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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/01/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Rejections - 35 USC § 103
1 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.
2 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.
3 Claim(s) 1-9 and 11-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (US 20220012472 A1) in view of Hu et al. (US 20210209347 A1).
4 Regarding claim 1, Lee teaches a computer-implemented method comprising:
accessing a first image of a client device, wherein the first image depicts a face of a user ([Abstract] reciting “An image processing method includes the steps of: extracting a first two-dimensional feature point from a two-dimensional face image”);
identifying a first plurality of 3D facial feature points by applying a facial feature detection model to the first image, wherein each of the facial feature points identifies a 3D location of a facial feature of the user ([0040] reciting “In FIG. 1, (a) is an obtained two-dimensional facial image, and (b) is a three-dimensional face model. First, a two-dimensional first landmark DP1 may be extracted from the two-dimensional facial image illustrated in (a) by using a facial landmark detection algorithm.”; [0042] reciting “The present invention provides a method for obtaining an unextracted landmark from the two-dimensional facial image by using the facial landmark detection algorithm.”);
identifying a 2D ear feature point by applying an ear feature detection model to the first image, wherein the ear feature detection model is a machine-learning model trained to identify a location of an ear feature in an image, wherein the ear feature corresponds to a location on an ear of the user ([0075] reciting “All desired landmarks may not be obtained only with the landmark extracted from the two-dimensional facial image, or face learning data already obtained through machine learning may be provided, but desired landmark information may be omitted from the face learning data.”; [0061] reciting “The three-dimensional second landmark may include a landmark specified by a user (for example, an eyebrow, ear top point, and ear bottom point) based on a geometric model of a standard face provided in an internal or external database, or a landmark positioned in an area specified by the user (for example, an entire ear area).”);
generating a user head model based on the 2D ear feature point, the first plurality of 3D facial feature points, and a feature relationship model that describes relationships between facial features and ear features of users ([Abstract] reciting “generating a three-dimensional face model including the three-dimensional feature point set”; [0041] reciting “In the present invention, it is possible to update the three-dimensional landmark set based on a relationship between the three-dimensional first landmark TP1 and the two-dimensional first landmark DP1, and to generate a three-dimensional face model accordingly.”; [0061] reciting “The three-dimensional model generator 200 may derive a three-dimensional second landmark different from the three-dimensional first landmark, based on the geometric model of the standard face. The three-dimensional second landmark may include a landmark specified by a user (for example, an eyebrow, ear top point, and ear bottom point) based on a geometric model of a standard face provided in an internal or external database, or a landmark positioned in an area specified by the user (for example, an entire ear area).”; [0081] reciting “According to an embodiment, the geometric model of the standard face may include information on an area and proportion occupied by each portion of the face, and information on a distance between respective objects.”);
accessing a of the client device, wherein the second image depicts the face of the user ([Abstract] reciting “An image processing method includes the steps of: extracting a first two-dimensional feature point from a two-dimensional face image”);
identifying a second plurality of 3D facial feature points based on the second image ([0045] reciting “According to an embodiment, the three-dimensional second landmark TP2 estimated based on the three-dimensional first landmark TP1 may be specified according to the user's selection, or may be determined according to a type of the three-dimensional first landmark TP1.”);
estimating a 3D ear feature location for the ear feature based on the user head model and the second plurality of 3D facial feature points ([0061] reciting “The three-dimensional model generator 200 may derive a three-dimensional second landmark different from the three-dimensional first landmark, based on the geometric model of the standard face. The three-dimensional second landmark may include a landmark specified by a user (for example, an eyebrow, ear top point, and ear bottom point) based on a geometric model of a standard face provided in an internal or external database, or a landmark positioned in an area specified by the user (for example, an entire ear area).”);
5 Although Lee could teach accessing a first image captured by a camera of a client device, wherein the first image depicts a face of a user; … accessing a second image captured by a camera of the client device, wherein the second image depicts the face of the user ([0020] reciting “In one embodiment, the three-dimensional landmark set includes a three-dimensional second landmark different from the three-dimensional first landmark”; [0109] reciting “In Equation 6, F represents a two-dimensional projection result for a three-dimensional model X, K represents a camera-specific matrix, P represents an extrinsic parameter (three-dimensional rotation and transformation matrix)…”); … generating augmented reality content based on the estimated 3D feature location; augmenting the second image to include the augmented reality content; and displaying the augmented image to the user through the client device ([0027] reciting “When a landmark is estimated according to the present invention, a data augmentation service or the like capable of adding an estimated landmark in addition to a landmark annotated in existing facial data may be provided, thereby securing much more data.”), prior art from Hu can teach these limitations further.
