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 .
Claim Objections
Claim 8 is objected to because of the following informalities: the claim limitation “each the human body” should recite “each of the two or more human bodies” for proper grammar and antecedent basis. Appropriate correction is required.
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 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) 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):
(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). The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) 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). The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) 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) 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) 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), 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) are: “photographic unit” in claim 15, “processing unit” in claim 15, “a human body area ratio calculation module” in claim 15, “cropping range calculation module” in claim 15, and “focusing and cropping module” in claim 15.
Because these claim limitation(s) are being interpreted under 35 U.S.C. 112(f), 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), applicant may: (1) amend the claim limitation(s) to avoid them being interpreted under 35 U.S.C. 112(f) (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 8, and 15-17 are rejected are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without integration into a practical application or recitation of significantly more.
In the analysis below, the method of independent claim 1 is considered representative of independent claims 15 and 16, and independent claim 8 is considered representative of independent claim 17, since claims 15-17 recite identical steps despite being directed to different statutory matter, respectively to independent claims 1 and 8. Furthermore, independent claims 1, 8, and 15-17 are directed to one of the four statutory categories of eligible subject matter (a system for independent claim 15, and computer-readable media for independent claims 16-17); thus, the claims pass Step 1 of the Subject Matter Eligibility Test (See flowchart in MPEP 2106).
Step 2A, prong 1 analysis:
Independent claim 1 is directed to identifying a human body in an initial image, calculating a human body area ratio by identifying a first upper boundary coordinate and a first lower boundary coordinate of the human body in the initial image and defining a human body coverage area for covering the human body, and defining a first focal coordinate of a center point of the human body coverage area, in order to calculate a human body area ratio of the human body coverage area occupying an original size of the initial image, calculating a cropping range by identifying a second upper boundary coordinate and a second lower boundary coordinate in the original size according to a cropping ratio corresponding to the human body area ratio to define a cropping area, and defining a second focal coordinate of a center point of the cropping area, and focusing and cropping by coinciding the first focal coordinate and the second focal coordinate, when the human body coverage area is covered within the cropping area in the initial image, the cropping area is selected as a cropped image.
Each of the above steps can be performed mentally. In particular, a person takes images of another human with a smartphone and analyzes the photo with their own eyes after taking the image to identify that there is a human in the photo. Using, generic photo editing software or using a printed out photo, the person draws a bounding box around the human and identifies two corner points of the bounding box and a center point; they may make measurements of the bounding box around the human and create coordinates for the corner points with accurate measurements that is a human body coverage area; the person also takes measurements using a ruler on a printed photo, or using photo editing software, so the person knows the size of the total image and the size of the human bounding box which then simple math is used to calculate a human body coverage ratio or percentage of the image the human body covers; then, the person decides a good cropping zone bounding box that is centered with the entire image with its own corner coordinates, size, and center point; the cropping zone bounding box percentage of the total image is chosen based on the percentage of coverage the human bounding box covers in the total image; then, the cropping bounding box is moved so the center points of both boxes line up so the cropping bounding box surrounds the human totally and then the cropping of the image occurs; therefore, this process can all be done mentally.
Independent claim 8 is directed to all the same steps as claim 1, except with additional steps of identifying two or more human bodies in an initial image, and calculating a human body area ratio by identifying a first upper boundary coordinate and a first lower boundary coordinate of each the human body in the initial image, and taking a maximum longitudinal ordinate value and a minimum horizontal ordinate value to define a maximum upper boundary coordinate, and taking a minimum longitudinal ordinate value and a maximum horizontal ordinate value to define a maximum lower boundary coordinate, the maximum upper boundary coordinate and the maximum lower boundary coordinate are used to define a human body coverage area for covering all the human bodies, and defining a first focal coordinate of a center point of the human body coverage area, in order to calculate a human body area ratio of the human body coverage area in the initial image.
Each of the above steps can be performed mentally. In particular, when two or more people are in an image then there will be multiple bounding boxes drawn by a person around each person to identify them in the image and then coordinates have to be found that maximally turn the N number of bounding boxes for each human body into a single bounding encompassing all the humans in the image by deciding which corner coordinates from the bounding boxes are the max lower and upper boundary; this, again is easily accomplished using a printed out image and pen or simple photo editing software. All steps after are analogous to claim 1 in finding the percentage ratio the human bodies take up in the image relative to the original image size. therefore, this process can all be done mentally.
As such, the description in independent claims 1, 8, and 15-17 is an abstract idea – namely, a mental process. Accordingly, the analysis under prong one of step 2A of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
Additional elements:
The additional element recited in independent claims 1, 13, and 19 are an electronic device, artificial intelligence, a photographic unit, a processing unit, a human body area ratio calculation module, a cropping range calculation module, and a focusing and cropping module.
Step 2A, prong 2 analysis:
The above-identified additional elements do not integrate the judicial exception into a practical application. All modules, devices, and AI are generic with no specific functioning beyond a human’s capabilities to carry out the claimed functionality.
The step of a human body identified in an initial image by artificial intelligence amounts to insignificant pre-solution activity which does not integrate the claimed mental process into a practical application (See MPEP 2106.05(g)).
Each of the other additional elements (an electronic device, artificial intelligence, a photographic unit, a processing unit, a human body area ratio calculation module, a cropping range calculation module, and a focusing and cropping module) amounts to merely using different devices as tools to perform the claimed mental process. Implementing an abstract idea on a computer or using known generic devices does not integrate a judicial exception into a practical application (See MPEP 2106.05(f)).
Moreover, the additional elements of the claims do not recite an improvement in the functioning of a computer or other technology or technical field, the claimed steps are not performed using a particular machine, the claimed steps do not effect a transformation, and the claims do not apply the judicial exception in any meaningful way beyond generically linking the use of the judicial exception to a particular technological environment (See MPEP 2106.04(d)). Therefore, the analysis under prong two of step 2A of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
Step 2B:
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As noted above, the step of a human body identified in an initial image by artificial intelligence amounts to insignificant pre-solution activity which does not integrate the claimed mental process into a practical application (See MPEP 2106.05(g)).
