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 .
Election/Restrictions
Applicant’s election without traverse of Group I (claims 1-9, 13-16, and 19-20) in the reply filed on 03/02/2026 is acknowledged.
Claims 10-12 and 17-18 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected groups, there being no allowable generic or linking claim.
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.
Claim(s) 1-9, 13-16, and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). The claim(s) recite(s) a method, a system, and a CRM for selecting a part of a specific type in an image based on estimated distance between the part and another part. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory) .
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1 and 19-20 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories?
YES .
Claim(s) 1, and 19-20 are directed to a system, a method, and a CRM, respectively.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
YES.
The claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The claims comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding Claim(s) 1, 19, and 20: the claims recite the steps (functions) of:
perform first position estimation of detecting one or more parts of a first type in an image (mental process including observation and evaluation, and can be done mentally in the human mind);
estimate a distance between each of the one or more parts of the first type and a part of a second type in the image(mental process including observation and evaluation, and can be done mentally in the human mind);
select, from among the one or more parts of the first type detected, one part of the first type, based on the distance estimated for each of the parts of the first type (mental process including observation and evaluation, and can be done mentally in the human mind).
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As such, a person could look at ad a facial image, determine eyes position, and estimate the distance the nose, and select one of the two eyes based on the distance to the nose either mentally or using a pen and paper. The mere nominal recitation that the various steps are being executed by a device/in a device (e.g. processing unit) does not take the limitations out of the mental process grouping. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO.
The claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, and 19-20 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Claim(s) 1 recite(s) the further limitations of:
one or more memories storing instructions and one or more processors that execute the instructions (generic computers or components configured to perform the method);
output information indicating the part selected (insignificant post-solution extra activity of generating an output).
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
NO.
The claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claim(s) 1, and 19-20 do not recite any additional elements that are not well-understood, routine or conventional. The use of a computer to perform, estimate, select, and output as claimed in Claim(s) 1, and 19-20 is a routine, well-understood and conventional process that is performed by computers.
Regarding claim 2-9, and 13-16: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The additional limitation(s) of the dependent claims fall under: (mental process including observation and evaluation, and can be done mentally in the human mind) OR (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations) OR (insignificant pre/post-solution extra activity of gathering/generating data) OR (generic computers or components configured to perform the method).
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.
Claim(s)1, 3-5, 8-9, 13-16, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kunishige et al. (US 20140104483), hereinafter “Kun”, in view of Zambrano at al. (US 20210056701), hereinafter “Zamb”.
Regarding claims 1 (apparatus), 19 (method), and 20 (CRM):
Kun discloses: (claim 1) an image processing apparatus comprising one or more memories storing instructions and one or more processors (FIG. 1,¶ [0033] “…The memory 110 is connected to an image processing section 111 and a system control section 116.”)) that execute the instructions to:
perform first position estimation of detecting one or more parts of a first type in an image (¶ [0042] “…The image processing section 111 also acts as a facial organ detection section, and performs detection of organs within a face such as eyes, nose and mouth, corners of the mouth, and pupils. Here, in the case where organs such as eyes and pupils are detected, the position and size of the respective left and right eyes are also detected, and inclination of the face is also detected based on the position etc. of these organs.”);
While Kun discloses relevant facial parts in ¶ [0071] “…The image processing section 111 detects node points such as eyes, mouth, nose, chin, forehead, eyebrows, brow, etc. by facial organ detection, as shown in FIG. 7, forms a wireframe by connecting these points, as shown in FIG. 6A and FIG. 6B, and calculates an angle for the direction in which the face is facing based on this wireframe”;
Kun does not expressly teach: estimate a distance between each of the one or more parts of the first type and a part of a second type in the image.
However, in the same field of endeavor, Zamb teaches: estimate a distance between each of the one or more parts of the first type and a part of a second type in the image (¶ [0030] “At 304, the computing device 202 determines a first distance between the first reference point and the third reference point and determines a second distance between the second reference point and the third reference point at 306.”; ¶ [0032] “…the first reference point, second reference point, and third reference point correspond to a left eye, right eye, and a nose, the first distance and the second distance are determined by Equations (3) and (4) below, respectively”);
select, from among the one or more parts of the first type detected, one part of the first type, based on the distance estimated for each of the parts of the first type (Kun ¶ [0047] “…the system control section 116 function as an eye priority AF section for setting an AF region to an eye that has been detected by the facial organ detection section, and focusing on the eye. Also, the eye priority AF section selects the nearer, namely the larger, of left and right eyes that have been detected by the facial organ detection section and focuses on the selected eye”; ¶ [0007] “…determines inclination of a face based on the detected facial organs, the eye priority AF section selects one eye based on the inclination of the face”; ¶ [0071] “…The image processing section 111 detects node points such as eyes, mouth, nose, chin, forehead, eyebrows, brow, etc. by facial organ detection, as shown in FIG. 7, forms a wireframe by connecting these points, as shown in FIG. 6A and FIG. 6B, and calculates an angle for the direction in which the face is facing based on this wireframe”; Zamb in ¶ [0034] “…At 308, the computing device 202 compares the determined first distance to the determined second distance to calculate a head orientation value for the subject.”