6 Hu teaches accessing a first image captured by a camera of a client device, wherein the first image depicts a face of a user; … accessing a second image captured by a camera of the client device, wherein the second image depicts the face of the user ([0026] reciting “Exemplary aspects of the disclosure may include the electronic device and method to model a 3D face using multiple calibrated high-resolution cameras. All such cameras may capture images from several viewpoints, such as a front, a front-left, and a front-right view of the face and a depth sensor may be aligned with one of cameras to acquire depth information of the face.”; [0034] reciting “For example, the first image sensor 108A may capture a first color image from a first viewpoint 116A, the second image sensor 1088 may capture a second color image from a second viewpoint 1168, and the third image sensor 108C may capture a third color image from a third viewpoint 116C.”);
… generating augmented reality content based on the estimated 3D feature location ([0031] reciting “Examples of the electronic device 102 may include, but are not limited to, a computing device, a video-conferencing system, an augmented reality-based device, a gaming device, a mainframe machine, a server, a computer work-station, and/or a consumer electronic (CE) device.”; [0052] reciting “As an example, the second color image 318B from a frontal viewpoint (e.g., the second viewpoint 1168) may be used to generate the 3D model… In its 3D representation, the point cloud may spatially sample a surface portion of the subject's face 114 for a 3D representation of various facial features, such as eyes, nose, lips, ears, cheeks, or jaws.”);
augmenting the second image to include the augmented reality content ([0031] reciting “Examples of the electronic device 102 may include, but are not limited to, a computing device, a video-conferencing system, an augmented reality-based device, a gaming device, a mainframe machine, a server, a computer work-station, and/or a consumer electronic (CE) device.”; [0057] reciting “Examples of the one or more alignment parameters associated with the image sensor (e.g., the image sensors 108A, 108B, and 108C) may include, but are not limited to, a focal length, an aperture, an image sensor format, a principal point, a scale factor, and a lens distortion, associated with the image sensor.”; [0108] reciting “The assignment of a small energy value to pixels with a large confidence value may ensure that such pixels are selected as seam positions along which texture maps may be stitched. The selection of such pixels as the seam positions may enhance the confidence values along the seam.”); and
displaying the augmented image to the user through the client device ([0031] reciting “Examples of the electronic device 102 may include, but are not limited to, a computing device, a video-conferencing system, an augmented reality-based device, a gaming device, a mainframe machine, a server, a computer work-station, and/or a consumer electronic (CE) device.”; [0043] reciting “The I/O device 206 may include suitable logic, circuitry, interfaces, and/or code that may be configured to receive an input from a user. For example, the I/O device 206 may be configured to receive a user-input associated with a range of selection for seams in a layout for the final texture map. The I/O device 206 may be also configured to provide an output to the user. For example, as part of the I/O device 206, the display screen 206A may output the final texture map of the subject's face 114 and/or a 3D model onto which the final texture map may be applied.”).
7 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Lee) to incorporate the teachings of Hu to provide a clearer method to provide a camera that can capture more than one images, as well as to provide AR technology for the types of images and pluralities of features provided by the teachings of Lee. Doing so would provide suitable logic, circuitry, interfaces, and/or code that may be configured to generate a texture map of a face of a subject from multiple color images associated with multiple viewpoints as stated by Hu ([0031] recited).