Each of the other additional elements (an electronic device, artificial intelligence, a photographic unit, a processing unit, a human body area ratio calculation module, a cropping range calculation module, and a focusing and cropping module) are generic computer features which perform generic computer functions that are well-understood, routine, and conventional and do not amount to more than implementing the abstract idea with a computerized system. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea).
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation, and mere implementation on a generic computer does not add significantly more to the claims. Accordingly, the analysis under step 2B of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
For all of the foregoing reasons, independent claims 1, 8, and 15-17 do not recite eligible subject matter under 35 USC 101.
Dependent claims 2-7 and 9-14 recite generic photo editing such as scaling, setting preset values for cropping, limits to the cropping region, adjusting the cropping size if it does not encapsulate the human bodies, adjusting the cropping size if it bigger than the image itself by changing longitudinal and latitudinal aspects of the cropping zone, shifting the cropping bounding box or the human body bounding box, and correlating the cropping bounding box percentage of the total image to the human body bounding box percentage coverage so the cropping is correct in encapsulating the human bodies; further, a person has the ability to design a correlation table between percentages of how much the human bodies take up in an image to what percent of the image should be cropped in response; these steps are accomplished by human vision with pen, a ruler, and a printed out image or simple photo editing software; therefore, this process can all be done mentally.
Therefore, dependent claims 2-7 and 9-14 recite the same abstract idea of a mental process which can be performed in the mind with the aid of pen and paper, and are therefore also rejected under 35 U.S.C. 101.
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, 3-4, 8, 10-11, and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over International Patent Application Publication No.: WO 2021147648 A1 (Wu et al.) (hereinafter Wu), in view of U.S. Patent Application Publication No.: 2022/0321788 (Chen et al.) (hereinafter Chen), and in view of Korean Patent Publication No.: KR 102430071 B1 (Yi et al.) (hereinafter Yi).
Regarding claim 1, Wu teaches an image cropping processing method, executed by an electronic device reading an executable code, when there is a human body identified in an initial image by artificial intelligence, cropping processing to the initial image is executed, comprising the following steps: (Wu, page 7, para. 7-9; page 8, para. 1; page 22, para. 9: “In the embodiment of the present application, the electronic device may obtain an image sample containing the human body in advance to train a deep learning model such as a convolutional neural network to obtain a trained model. The trained model can be used as the portrait detection in the embodiment of the present application. For example, after obtaining the preview image, the electronic device may use a pre-trained scene recognition model to perform scene recognition on the preview image to confirm whether there is a single human body in the preview image. When there is a single human body in the preview image, the electronic device can use a pre-trained portrait detection model to perform portrait detection on the preview image to obtain a human body bounding box. When there is no human body or multiple human bodies in the preview image, the electronic device can directly end the process. In some embodiments, the electronic device may use a pre-trained target detection model to perform target detection on the preview image to obtain a bounding box of the human body. It should be noted that the target detection model only detects the human body in the preview image, and does not detect other objects.”; “For example, after obtaining the percentage of the area of the human body bounding box in the preview image, the electronic device can also crop the human body image from the preview image");
calculating a human body area ratio: identifying a first upper boundary coordinate and a first lower boundary coordinate of the human body in the initial image and defining a human body coverage area for covering the human body (Wu, page 8, para. 1-5: “In 203, the electronic device determines the width and height of the bounding box of the human body. In 204, the electronic device calculates the ratio of width to height. For example, after obtaining the human body bounding box, the electronic device can obtain the upper left corner coordinates and the lower right corner coordinates of the human body bounding box, and determine the width and height of the human body bounding box by the upper left corner coordinates of the human body bounding box and the upper right corner coordinates of the human body bounding box, and calculate the ratio of the width of the human body bounding box to the height of the human body bounding box. Among them, the coordinates of the upper left corner can be expressed as (x1, y1), and the coordinates of the lower right corner can be expressed as (x2, y2), then the width of the human body bounding box=|x2-x1|, the height of the human body bounding box=|y2-y1|, x1 and y1 are the abscissa and ordinate of the upper left corner of the human body bounding box in the screen coordinate system; x2 and y2 are the abscissa and ordinate of the lower right corner of the human body bounding box in the screen coordinate system, respectively. For example, assuming that the coordinates of the upper left corner of the human body bounding box are (10, 40) and the coordinates of the lower right corner of the human body bounding box are (70, 60), the width of the human body bounding box is 60, the height of the human body bounding box is 20, and the body boundary the ratio of the width of the box to the height of the bounding box of the human body is 4.”), and
defining a first focal coordinate of a center point of the human body coverage area (Wu, page 18, para. 2: “If there are no preset key points in the human body key point set, the electronic device can obtain the center coordinates of the human body boundary box”), in order to calculate a human body area ratio of the human body coverage area occupying an original size of the initial image (Wu, “For example, after obtaining the ratio of the width of the human body boundary box to the height of the human body boundary box, the electronic device may also determine the area percentage of the human body boundary box in the preview image. For example, if the area of the human body bounding box is 40 millimeters and the area of the preview image is 200 millimeters, the area percentage of the human body bounding box in the preview image is 20%.”); and
focusing and cropping: when the human body coverage is covered within the cropping area in the initial image, the cropping area is selected as a cropped image (Wu, page 18, para. 9: “For example, after obtaining the percentage of the area of the human body bounding box in the preview image, the electronic device can also crop the human body image from the preview image based on the human body bounding box”).
Wu fails to teach
calculating a cropping range: identifying a second upper boundary coordinate and a second lower boundary coordinate in the original size according to a cropping ratio corresponding to the human body area ratio to define a cropping area.
