of the frame image is less than a preset standard illuminance, an illuminance control unit performs low light image enhancement processing and changes the illuminance to a preset recommended illuminance;” See also page 5 paragraph 13, the anchor boxes defined, are overlapping and used for object detection as seen on fig. 4. Jung)
Claim 14 is rejected under the same analysis as claim 4.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 5-6 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Jung in view of Huang et. al. (CN 116452850 A) .
As per claim 5, Jung already teaches “the apparatus of claim 1, wherein the processor, in order to overlap the anchor boxes, generates anchor boxes for… the low-light enhancement image of the original image.”, however Jung does not teach “generates anchor boxes for rotated images of the original image…”
Huang teaches “generates anchor boxes for rotated images of the original image…” (See page 7 last paragraph, the images are rotated “In the embodiment, by turning, pixel RGB value conversion, adding noise point, reducing the brightness of the picture, rotating at 45 degrees, 90 degrees rotation and image scaling and so on image processing mode, so as to generate several times of the original image of the picture number, effectively expands the data set, increases the diversity of the data.”. See also page 8 paragraphs 2-12, it shows the generated anchor boxes for the images. “S4, using K-means clustering algorithm, clustering the target frame of the training set, automatically generating a group of anchor frame more suitable for user-defined data set, adjusting the size and length-width ratio of anchor in the model configuration file…” See also page 9 paragraphs 5-9. “…judging the overlapped anchor and the IOU value of the target frame by executing NMS method, so as to obtain the refined candidate ROI area…” Huang)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Jung with the teachings of Huang to generate anchor boxes for rotated images. The modification would have been motivated by the desire to effectively expand the data set and increase the diversity of the data, therefore it is an improvement, as suggested by Huang (See page 7 last paragraph, the images are rotated “In the embodiment, by turning, pixel RGB value conversion, adding noise point, reducing the brightness of the picture, rotating at 45 degrees, 90 degrees rotation and image scaling and so on image processing mode, so as to generate several times of the original image of the picture number, effectively expands the data set, increases the diversity of the data.” Huang)
Claim 15 is rejected under the same analysis as claim 5.
As per claim 6, Jung already teaches “the apparatus of claim 1, wherein the processor, in overlapping the anchor boxes, generates anchor boxes of the original image, the low-light enhancement image of the original image… for the original image and the low-light enhancement image of the original image, and overlaps the generated anchor boxes.” (See page 5 paragraph 13, the anchor boxes defined, are overlapping and used for object detection as seen on fig. 4 “Specifically, the object detection unit 50 defines anchor boxes 511 of different sizes for detecting objects from the frame image as shown in 501 of FIG. 4, and applies each of the defined anchor boxes 511 to create an anchor A target object of a size corresponding to the box is detected, and target object information including the number of target objects detected for each anchor box (511-1, 511-2, 511-3, and 511 4) is generated. The size of the anchor box 511 may be defined as 64 pixels, 32 pixels, 16 pixels, 8 pixels, etc.” See also page 4 paragraph 7 “In addition, the present invention applies anchor boxes with different sizes to the acquired image to check the number of each detected object, and when a small-sized object exists, an anchor box applied to detect a small-sized object is used. After determining the number of tilings (number of divisions) in response to the size of the box (size of the small target object), the obtained image is tiled with the determined number of tilings, and the tiled segmented image is converted to super-resolution, thereby detecting and classifying objects. It has the effect of improving recognition rate and accuracy.” The tilings are composed of different images.), however Jung does not teach “the rotated images…”
Huang teaches “the rotated images… and overlaps the generated anchor boxes” (See page 7 last paragraph, the images are rotated “In the embodiment, by turning, pixel RGB value conversion, adding noise point, reducing the brightness of the picture, rotating at 45 degrees, 90 degrees rotation and image scaling and so on image processing mode, so as to generate several times of the original image of the picture number, effectively expands the data set, increases the diversity of the data.”. See also page 8 paragraphs 2-12, it shows the generated anchor boxes for the images. “S4, using K-means clustering algorithm, clustering the target frame of the training set, automatically generating a group of anchor frame more suitable for user-defined data set, adjusting the size and length-width ratio of anchor in the model configuration file…” See also page 9 paragraphs 5-9. “…judging the overlapped anchor and the IOU value of the target frame by executing NMS method, so as to obtain the refined candidate ROI area…” Huang)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Jung with the teachings of Huang to generate anchor boxes for rotated images. The modification would have been motivated by the desire to effectively expand the data set and increase the diversity of the data, therefore it is an improvement, as suggested by Huang (See page 7 last paragraph, the images are rotated “In the embodiment, by turning, pixel RGB value conversion, adding noise point, reducing the brightness of the picture, rotating at 45 degrees, 90 degrees rotation and image scaling and so on image processing mode, so as to generate several times of the original image of the picture number, effectively expands the data set, increases the diversity of the data.” Huang)
Claim 16 is rejected under the same analysis as claim 6.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Jung in view of Huang and further in view of Mustikovela et. al. (CN 114787879 A).