8 Regarding claim 2, Lee in view of Hu teaches the method of claim 1 (see claim 1 rejection above), wherein the 2D ear feature point comprises coordinates for a pixel in the image depicting the ear feature (Lee; [0082] reciting “A top-of-ear y coordinate Ear_Y_Top.y may be calculated through a predetermined ratio of sum of y coordinates of the three landmarks eb_1, eb_2, and eb_3 constituting the eyebrow, and a bottom-of-ear y coordinate Ear_Y-Bottom.y may be calculated through a ratio of a y coordinate of a nose end point NB. In addition, a facial directional front end-of-ear z coordinate Ear_Z_Near.z has a z coordinate corresponding to a width F_w of a face area, and an occipital directional rear end-of-ear z coordinate Er_Z-Far.z may be calculated through a ratio of the facial directional front end-of-ear z coordinate Ear_Z_Near.z and the face area width F_w.”; [0104] reciting “Specifically, the three-dimensional first landmark TP1 projected as the two-dimensional second landmark DP2 corresponds to the adjusted two-dimensional third landmark DP3′, and accordingly a z coordinate of the third-dimension first landmark TP1 may be inputted as a z coordinate value of the corresponding points of the two-dimensional third landmark DP3′.”).
9 Regarding claim 3, Lee in view of Hu teaches the method of claim 2 (see claims 1-2 rejections above), wherein the 2D ear feature point describes a set of coordinates for a set of pixels in the image depicting the ear feature (Lee; [0020] reciting “In one embodiment, the three-dimensional landmark set includes a three-dimensional second landmark different from the three-dimensional first landmark, and the step of re-deriving, based on the two-dimensional third landmark, the three-dimensional landmark set may include a step of inserting a z coordinate of the three-dimensional first landmark with respect to the two-dimensional third landmark, and a step of deriving, based on a geometric model of a standard face, a three-dimensional fourth landmark with respect to a three-dimensional third landmark into which the z coordinate is inserted.”).
10 Regarding claim 4, Lee in view of Hu teaches the method of claim 1, wherein identifying a first plurality of 3D facial feature points comprises (see claim 1 rejection above):
identifying a first plurality of 3D facial feature points for a facial feature of the user (Lee; [0025] reciting “In one embodiment, the three-dimensional model generator may be configured to define the three-dimensional first landmark as a two-dimensional second landmark by projecting the three-dimensional first landmark onto a two-dimensional plane, rearrange…”).
11 Regarding claim 5, Lee in view of Hu teaches the method of claim 1, wherein generating the user head model comprises (see claim 1 rejection above):
12 Hu from claim 1 can further teach the limitations, specifically applying an objective function to the 2D ear feature point, the first plurality of 3D facial feature points, and the feature relationship model ([0026] reciting “The projection of the 3D model on multiple image planes may be based on perspective projection. The refinement of the shape model using RGB images may be based on a 3D flow refinement, which may optimize the offset for each vertex of the 3D model by minimizing the difference between the projected face models on 2D plane and the input images.”; [0059] reciting “The objective function may include a first term for the minimization of the difference between each of the set of viewpoint-specific projections (e.g., the viewpoint-specific projections 324A, 324B, and 324C) and the corresponding color image of the acquired set of color images (e.g., the color images 318A, 318B, and 318C)… The objective function may further include a second term to minimize an offset between a set of landmark points on each of the set of viewpoint-specific projections (e.g., the viewpoint-specific projections 324A, 324B, and 324C) and a corresponding set of feature points on a corresponding color image of the acquired set of color images (e.g., the color images 318A, 318B, and 318C). The objective function may further include a third term for the minimization of a sum of gradient magnitude of each component of a 3D flow term for each vertex of the generated 3D model 322.”; [0065] reciting “As an example, the first color image 318A may capture the right-side of the subject's face 114. In the first color image 318A, the left-side of the subject's face 114 including, for example, the left-ear may be occluded. Thus, a region representing the left-side of the subject's face 114 in the first texture map 328A may be wrongly projected due to occlusion of the left-ear in the first color image 318A.”).