Kun teaches detecting facial organs, forming wireframe from node points corresponding to these organs, and calculating face-direction angle from that wireframe, and then selecting the eye corresponding to the nearer side of the face based on the determined inclination/turning of the face. Because inclination is derived from the spatial arrangement of the detected eye and nose node points in the image, the selected eye is indirectly selected based on relative distance/positions between detected eyes and nose. Zamb also supplies comparing the eye-nose distance for the left and right eye); and
output information indicating the part selected (Kun ¶ [0086] “…Also, with this embodiment, left and right eyes are respectively detected at the time of carrying out facial organ detection (S27), and the closer of the left and right eyes, namely the one that is largest, is selected (S29), an action to focus on the selected eye is carried out (S33)” An indication of the selected eye is output in order to perform (S33)).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Kun’s eye-priority AF selection to use Zamb’s comparison of the distances, because Kun already selects the eye corresponding to the nearer side of the face based on face inclination/turning, and Zamb teaches a known facial-geometry technique for calculating head orientation from those eye to nose distances. Using Zamb’s explicit distance comparison in Kun’ would have been a predicable substitution of one known orientation determination technique for another to provide more explicit basis for selecting the eye priority AF frame.
Regarding claim 3:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
perform second position estimation of detecting a part of a second type in the image (Kun teaches ¶ [0042] “…The image processing section 111 also acts as a facial organ detection section, and performs detection of organs within a face such as eyes, nose and mouth, corners of the mouth, and pupils. Here, in the case where organs such as eyes and pupils are detected, the position and size of the respective left and right eyes are also detected, and inclination of the face is also detected based on the position etc. of these organs.”; ¶ [0069] “…the image processing section 111 detects facial organs, namely eyes, nose mouth, corners of the mouth etc., of a face of a person within a subject based on image data from the image sensor 107. Also, when eyes have been detected, the left and right eyes are respectively detected.” Zamb further reinforces in ¶ [0027] “The computing device 202 implementing the head orientation module 108 receives or derives the coordinates representing a set 212 of at least three reference points of a subject gazing on a plurality of user interface elements 214 at 302”; ¶ [0032] “…the first reference point, second reference point, and third reference point correspond to a left eye, right eye, and a nose”); and
determine a distance between each of the one or more parts of the first type detected from the image and the part of the second type detected from the image (Zamb in ¶ [0030] “At 304, the computing device 202 determines a first distance between the first reference point and the third reference point and determines a second distance between the second reference point and the third reference point at 306.”; ¶ [0032] “…the first reference point, second reference point, and third reference point correspond to a left eye, right eye, and a nose, the first distance and the second distance are determined by Equations (3) and (4) below, respectively”).
Regarding claim 4:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
wherein the distance estimated for the one part of the first type selected is longer than the distance estimated for another part among the one or more parts of the first type (Kun ¶ [0047] “…the system control section 116 function as an eye priority AF section for setting an AF region to an eye that has been detected by the facial organ detection section, and focusing on the eye. Also, the eye priority AF section selects the nearer, namely the larger, of left and right eyes that have been detected by the facial organ detection section and focuses on the selected eye”; ¶ [0007] “…determines inclination of a face based on the detected facial organs, the eye priority AF section selects one eye based on the inclination of the face”; ¶ [0071] “…The image processing section 111 detects node points such as eyes, mouth, nose, chin, forehead, eyebrows, brow, etc. by facial organ detection, as shown in FIG. 7, forms a wireframe by connecting these points, as shown in FIG. 6A and FIG. 6B, and calculates an angle for the direction in which the face is facing based on this wireframe”; Zamb in ¶ [0034] “…At 308, the computing device 202 compares the determined first distance to the determined second distance to calculate a head orientation value for the subject.”
Kun teaches detecting facial organs, forming wireframe from node points corresponding to these organs, and calculating face-direction angle from that wireframe, and then selecting the eye corresponding to the nearer side of the face based on the determined inclination/turning of the face. Because inclination is derived from the spatial arrangement of the detected eye and nose node points in the image, the selected eye is indirectly selected based on relative distance/positions between detected eyes and nose, and one distance is longer than the other. Zamb also supplies comparing the eye-nose distance for the left and right eye).