Chen teaches
calculating a cropping range: identifying a second upper boundary coordinate and a second lower boundary coordinate in the original size according to a cropping ratio corresponding to the human body area ratio to define a cropping area (Chen, para. [0102]-[0120]; FIG. 6; FIG. 8A: “In a first manner, referring to FIG. 6, the cropping box 81 for cropping the original video frame may be determined in the following manner. S600. Determine a width δW of the target object by using the coordinate box 50. For example, referring to FIG. 5C and FIG. 5D, the width δW of the target object may be obtained by subtracting Xmin from Xmax. S610. Obtain a width Width of the original image frame. S620. Determine, based on the width δW of the target object and the width Width of the original image frame, a cropping width for cropping the original image frame. In one implementation process, the cropping width may be determined by using a ratio of the width δW of the target object to the width Width of the image. For example, referring to FIG. 7, when δW/Width is less than or equal to a first preset ratio, the cropping width is the first preset ratio multiplied by the width of the original image frame. When SW/Width is greater than the first preset ratio and less than or equal to a second preset ratio, the cropping width is the width δW of the target object. When δW/Width is greater than the second preset ratio, the cropping width is Width … S630. Determine a left cropping side 81 a and a right cropping side 81 b by using the cropping width. For example, it is assumed that the first preset ratio is 0.5 and the second preset ratio is 0.8. In this case, when δW is less than or equal to 0.5, the cropping width is 0.5 times the width of the original image frame. When δW is greater than 0.5 and less than or equal to 0.8, the cropping width is W. When δW is greater than 0.8, the cropping width is the width of the original image frame.;
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For example, it is assumed that the original image frame is shown in FIG. 8A. In FIG. 8A, 80 represents an outer box border of the original video frame, 50 represents the coordinate box of the target object, and the coordinate box 50 includes a left box border 50 a, a right box border 50 b, an upper box border 50 c, and a lower box border 50 d. Because SW/Width is less than 0.5, it is determined that the cropping width is 0.5 times the width Width of the original video frame … After the center point [human object coordinate box] is determined, the center point is extended leftwards by a first preset width W1, and a straight line perpendicular to the X-axis direction is made to determine the left cropping side 81 a. The center point is extended rightwards by a second preset width W2, and a straight line perpendicular to the X-axis direction is made to obtain the right cropping side 81 b. A sum of the first preset width W1 and the second preset width W2 is the cropping width, for example, the sum of the first preset width W1 and the second preset width W2 is 0.5 multiplied by Width. The first preset width W1 may be equal to the second preset width W2, and both the first preset width W1 and the second preset width W2 are ½ of the cropping width, for example, ¼*Width. The first preset width W1 may be unequal to the second preset width W2. This is not limited in this embodiment of the present disclosure ...S640. Determine an upper cropping side 81 c and a lower cropping side 81 d based on a vertical coordinate of the target object in the coordinate box 50. For example, the upper box border 50 c may be used as the upper cropping side 81 c after being moved upwards by a first preset height H1 (in one implementation process, the upper box border 50 c may be directly used as the upper cropping side 81 c). The upper cropping side 81 c is used as the lower cropping side 81 d after being extended downwards by a second preset height H2. For example, the first preset height H1 is 0.05 times or 0.01 times (or which certainly may be another value) a height of the original image frame, and the second preset height H2 is 0.5 times or 0.6 times (or which certainly may be another value) the height of the original image frame, (as shown in FIG. 8A to FIG. 8C … In one implementation process, a cropping height may be determined based on a proportion of the width of the original video frame that is occupied by the cropping width, and the upper cropping side 81 c and the lower cropping side 81 d are determined based on the cropping height … S650. Determine the cropping box 81 based on the upper cropping side 81 c, the lower cropping side 81 d, the left cropping side 81 a, and the right cropping side 81 b. It may be learned from FIG. 8A to FIG. 8C that a size of the finally determined cropping box 81 varies based on different widths δW of the target object, so that a picture of an output video frame may also occupy different sizes of a picture of the original video frame.”;
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the corner coordinates of the cropping box 81 may be seen in FIG. 8A that are found from the cropping height and width).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the method, as taught by Wu, to include the step of calculating a cropping range by identifying a second upper boundary coordinate and a second lower boundary coordinate in the original size according to a cropping ratio corresponding to the human body area ratio to define a cropping area, as taught by Chen.
The suggestion/motivation for doing so would have been that “by using the foregoing solution, it can be ensured that the target object is tracked by using the target object as a center in a video collection process.” (Chen, para. [0125]).
Wu, in view of Chen, fails to teach
defining a second focal coordinate of a center point of the cropping area; and coinciding the first focal coordinate and the second focal coordinate.
Yi teaches
defining a second focal coordinate of a center point of the cropping area; and coinciding the first focal coordinate and the second focal coordinate (Yi, page 3, para. 11; page 4, para. 1: “Accordingly, the processor 120 may generate each enlarged cropped image based on the size of each enlargement box. In this case, the processor 120 may generate the enlarged cropped image so that the center point of the enlarged box coincides with the center point of the bounding box.”).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to 1) modify the step of calculating a cropping range, as taught Wu, in view of Chen, to include defining a second focal coordinate of a center point of the cropping area, as taught by Yi, and 2) modify the step of focusing and cropping, as taught by Wu, in view of Chen, to include coinciding the first focal coordinate and the second focal coordinate, as taught by Yi.
The suggestion/motivation for doing so would have been to that aligning the object's bounding box center coordinate with the cropping bounding box center coordinate before cropping ensures the object of interest remains in focus and is fully visible within the new image; this prevents inadvertently cutting off important parts of the object, which is crucial for accurate image analysis.