As per claim 7, Jung in view of Huang already teaches “the apparatus of claim 6, wherein the processor, in order to overlap the anchor boxes of the rotated image, applies, to the anchor boxes… with respect to a rotation direction and a rotation angle of the rotated image.” (See page 7 last paragraph, the images are rotated. It is well known to one of ordinary skill in the art that a rotation/positive rotation goes in a counterclockwise direction, and a reverse/negative rotation goes in a clockwise direction. It is also well known to one ordinary skill in the art that rotations can be negative. “In the embodiment, by turning, pixel RGB value conversion, adding noise point, reducing the brightness of the picture, rotating at 45 degrees, 90 degrees rotation and image scaling and so on image processing mode, so as to generate several times of the original image of the picture number, effectively expands the data set, increases the diversity of the data.”. See also page 8 paragraphs 2-12, it shows the generated anchor boxes for the images. “S4, using K-means clustering algorithm, clustering the target frame of the training set, automatically generating a group of anchor frame more suitable for user-defined data set, adjusting the size and length-width ratio of anchor in the model configuration file…” See also page 9 paragraphs 5-9. “…judging the overlapped anchor and the IOU value of the target frame by executing NMS method, so as to obtain the refined candidate ROI area…” Huang), however Jung in view of Huang does not teach “a reverse rotation direction and a reverse rotation angle”
Mustikovela teaches “a reverse rotation direction and a reverse rotation angle” (See page 27 paragraphs 3-4 and page 28 first and second paragraph, it shows a reverse angle and reverse direction “In at least one embodiment, the input image is selected from the training image set. In at least one embodiment, transform the input image application to generate a transformed image… In at least one embodiment, the first direction is predicted for the input image and the second direction is predicted for the horizontal turnover version of the input image. In at least one embodiment, based on whether some attribute is established to calculate loss. In at least one embodiment, the transform or inverse transform is applied to the predicted direction of the transformed version of the input image. In at least one embodiment, if the input image is rotated (Φ, θ, ψ) angle to generate the transformed image, the direction of the transformed image of the inference can rotate reversely (-theta, - theta, -ψ) angle.” )” “In at least one embodiment, using convolution neural network CNN) based on the feature similarity of the image pair to calculate the viewpoint constant distance. In at least one embodiment, the anchor image is selected from the set of training images.” Therefore both anchor images and original images are compared and the training set contains both the original/anchor along with their respective reversed versions. Mustikovela)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Jung and Huang with the teachings of Mustikovela to apply a reverse direction and reverse angle to the anchor boxes respective to the direction and angle of the images. The modification would have been motivated by the desire to generate a case in which there is zero loss which commonly results in better accuracy, therefore it is an improvement, as suggested by Mustikovela (See page 27 paragraphs 3-4 and page 28 first and second paragraph. “In at least one embodiment, if the input image is rotated (Φ, θ, ψ) angle to generate the transformed image, the direction of the transformed image of the inference can rotate reversely (-theta, - theta, -ψ) angle. In at least one embodiment, by comparing the azimuth angle of the first direction of the input image, the elevation and the tilt amplitude with the second direction of the transformed image to calculate the loss, wherein when the amplitude of each direction parameter is equal to generate zero loss… In at least one embodiment, the neural network viewpoint of the predicted anchor image is predicted and the second viewpoint of the nearest neighbor image is predicted and the loss is calculated, such that the closer distance between the viewpoint is corresponding to less loss.” Mustikovela)
Claim 17 is rejected under the same analysis as claim 7.