Regarding claim 5:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
detect two parts of the first type (Kun ¶ [0042] “…in the case where organs such as eyes and pupils are detected, the position and size of the respective left and right eyes are also detected, and inclination of the face is also detected based on the position etc. of these organs.”);
select a method for selecting one part among the two parts based on a difference in distances from each of the two parts to the part of the second type ( Kun ¶ [0047] “…the system control section 116 function as an eye priority AF section for setting an AF region to an eye that has been detected by the facial organ detection section, and focusing on the eye. Also, the eye priority AF section selects the nearer, namely the larger, of left and right eyes that have been detected by the facial organ detection section and focuses on the selected eye”; ¶ [0007] “…determines inclination of a face based on the detected facial organs, the eye priority AF section selects one eye based on the inclination of the face”; ¶ [0071] “…The image processing section 111 detects node points such as eyes, mouth, nose, chin, forehead, eyebrows, brow, etc. by facial organ detection, as shown in FIG. 7, forms a wireframe by connecting these points, as shown in FIG. 6A and FIG. 6B, and calculates an angle for the direction in which the face is facing based on this wireframe”; Zamb in ¶ [0034] “…At 308, the computing device 202 compares the determined first distance to the determined second distance to calculate a head orientation value for the subject.”
Kun teaches detecting facial organs, forming wireframe from node points corresponding to these organs, and calculating face-direction angle from that wireframe, and then selecting the eye corresponding to the nearer side of the face based on the determined inclination/turning of the face. Because inclination is derived from the spatial arrangement of the detected eye and nose node points in the image, the selected eye is indirectly selected based on relative distance/positions between detected eyes and nose, and one distance is longer than the other. Zamb also supplies comparing the eye-nose distance for the left and right eye).
Regarding claim 8:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
wherein the part of the second type is a part that is equidistant from the one or more parts of the first type (Kun in ¶ [0069] “…In this step the image processing section 111 detects facial organs, namely eyes, nose mouth, corners of the mouth etc. “;
Zamb in ¶ [0030] “At 304, the computing device 202 determines a first distance between the first reference point and the third reference point and determines a second distance between the second reference point and the third reference point at 306.”; ¶ [0032] “…the first reference point, second reference point, and third reference point correspond to a left eye, right eye, and a nose”; the nose has an equal distance to the left and right eyes).
Regarding claim 9:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
wherein the part of the second type is a nose, a mouth, a chin, a brow, or a head (Kun in ¶ [0069] “…In this step the image processing section 111 detects facial organs, namely eyes, nose mouth, corners of the mouth etc. “; Zamb in ¶ [0030] “At 304, the computing device 202 determines a first distance between the first reference point and the third reference point and determines a second distance between the second reference point and the third reference point at 306.”; ¶ [0032] “…the first reference point, second reference point, and third reference point correspond to a left eye, right eye, and a nose).
Regarding claim 13:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
wherein the part of the first type is an eye or an ear (Kun in ¶ [0042] “…The image processing section 111 also acts as a facial organ detection section, and performs detection of organs within a face such as eyes, nose and mouth, corners of the mouth, and pupils. Here, in the case where organs such as eyes and pupils are detected, the position and size of the respective left and right eyes are also detected, and inclination of the face is also detected based on the position etc. of these organs.”);
Regarding claim 14:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
detect a frame corresponding to a third part in the image (Kun in ¶ [0063] “If the result of the determination in step S3 is that it has been possible to carry out face detection, face frame display is next carried out (S5)”; ¶ [0067] “…the largest face priority AF frame is selected (S23). Here, the face having the largest size, from among faces that have been detected in the face detection of step S3, is selected, and a face priority AF frame is superimposed on this face in the subject image”; ¶ [0068] “…it is determined whether or not the largest face that was selected in step S23 is larger than a specified value “); and
detect the part of the first type from within the frame (¶ [0069] “If the result of determination in step S25 is that the size of the face is larger than the specified value, facial organ detection is carried out (S27). In this step the image processing section 111 detects facial organs, namely eyes, nose mouth, corners of the mouth etc., of a face of a person within a subject based on image data from the image sensor 107. Also, when eyes have been detected, the left and right eyes are respectively detected.”).
Regarding claim 15:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
wherein the third part is a face, a head, or a person ((Kun in ¶ [0063] “If the result of the determination in step S3 is that it has been possible to carry out face detection, face frame display is next carried out (S5)”; ¶ [0067] “…the largest face priority AF frame is selected (S23). Here, the face having the largest size, from among faces that have been detected in the face detection of step S3, is selected, and a face priority AF frame is superimposed on this face in the subject image”).