Therefore, it would have been obvious to combine Wu and Chen, with Yi, to obtain the invention as specified in claim 1.
Regarding claim 3, Wu, in view of Chen, and in view of Yi, teaches the image cropping processing method according to claim 1, wherein the human body area ratio is proportional to the cropping ratio (Chen, para. [0102]-[0120]; FIG. 6; FIG. 8A; see rejection of claim 1; the ratio of the width of the coordinate box (human body bounding box) to the original image width (δW/Width) (i.e. the human body area ratio) is compared to different preset ratios to determine how the cropping width is calculated; the preset ratios are, for example, P1 = 0.3 (30%) and P2 = 0.6 (60%) or P1 = 0.5 (50%) and P2 = 0.8 (80%); if δW/Width is less than or equal to P1, then the cropping width is Width*P1; if δW/Width is greater than or equal P1 and less than P2, then the cropping width is δW (human body bounding box width); if δW/Width is greater than or equal to P2, then the cropping width is Width (width of the original image); the human body area ratio (δW/Width) is proportional to the preset ratios (cropping ratio)).
Regarding claim 4, Wu, in view of Chen, and in view of Yi, teaches the image cropping processing method according to claim 3, wherein an upper limiting value and a lower limiting value corresponding to the human body area ratio are set, and the cropping ratio is correspondingly scaled according to an interval size of the upper limiting value and the lower limiting value (Chen, para. [0102]-[0120]; FIG. 6; FIG. 8A; see rejection of claim 3 above; the lower limiting value of the human body area ratio is when δW/Width (human body area ratio) is less than or equal to the first preset ratio P1 (ex: P1 = 30%) so regardless of how low the human body area ratio goes in terms of percentage of the entire image (29% all the way down to 1% of the image), the cropping ratio is only scaled down by multiplying P1 by the width of the original image (in example given, the cropping width will always be 30% of the width of the original image); the upper limiting value of the human body area ratio is when δW/Width (human body area ratio) is greater than or equal to the second preset ratio (ex: P2 = 60%) so regardless of how high the human body area ratio goes in terms of percentage of the entire image (61% all the way up to 100% of the image), the cropping width will be limited to the width of the entire image; therefore the cropping width is scaled by the preset ratios accordingly to the upper and lower limit conditions put on the human body area ratio).
Regarding claim 8, Wu teaches an image cropping processing method, executed by an electronic device reading an executable code, when there are two or more human bodies identified in an initial image by artificial intelligence, cropping processing to the initial image is executed, comprising the following steps: (Wu, page 7, para. 7-9; page 8, para. 1; page 22, para. 9: “In the embodiment of the present application, the electronic device may obtain an image sample containing the human body in advance to train a deep learning model such as a convolutional neural network to obtain a trained model. The trained model can be used as the portrait detection in the embodiment of the present application. For example, after obtaining the preview image, the electronic device may use a pre-trained scene recognition model to perform scene recognition on the preview image to confirm whether there is a single human body in the preview image. When there is a single human body in the preview image, the electronic device can use a pre-trained portrait detection model to perform portrait detection on the preview image to obtain a human body bounding box. When there is no human body or multiple human bodies in the preview image, the electronic device can directly end the process. In some embodiments, the electronic device may use a pre-trained target detection model to perform target detection on the preview image to obtain a bounding box of the human body. It should be noted that the target detection model only detects the human body in the preview image, and does not detect other objects.”; “For example, after obtaining the percentage of the area of the human body bounding box in the preview image, the electronic device can also crop the human body image from the preview image");
calculating a human body area ratio: identifying a first upper boundary coordinate and a first lower boundary coordinate of the human body in the initial image, the upper boundary coordinate and the lower boundary coordinate are used to define a human body coverage area for covering the human body (Wu, page 8, para. 1-5: “In 203, the electronic device determines the width and height of the bounding box of the human body. In 204, the electronic device calculates the ratio of width to height. For example, after obtaining the human body bounding box, the electronic device can obtain the upper left corner coordinates and the lower right corner coordinates of the human body bounding box, and determine the width and height of the human body bounding box by the upper left corner coordinates of the human body bounding box and the upper right corner coordinates of the human body bounding box, and calculate the ratio of the width of the human body bounding box to the height of the human body bounding box. Among them, the coordinates of the upper left corner can be expressed as (x1, y1), and the coordinates of the lower right corner can be expressed as (x2, y2), then the width of the human body bounding box=|x2-x1|, the height of the human body bounding box=|y2-y1|, x1 and y1 are the abscissa and ordinate of the upper left corner of the human body bounding box in the screen coordinate system; x2 and y2 are the abscissa and ordinate of the lower right corner of the human body bounding box in the screen coordinate system, respectively. For example, assuming that the coordinates of the upper left corner of the human body bounding box are (10, 40) and the coordinates of the lower right corner of the human body bounding box are (70, 60), the width of the human body bounding box is 60, the height of the human body bounding box is 20, and the body boundary the ratio of the width of the box to the height of the bounding box of the human body is 4.”), and
defining a first focal coordinate of a center point of the human body coverage area (Wu, page 18, para. 2: “If there are no preset key points in the human body key point set, the electronic device can obtain the center coordinates of the human body boundary box”), in order to calculate a human body area ratio of the human body coverage area occupying an original size of the initial image (Wu, “For example, after obtaining the ratio of the width of the human body boundary box to the height of the human body boundary box, the electronic device may also determine the area percentage of the human body boundary box in the preview image. For example, if the area of the human body bounding box is 40 millimeters and the area of the preview image is 200 millimeters, the area percentage of the human body bounding box in the preview image is 20%.”); and
focusing and cropping: when the human body coverage is covered within the cropping area in the initial image, the cropping area is selected as a cropped image (Wu, page 18, para. 9: “For example, after obtaining the percentage of the area of the human body bounding box in the preview image, the electronic device can also crop the human body image from the preview image based on the human body bounding box”).