13 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Lee) to incorporate the teachings of Hu to provide a type of objective function to be utilized for the ear feature points, the 3d facial feature points, and the relationships that are provided by the teachings of Lee (see claim 1 above). Doing so would provide suitable logic, circuitry, interfaces, and/or code that may be configured to generate a texture map of a face of a subject from multiple color images associated with multiple viewpoints as stated by Hu ([0031] recited).
14 Regarding claim 6, Lee in view of Hu teaches the method of claim 1, wherein generating the user head model comprises:
generating the user head model based on 2D ear feature points and 3D facial feature points identified based on a plurality of images (Lee; [0060] reciting “For example, when a partial facial image is cut off from the two-dimensional facial image, or when a front two-dimensional facial image is obtained, but a three-dimensional movement of turning a head from side to side is performed, it may be required to detect a position of an ear.”; [0061] reciting “The three-dimensional model generator 200 may derive a three-dimensional second landmark different from the three-dimensional first landmark, based on the geometric model of the standard face. The three-dimensional second landmark may include a landmark specified by a user (for example, an eyebrow, ear top point, and ear bottom point) based on a geometric model of a standard face provided in an internal or external database, or a landmark positioned in an area specified by the user (for example, an entire ear area).”)
15 Hu as mentioned previously in claim 1 further teaches the following limitations, specifically the plurality of images captured by the camera of the client device ([0026] reciting “Exemplary aspects of the disclosure may include the electronic device and method to model a 3D face using multiple calibrated high-resolution cameras. All such cameras may capture images from several viewpoints, such as a front, a front-left, and a front-right view of the face and a depth sensor may be aligned with one of cameras to acquire depth information of the face.”; [0034] reciting “For example, the first image sensor 108A may capture a first color image from a first viewpoint 116A, the second image sensor 1088 may capture a second color image from a second viewpoint 1168, and the third image sensor 108C may capture a third color image from a third viewpoint 116C.”).
16 As explained in the rejection of claim 1, the obviousness for combining of the camera of the client device of Hu into Lee is provided above.
17 Regarding claim 7, Lee in view of Hu teaches the method of claim 1 (see claim 1 rejection above), wherein the feature relationship model comprises statistical distributions of values representing a vector between a facial feature and the ear feature (Lee; [0081] reciting “With respect to the extracted landmark, the geometric model of the standard face may be used to derive landmarks defining an ear of a face. According to an embodiment, the geometric model of the standard face may include information on an area and proportion occupied by each portion of the face, and information on a distance between respective objects.”; [0082] reciting “A top-of-ear y coordinate Ear_Y_Top.y may be calculated through a predetermined ratio of sum of y coordinates of the three landmarks eb_1, eb_2, and eb_3 constituting the eyebrow, and a bottom-of-ear y coordinate Ear_Y-Bottom.y may be calculated through a ratio of a y coordinate of a nose end point NB. In addition, a facial directional front end-of-ear z coordinate Ear_Z_Near.z has a z coordinate corresponding to a width F_w of a face area, and an occipital directional rear end-of-ear z coordinate Er_Z-Far.z may be calculated through a ratio of the facial directional front end-of-ear z coordinate Ear_Z_Near.z and the face area width F_w. When coordinates of a particular point are thus obtained, different coordinates may be derived from the geometric model of the standard face. This in turn may be referred to as deriving a missing point based on a non missing point.”).
18 Regarding claim 8, Lee in view of Hu teaches the method of claim 1, wherein estimating a 3D ear feature location comprises (see claim 1 rejection above):
calculating a transformation from locations on the user head model to the physical world based on the 3D facial feature points (Lee; [0017] reciting “In order to perform following steps on a computer that applies a three-dimensional face model to a two-dimensional facial image, a program may be recorded on a physical recording medium that is readable by the computer. Both the physical recording medium on which the program is recorded and the program recorded on the physical storage medium may be within the scope of the present invention. The program executes steps of: extracting a two-dimensional first landmark from a two-dimensional facial image, deriving, based on a geometric model of a standard face, a three-dimensional landmark set including a three-dimensional first landmark corresponding to the two-dimensional first landmark, deriving a two-dimensional second landmark by projecting the three-dimensional first landmark onto a two-dimensional plane, rearranging, based on a similarity between the two-dimensional second landmark and the two-dimensional first landmark, the two-dimensional second landmark as a two-dimensional third landmark, and re-deriving, based on the two-dimensional third landmark, the three-dimensional landmark set.”).