Regarding claim 16:
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
further comprising an image capture unit configured to capture the image (Kun in ¶ [0033] “FIG. 1 is a block diagram mainly showing the electrical structure of a camera 100”)
wherein the one or more processors execute the instructions to control the image capture unit so as to bring the one part of a first type that has been selected into focus (¶ [0047] “…the AF processing section 113 and the system control section 116 function as an eye priority AF section for setting an AF region to an eye that has been detected by the facial organ detection section, and focusing on the eye.”; ¶ [0070] “…The eye-priority AF frame is set so as to focus on the eye portion.”; ¶ [0075] “…When setting the eye-priority AF frame and focusing on the eye, the diaphragm 103 is set to its wide-open value”; ¶ [0076] “…The system control section 116 carries out focus adjustment control to move the photographing lens 101”).
Claim(s) 2 is rejected under 35 U.S.C. 103 as being unpatentable over Kunishige et al. (US 20140104483), hereinafter “Kun”, in view of Zambrano at al. (US 20210056701), hereinafter “Zamb” and Mayer (US 9846807).
Kun in view of Zamb teaches the limitations of claim 1 as applied above.
Kun in view of Zamb does not specifically teach: estimate the distance using a map indicating a distance to the part of the second type for each of the one or more parts of the first type in the image, the map being obtained using a trained model.
However, in the same field of endeavor, Mayer teaches: estimate the distance using a map (col 7, lines 64-68, col. 8, lines 1-12 “a neural network classifier can be trained to receive a patch (e.g., 16 pixels×16 pixels region of interest) from an eye image as input, and provide, as an output, distance values indicating how far from a corner location the patch is centered. For example, a patch centered on an eye corner may return a distance of zero… Use of trained neural networks for corner detection is achieved by (i) submitting multiple patches from an input sample to this configuration of neural network classifier, and (ii) constructing a map from the distance values that result.”; col. 4, lines 37-40 “…The subject 110 may, in general, by any physical and tangible object. an image of the subject 110 may include, for example, an image of a person, a person's face, or a person's eyes.”)
indicating a distance to the part of the second type for each of the one or more parts of the first type in the image, the map being obtained using a trained model (col. 7 lines 21-2, “Each neural network classifier may accept a ROI of the eye image as an input, and may provide at least one distance measure describing the displacement of the ROI from the eye corner location in the eye image. In some implementations, each neural network classifier may process multiple ROIs of an eye image.”; col 7, lines 64-68, col. 8, lines 1-12 “a neural network classifier can be trained to receive a patch (e.g., 16 pixels×16 pixels region of interest) from an eye image as input, and provide, as an output, distance values indicating how far from a corner location the patch is centered. For example, a patch centered on an eye corner may return a distance of zero… Use of trained neural networks for corner detection is achieved by (i) submitting multiple patches from an input sample to this configuration of neural network classifier, and (ii) constructing a map from the distance values that result.”; col. 4, lines 37-40 “…The subject 110 may, in general, by any physical and tangible object. an image of the subject 110 may include, for example, an image of a person, a person's face, or a person's eyes).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Kun’s eye-priority AF selection to and Zamb’s comparison of the distances to use Mayer’s trained neural network technique that outputs distance values and constructs a map from these values in the facial-part distance estimation framework. Mayor teaches a know way to obtain map-based distance information from a trained model for locating image parts.
Potential Allowable Subject Matter
Claims 6-7 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101 set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Relevant prior art not relied upon
Maes (US 20020135618) teaches determining distances from one eye to the nose differed from the distance form the other eye to the nose, and that this difference relates to the face turning/pose. ¶ [0078] “…on a picture of a slightly turned face, the distance between the right eye and the nose should be different from the distance between the left eye and the nose, and this difference should increase as the face turns. We can also try to estimate the facial orientation from inherent properties of a face.”
Kim (US 20160335495) teaches: measuring distances among left eye, right eye, and nose. ¶ [0034] “FIG. 2 is a view showing an illustration of the distance between the left eye and the right eye, which may be variously measured based on the positions of reference points”. ¶ [0066] “…the distance between the left eye and the right eye, the distance between the left eye and the nose, the distance between the left eye and the mouth, the distance between the right eye and the nose, the distance between the right eye and the mouth, or the distance between the nose and the mouth is used.”
Guan (US 20100253806) teaches: reference feature parameter T1 may be selected from the group consisting of a first ratio of a horizontal width of the left eye to a horizontal width of the right eye in the portrait image, a second ratio of a distance between the center of the pupil of the left eye and the nose tip to a distance between the center of the pupil of the right eye and the nose tip, and a third ratio of a distance between the two corners of the mouth to a distance between the two centers of the two nostril.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WASSIM MAHROUKA whose telephone number is (571)272-2945. The examiner can normally be reached Monday-Thursday 8:00-5:00 EST.
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/WASSIM MAHROUKA/Primary Examiner, Art Unit 2665
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