Wu fails to teach
calculating a human body area ratio: identifying a first upper boundary coordinate and a first lower boundary coordinate of each the human body in the initial image, and taking a maximum longitudinal ordinate value and a minimum horizontal ordinate value to define a maximum upper boundary coordinate, and taking a minimum longitudinal ordinate value and a maximum horizontal ordinate value to define a maximum lower boundary coordinate, the maximum upper boundary coordinate and the maximum lower boundary coordinate are used to define a human body coverage area for covering all the human bodies; and calculating a cropping range: identifying a second upper boundary coordinate and a second lower boundary coordinate in the original size according to a cropping ratio corresponding to the human body area ratio to define a cropping area.
Chen teaches
calculating a human body area ratio: identifying a first upper boundary coordinate and a first lower boundary coordinate of each the human body in the initial image, and taking a maximum longitudinal ordinate value and a minimum horizontal ordinate value to define a maximum upper boundary coordinate, and taking a minimum longitudinal ordinate value and a maximum horizontal ordinate value to define a maximum lower boundary coordinate, the maximum upper boundary coordinate and the maximum lower boundary coordinate are used to define a human body coverage area for covering all the human bodies (Chen, para. [0099]: “In one implementation process, the output second video frame may be obtained by cropping an original video frame. For example, the target object is a person. A coordinate box 50 of a human body may be first determined by using a human body detection model, and then a cropping box 81 for cropping the video frame is determined by using the coordinate box 50. The coordinate box 50 may be represented by coordinates of each point in the coordinate box 50, may be represented by coordinates in an upper left corner plus coordinates in a lower right corner, may be represented by coordinates in a lower left corner plus coordinates in an upper right corner, and so on. FIG. 5C is a schematic diagram of a determined coordinate box 50 when there is one target object, and FIG. 5D is a schematic diagram of a determined coordinate box 50 when the target object is two persons (a case of a plurality of persons is similar to this). Coordinate boxes 50 of all persons in the original video frame may be first determined based on a human body detection technology, and then the coordinate boxes 50 of all the persons are combined to obtain the coordinate box 50 of the target object. In FIG. 5D, the coordinate box 50 is represented by coordinates (Xmin, Ymin) in an upper left corner and coordinates (Xmax, Ymax) in a lower right corner. Xmin represents a minimum value on an X-axis, Ymin represents a minimum value on a Y-axis, Xmax represents a maximum value on the X-axis, Ymax represents a maximum value on the Y-axis, and an upper left corner of the video frame is an origin.”;
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calculating a cropping range: identifying a second upper boundary coordinate and a second lower boundary coordinate in the original size according to a cropping ratio corresponding to the human body area ratio to define a cropping area (Chen, para. [0102]-[0120]; FIG. 6; FIG. 8A: “In a first manner, referring to FIG. 6, the cropping box 81 for cropping the original video frame may be determined in the following manner. S600. Determine a width δW of the target object by using the coordinate box 50. For example, referring to FIG. 5C and FIG. 5D, the width δW of the target object may be obtained by subtracting Xmin from Xmax. S610. Obtain a width Width of the original image frame. S620. Determine, based on the width δW of the target object and the width Width of the original image frame, a cropping width for cropping the original image frame. In one implementation process, the cropping width may be determined by using a ratio of the width δW of the target object to the width Width of the image. For example, referring to FIG. 7, when δW/Width is less than or equal to a first preset ratio, the cropping width is the first preset ratio multiplied by the width of the original image frame. When SW/Width is greater than the first preset ratio and less than or equal to a second preset ratio, the cropping width is the width δW of the target object. When δW/Width is greater than the second preset ratio, the cropping width is Width … S630. Determine a left cropping side 81 a and a right cropping side 81 b by using the cropping width. For example, it is assumed that the first preset ratio is 0.5 and the second preset ratio is 0.8. In this case, when δW is less than or equal to 0.5, the cropping width is 0.5 times the width of the original image frame. When δW is greater than 0.5 and less than or equal to 0.8, the cropping width is W. When δW is greater than 0.8, the cropping width is the width of the original image frame.;
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For example, it is assumed that the original image frame is shown in FIG. 8A. In FIG. 8A, 80 represents an outer box border of the original video frame, 50 represents the coordinate box of the target object, and the coordinate box 50 includes a left box border 50 a, a right box border 50 b, an upper box border 50 c, and a lower box border 50 d. Because SW/Width is less than 0.5, it is determined that the cropping width is 0.5 times the width Width of the original video frame … After the center point [human object coordinate box] is determined, the center point is extended leftwards by a first preset width W1, and a straight line perpendicular to the X-axis direction is made to determine the left cropping side 81 a. The center point is extended rightwards by a second preset width W2, and a straight line perpendicular to the X-axis direction is made to obtain the right cropping side 81 b. A sum of the first preset width W1 and the second preset width W2 is the cropping width, for example, the sum of the first preset width W1 and the second preset width W2 is 0.5 multiplied by Width. The first preset width W1 may be equal to the second preset width W2, and both the first preset width W1 and the second preset width W2 are ½ of the cropping width, for example, ¼*Width. The first preset width W1 may be unequal to the second preset width W2. This is not limited in this embodiment of the present disclosure ...S640. Determine an upper cropping side 81 c and a lower cropping side 81 d based on a vertical coordinate of the target object in the coordinate box 50. For example, the upper box border 50 c may be used as the upper cropping side 81 c after being moved upwards by a first preset height H1 (in one implementation process, the upper box border 50 c may be directly used as the upper cropping side 81 c). The upper cropping side 81 c is used as the lower cropping side 81 d after being extended downwards by a second preset height H2. For example, the first preset height H1 is 0.05 times or 0.01 times (or which certainly may be another value) a height of the original image frame, and the second preset height H2 is 0.5 times or 0.6 times (or which certainly may be another value) the height of the original image frame, (as shown in FIG. 8A to FIG. 8C … In one implementation process, a cropping height may be determined based on a proportion of the width of the original video frame that is occupied by the cropping width, and the upper cropping side 81 c and the lower cropping side 81 d are determined based on the cropping height … S650. Determine the cropping box 81 based on the upper cropping side 81 c, the lower cropping side 81 d, the left cropping side 81 a, and the right cropping side 81 b. It may be learned from FIG. 8A to FIG. 8C that a size of the finally determined cropping box 81 varies based on different widths δW of the target object, so that a picture of an output video frame may also occupy different sizes of a picture of the original video frame.”;