Claims 8-10 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Jung in view of Huang and further in view of Tang et. al. (CN 113052006 A)
As per claim 8, Jung already teaches “the apparatus of claim 1, wherein the processor overlaps the anchor boxes of the plurality of images… the overlapping anchor boxes at one time to detect an object.”, however Jung does not teach “and applies a non-maximum suppression (NMS) algorithm…”
Tang teaches “and applies a non-maximum suppression (NMS) algorithm…” (See page 12 penultimate paragraph “…removing the overlapping frame process is mainly the candidate target after filtering to remove the redundant frame close to the overlapping degree, specifically using method is non-maximum suppression (nms). the basic step is each time selecting the prediction frame with the highest confidence score, calculating the IoU with the remaining frame, when IoU is greater than a certain threshold value, deleting the frame, then continuously selecting the frame with the highest score from the unprocessed frame, repeating the above process…” Tang)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to combine the teachings of Jung with the teachings of Tang to utilize a non maximum suppression algorithm to detect an object. The modification would have been motivated by the desire to filter redundant frames and properly detect objects that are close to each other, therefore it is an improvement, as suggested by Tang (See page 12 penultimate paragraph “…removing the overlapping frame process is mainly the candidate target after filtering to remove the redundant frame close to the overlapping degree, specifically using method is non-maximum suppression (nms). the basic step is each time selecting the prediction frame with the highest confidence score, calculating the IoU with the remaining frame, when IoU is greater than a certain threshold value, deleting the frame, then continuously selecting the frame with the highest score from the unprocessed frame, repeating the above process…”. See also page 12 paragraph 6 “when IoU is less than the threshold value, then selecting the maximum IoU anchor responsible for detecting the current target frame box. The advantage is that it can properly solve the problem that the object is not detected when the object is close to each other…”. See also page 4 last paragraphs and page 5 first paragraph. Tang)
Claim 18 is rejected under the same analysis as claim 8.
As per claim 9, Jung in view of Tang already teaches “the apparatus of claim 8, wherein the processor selects”, however Tang also teaches “an anchor box having a highest probability of being an object based on a degree of overlap between a plurality of overlapping anchor boxes for each image through the NMS algorithm.” (See page 12 penultimate paragraph, the prediction frame contains the anchor box with the highest probability. The score also indicates a probability. “…removing the overlapping frame process is mainly the candidate target after filtering to remove the redundant frame close to the overlapping degree, specifically using method is non-maximum suppression (nms). the basic step is each time selecting the prediction frame with the highest confidence score, calculating the IoU with the remaining frame, when IoU is greater than a certain threshold value, deleting the frame, then continuously selecting the frame with the highest score from the unprocessed frame, repeating the above process…” The IOU (intersection over union) presents the overlap. See also page 12 paragraph 6 “the main process is as for all the target frame in each picture, orderly with 12 anchor calculating IoU, the IoU greater than the threshold value of the anchor is used for detecting the current target frame box, here the threshold is defined as 0.3; when IoU is less than the threshold value, then selecting the maximum IoU anchor responsible for detecting the current target frame box.” See also page 4 last paragraphs and page 5 first paragraph. Tang)
Claim 19 is rejected under the same analysis as claim 9.
As per claim 10, Jung in view of Tang already teaches “the apparatus of claim 9, wherein the processor selects an anchor box among the plurality of overlapping anchor boxes that has an intersection of union (IoU) less than a threshold value and has a maximum confidence value.” (See page 12 paragraph 6 “the main process is as for all the target frame in each picture, orderly with 12 anchor calculating IoU, the IoU greater than the threshold value of the anchor is used for detecting the current target frame box, here the threshold is defined as 0.3; when IoU is less than the threshold value, then selecting the maximum IoU anchor responsible for detecting the current target frame box.” See also page 4 last paragraphs and page 5 first paragraph. “if the target frame box and each of the IoU of the Anchor less than the preset threshold value, then selecting the maximum of the IoU of the anchor for detecting corresponding to the target frame box”. See also page 5 paragraph 7 “and the balance parameter of the foreground confidence and the background confidence is respectively representing the background predicted value and the maximum value of all real frame IoU is less than the preset value thresh to calculate the current background; it satisfies 1;…” Tang)
Claim 20 is rejected under the same analysis as claim 10.
Conclusion
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/DYLAN JOHN MENDEZ MUNIZ/Examiner, Art Unit 2675
/ANDREW M MOYER/Supervisory Patent Examiner, Art Unit 2675
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