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the corner coordinates of the cropping box 81 may be seen in FIG. 8A that are found from the cropping height and width).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify 1) the step of calculating a human body area ratio by identifying a first upper boundary coordinate and a first lower boundary coordinate of the human body in the initial image, the upper boundary coordinate and the lower boundary coordinate are used to define a human body coverage area for covering the human body, as taught by Wu, to include identifying a first upper boundary coordinate and a first lower boundary coordinate of each the human body in the initial image, and taking a maximum longitudinal ordinate value and a minimum horizontal ordinate value to define a maximum upper boundary coordinate, and taking a minimum longitudinal ordinate value and a maximum horizontal ordinate value to define a maximum lower boundary coordinate, the maximum upper boundary coordinate and the maximum lower boundary coordinate are used to define a human body coverage area for covering all the human bodies, as taught by Chen, and 2) the method, as taught by Wu, to include the step of calculating a cropping range by identifying a second upper boundary coordinate and a second lower boundary coordinate in the original size according to a cropping ratio corresponding to the human body area ratio to define a cropping area, as taught by Chen.
The suggestion/motivation for doing so would have been that “by using the foregoing solution, it can be ensured that the target object is tracked by using the target object as a center in a video collection process.” (Chen, para. [0125]); further suggestion/motivation for doing so would have been that combining the bounding boxes of multiple detected people into a single, larger bounding box before cropping the image offers several benefits, primarily centered on preserving the contextual relationships and ensuring that the entire group remains the focus of the subsequent analysis or display; cropping based on a combined box ensures that all individuals within the group shot are included in the final image, maintaining their spatial relationship and the overall scene context; this is vital for applications where the interaction between people is important, such as in social media photo tagging, surveillance analysis, or crowd behavior studies.
Wu, in view of Chen, fails to teach
defining a second focal coordinate of a center point of the cropping area; and coinciding the first focal coordinate and the second focal coordinate.
Yi teaches
defining a second focal coordinate of a center point of the cropping area; and coinciding the first focal coordinate and the second focal coordinate (Yi, page 3, para. 11; page 4, para. 1: “Accordingly, the processor 120 may generate each enlarged cropped image based on the size of each enlargement box. In this case, the processor 120 may generate the enlarged cropped image so that the center point of the enlarged box coincides with the center point of the bounding box.”).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to 1) modify the step of calculating a cropping range, as taught Wu, in view of Chen, to include defining a second focal coordinate of a center point of the cropping area, as taught by Yi, and 2) modify the step of focusing and cropping, as taught by Wu, in view of Chen, to include coinciding the first focal coordinate and the second focal coordinate, as taught by Yi.
The suggestion/motivation for doing so would have been to that aligning the object's bounding box center coordinate with the cropping bounding box center coordinate before cropping ensures the object of interest remains in focus and is fully visible within the new image; this prevents inadvertently cutting off important parts of the object, which is crucial for accurate image analysis.
Therefore, it would have been obvious to combine Wu and Chen, with Yi, to obtain the invention as specified in claim 8.
Regarding claim 10, Wu, in view of Chen, and in view of Yi, teaches the image cropping processing method according to claim 8, wherein the human body area ratio is proportional to the cropping ratio (Chen, para. [0102]-[0120]; FIG. 6; FIG. 8A; see rejection of claim 8; the ratio of the width of the coordinate box (human body bounding box) to the original image width (δW/Width) (i.e. the human body area ratio) is compared to different preset ratios to determine how the cropping width is calculated; the preset ratios are, for example, P1 = 0.3 (30%) and P2 = 0.6 (60%) or P1 = 0.5 (50%) and P2 = 0.8 (80%); if δW/Width is less than or equal to P1, then the cropping width is Width*P1; if δW/Width is greater than or equal P1 and less than P2, then the cropping width is δW (human body bounding box width); if δW/Width is greater than or equal to P2, then the cropping width is Width (width of the original image); the human body area ratio (δW/Width) is proportional to the preset ratios (cropping ratio)).
Regarding claim 11, Wu, in view of Chen, and in view of Yi, teaches the image cropping processing method according to claim 10, wherein an upper limiting value and a lower limiting value corresponding to the human body area ratio are set, and the cropping ratio is correspondingly scaled according to an interval size of the upper limiting value and the lower limiting value (Chen, para. [0102]-[0120]; FIG. 6; FIG. 8A; see rejection of claim 10 above; the lower limiting value of the human body area ratio is when δW/Width (human body area ratio) is less than or equal to the first preset ratio P1 (ex: P1 = 30%) so regardless of how low the human body area ratio goes in terms of percentage of the entire image (29% all the way down to 1% of the image), the cropping ratio is only scaled down by multiplying P1 by the width of the original image (in example given, the cropping width will always be 30% of the width of the original image); the upper limiting value of the human body area ratio is when δW/Width (human body area ratio) is greater than or equal to the second preset ratio (ex: P2 = 60%) so regardless of how high the human body area ratio goes in terms of percentage of the entire image (61% all the way up to 100% of the image), the cropping width will be limited to the width of the entire image; therefore, the cropping width is scaled by the preset ratios accordingly to the upper and lower limit conditions put on the human body area ratio).
Regarding claim 15, Wu teaches an electronic device of image cropping processing, provided to connect to a database for communication, the electronic device receives an initial image and identifies a human body by artificial intelligence, and is used to execute cropping processing to the initial image, in order to complete a cropped image and transmit it to the database, the electronic device comprises: (Wu, page 26, para. 3; page 13, para. 4; page 22, para. 9: “The electronic device 500 may include a camera module 501, a memory 502, a processor 503 and other components.”; “The electronic device can find multiple candidate key point sets and multiple composition bounding boxes mapped in the composition database through this key, and use multiple candidate key point sets and multiple composition bounding boxes as the multiple corresponding to the background image. A set of candidate keypoints and multiple composition bounding boxes.”; “For example, after obtaining the percentage of the area of the human body bounding box in the preview image, the electronic device can also crop the human body image from the preview image").
With regards to the remaining limitations of claim 15, they recite functions of the process of claim 1, as an apparatus. Thus, the analysis in rejecting claim 1 is equally applicable to the remaining limitations of claim 15.
Regarding claim 16, Wu teaches a non-transitory computer-readable recording medium, storing a plurality of executable codes, after an electronic device reads the executable codes and executes (Wu, page 25, para. 9; page 26, para. 3; page 22, para. 9: “The embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed on a computer, the computer is caused to execute the process in the prompt method provided in this embodiment.”; “For example, after obtaining the percentage of the area of the human body bounding box in the preview image, the electronic device can also crop the human body image from the preview image").
With regards to the remaining limitations of claim 16, they recite the functions of the process of claim 1, as a non-transitory computer-readable recording medium storing instructions. Thus, the analysis in rejecting claim 1 is equally applicable to the remaining limitations of claim 16.
Regarding claim 17, Wu teaches a non-transitory computer-readable recording medium, storing a plurality of executable codes, after an electronic device reads the executable codes and executes (Wu, page 25, para. 9; page 26, para. 3; page 22, para. 9: “The embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed on a computer, the computer is caused to execute the process in the prompt method provided in this embodiment.”; “For example, after obtaining the percentage of the area of the human body bounding box in the preview image, the electronic device can also crop the human body image from the preview image").
With regards to the remaining limitations of claim 17, they recite the functions of the process of claim 8, as a non-transitory computer-readable recording medium storing instructions. Thus, the analysis in rejecting claim 8 is equally applicable to the remaining limitations of claim 17.
Claim 2, 6, 9, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Wu, in view of Chen, in in view of Yi, and in further view of U.S. Patent Application Publication No.: 2017/0200279 (Zhong et al.) (hereinafter Zhong).
Regarding claim 2, Wu, in view of Chen, and in view of Yi, teaches the image cropping processing method according to claim 1.
Wu, in view of Chen, and in view of Yi, fails to teach
wherein the step of calculating the human body area ratio comprises setting an expansion value to shift the first upper boundary coordinate and the first lower boundary coordinate, so that the human body coverage area is expanded in equal proportion by the setting of the expansion value.
Zhong teaches
wherein the step of calculating the human body area ratio comprises setting an expansion value to shift the first upper boundary coordinate and the first lower boundary coordinate, so that the human body coverage area is expanded in equal proportion by the setting of the expansion value (Zhong, para. [0033]: “Based on the object bounding box 204 that is output by the object tracker 122, individual video frames 202 may be cropped by performing frame cropping 206 to generate a cropped image 208. In some cases, the frame cropping 206 may include determining a portion of a particular video frame of the video frames 202 that is associated with the object bounding box 204 and increasing a size of the object bounding box 204 to generate an expanded object bounding box 210. In some cases, the frame cropping 206 may include receiving X,Y coordinates of corners of the object bounding box 204, a height/width/diagonal size of the object bounding box 204, etc. The expanded object bounding box 210 may capture not only pixels associated with a foreground portion 212 of the particular video frame but also additional pixels associated with a background portion 214 of the particular video frame. As an illustrative, non-limiting example, the frame cropping 206 may include increasing the size of the object bounding box 204 by 30% in both the X direction and the Y direction from a center point and generating the cropped image 208 by determining pixels of the particular video frame that are within the expanded object bounding box 210.;
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It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the step of calculating the human body area ratio, as taught by Wu, in view of Chen, and in view of Yi, to include setting an expansion value to shift the first upper boundary coordinate and the first lower boundary coordinate, so that the human body coverage area is expanded in equal proportion by the setting of the expansion value, as taught by Zhong.
The suggestion/motivation for doing so would have been that “the expanded object bounding box 210 may include additional pixels associated with a person's neck that may be useful for growing a mask for object tracking purposes” (Zhong, para. [0033]).
Therefore, it would have been obvious to combine Wu, Chen, and Yi, with Zhong, to obtain the invention as specified in claim 2.
Regarding claim 6, Wu, in view of Chen, in view of Yi, teaches the image cropping processing method according to claim 1.
Wu, in view of Chen, in view of Yi, fails to teach
if the human body coverage area exceeds the cropping area in a longitudinal direction or horizontal direction, the cropping area is expanded to the boundary that the human body coverage area exceeds in the longitudinal direction or horizontal direction, so as to meet the condition that the human body coverage area is covered within the cropping area.
Zhong teaches
if the human body coverage area exceeds the cropping area in a longitudinal direction or horizontal direction, the cropping area is expanded to the boundary that the human body coverage area exceeds in the longitudinal direction or horizontal direction, so as to meet the condition that the human body coverage area is covered within the cropping area (Zhong, para. [0033]: “Based on the object bounding box 204 that is output by the object tracker 122, individual video frames 202 may be cropped by performing frame cropping 206 to generate a cropped image 208. In some cases, the frame cropping 206 may include determining a portion of a particular video frame of the video frames 202 that is associated with the object bounding box 204 and increasing a size of the object bounding box 204 to generate an expanded object bounding box 210. In some cases, the frame cropping 206 may include receiving X,Y coordinates of corners of the object bounding box 204, a height/width/diagonal size of the object bounding box 204, etc. The expanded object bounding box 210 may capture not only pixels associated with a foreground portion 212 of the particular video frame but also additional pixels associated with a background portion 214 of the particular video frame. As an illustrative, non-limiting example, the frame cropping 206 may include increasing the size of the object bounding box 204 by 30% in both the X direction and the Y direction from a center point and generating the cropped image 208 by determining pixels of the particular video frame that are within the expanded object bounding box 210.;
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It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the step of focusing and cropping, as taught by Wu, in view of Chen, in view of Yi, to include expanding the cropping area to the boundary that the human body coverage area exceeds in the longitudinal direction or horizontal direction, if the human body coverage area exceeds the cropping area in a longitudinal direction or horizontal direction, so as to meet the condition that the human body coverage area is covered within the cropping area, as taught by Zhong.
The suggestion/motivation for doing so would have been to ensure the object of interest remains in focus and is fully visible within the new image; this prevents inadvertently cutting off important parts of the object, which is crucial for accurate image analysis.
Wu, in view of Chen, in view of Yi, and in view of Zhong, teaches wherein in the step of focusing and cropping, when the first focal coordinate and the second focal coordinate coincide, if the human body coverage area exceeds the cropping area in a longitudinal direction or horizontal direction, the cropping area is expanded to the boundary that the human body coverage area exceeds in the longitudinal direction or horizontal direction, so as to meet the condition that the human body coverage area is covered within the cropping area (Zhong, para. [0033]; Yi, page 3, para. 11; page 4, para. 1; after Yi coincides the cropping box with the bounding box around the human body via aligning the center coordinates, then when combined with Zhong, Zhong checks to see if the alignment of the boxes cut off some of the human body in the image and expands the boundary of the cropping zone as necessary to encompass the human face; this concept from Zhong is then applied to the full human body coverage taught by in Wu and Chen).
Therefore, it would have been obvious to combine Wu, Chen, and Yi, with Zhong, to obtain the invention as specified in claim 6.
With regards to dependent claims 9 and 13, they recite the process of claims 2 and 6, respectively, as apparatuses. Thus, the analysis in rejecting claims 2 and 6 are equally applicable to claims 9 and 13, respectively.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Wu, in view of Chen, in in view of Yi, in view of Zhong, and in further view of U.S. Patent Publication No.: 8,498,453 (Benson et al.) (hereinafter Benson).
Regarding claim 7, Wu, in view of Chen, in view of Yi, and in view of Zhong, teaches the image cropping processing method according to claim 6.
Wu, in view of Chen, in view of Yi, and in view of Zhong, fails to teach
wherein in the step of focusing and cropping, if the cropping area exceeds a longitudinal boundary and/or horizontal boundary of the original size, the cropping area shifts back according to the exceeded longitudinal boundary and/or horizontal boundary.
Benson teaches
wherein in the step of focusing and cropping, if the cropping area exceeds a longitudinal boundary and/or horizontal boundary of the original size, the cropping area shifts back according to the exceeded longitudinal boundary and/or horizontal boundary (Benson, col. 36, lines 19-27: “Further, when an original image is rotated for cropping, processing is performed in some embodiments to confirm that no portion of the cropped image extends beyond the boundaries of the rotated original image, or alternatively, extends outside of the active area of the rotated original image. If it is determined that any portion exceeds the active area or a boundary of the rotated original image, the cropping locations are adjusted to be within the active area or boundaries of the original image and to maintain the desired aspect ratio.”).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the step of focusing and cropping, as taught by Wu, in view of Chen, in view of Yi, and in view of Zhong, to include shifting the cropping area back according to a exceeded longitudinal boundary and/or a horizontal boundary, if the cropping area exceeds the longitudinal boundary and/or horizontal boundary of the original size, as taught by Benson.
The suggestion/motivation for doing so would have been to that cropping an image to a size larger than the original is technically impossible without creating new, fake pixels, which results in significant quality loss; it causes pixelation, blurring, and loss of detail because the software must stretch the existing pixels to fill the new space which defeats the purpose of cropping; therefore, correcting this issue improves image quality.
Wu, in view of Chen, in view of Yi, in view of Zhong, and in view of Benson teaches wherein in the step of focusing and cropping, when the first focal coordinate and the second focal coordinate coincide, if the cropping area exceeds a longitudinal boundary and/or horizontal boundary of the original size, the cropping area shifts back according to the exceeded longitudinal boundary and/or horizontal boundary (Yi, page 3, para. 11; page 4, para. 1; Benson, col. 36, lines 19-27; after Yi coincides the center points of the human body bounding box (Wu and Chen), with the cropping box, so the human bodies are fully encompassed in the cropping box, then Benson checks to see if the cropping box is determined to be larger than the original image’s horizontal and longitudinal boundaries; if it is, then the cropping box is adjusted to fit the object and be within the boundaries of the original image so there is not an error).
Therefore, it would have been obvious to combine Wu, Chen, Yi, and Zhong, with Benson, to obtain the invention as specified in claim 7.
With regards to dependent claim 14, it recites the functions of process of claim 7, as an apparatus. Thus, the analysis in rejecting claim 7 is equally applicable to claim 14.
Conclusion
Dependent claims 5 and 12 are rejected under 35 U.S.C. 101 but are not rejected under 35 U.S.C. 102 or 103 prior art.
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/MICHAEL ADAM SHARIFF/
Examiner, Art Unit 2672
/SUMATI LEFKOWITZ/Supervisory Patent Examiner, Art Unit 2672
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