19 Regarding claim 9, Lee in view of Hu teaches the method of claim 1, wherein displaying the augmented image comprises (see claim 1 rejection above):
20 Hu from claim can further teach the limitations, specifically transmitting the augmented image to the client device from a game server ([0031] reciting “Examples of the electronic device 102 may include, but are not limited to, a computing device, a video-conferencing system, an augmented reality-based device, a gaming device, a mainframe machine, a server, a computer work-station, and/or a consumer electronic (CE) device.”; [0032] reciting “Examples of the server 104 may include, but are not limited to, an application server, a cloud server, a web server, a database server, a file server, a gaming server, a mainframe server, or a combination thereof.”).
21 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Lee) to incorporate the teachings of Hu to provide a type of game server for the augmented methods, utilizing the images provided by Lee. Doing so would provide suitable logic, circuitry, interfaces, and/or code that may be configured to generate a texture map of a face of a subject from multiple color images associated with multiple viewpoints as stated by Hu ([0031] recited).
22 Claim 11 has similar limitations as of claim 1, therefore it is rejected under the same rationale as claim 1.
23 Claim 12 has similar limitations as of claim 2, therefore it is rejected under the same rationale as claim 2.
24 Claim 13 has similar limitations as of claim 3, therefore it is rejected under the same rationale as claim 3.
25 Claim 14 has similar limitations as of claim 4, therefore it is rejected under the same rationale as claim 4.
26 Claim 15 has similar limitations as of claim 5, therefore it is rejected under the same rationale as claim 5.
27 Claim 16 has similar limitations as of claim 6, therefore it is rejected under the same rationale as claim 6.
28 Claim 17 has similar limitations as of claim 7, therefore it is rejected under the same rationale as claim 7.
29 Claim 18 has similar limitations as of claim 8, therefore it is rejected under the same rationale as claim 8.
30 Claim 19 has similar limitations as of claim 9, therefore it is rejected under the same rationale as claim 9.
31 Claim(s) 10 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (US 20220012472 A1) in view of Hu et al. (US 20210209347 A1) as of claim 1 and 11, further in view of Teixido et al. (US 20220358726 A1) and Dong et al. (US 20170199565 A1).
32 Regarding claim 10, Lee in view of Hu teaches the method of claim 1, further comprising (see claim 1 rejection above):
identifying a third plurality of 3D facial feature points based on the image (Lee; [Abstract] reciting “An image processing method includes the steps of: extracting a first two-dimensional feature point from a two-dimensional face image”; [0040] reciting “In FIG. 1, (a) is an obtained two-dimensional facial image, and (b) is a three-dimensional face model. First, a two-dimensional first landmark DP1 may be extracted from the two-dimensional facial image illustrated in (a) by using a facial landmark detection algorithm.”; [0042] reciting “The present invention provides a method for obtaining an unextracted landmark from the two-dimensional facial image by using the facial landmark detection algorithm.”);
calculating a rotation of the user’s head based on the third plurality of 3D facial feature points (Lee; [0109] reciting “In Equation 6, F represents a two-dimensional projection result for a three-dimensional model X, K represents a camera-specific matrix, P represents an extrinsic parameter (three-dimensional rotation and transformation matrix), and X includes a value of an updated three-dimensional face model B′”); and
33 Hu as mentioned previously in claim 1 further teaches the following limitations, specifically accessing a third image captured by the camera of the client device ([0020] reciting “In one embodiment, the three-dimensional landmark set includes a three-dimensional second landmark different from the three-dimensional first landmark”; [0034] reciting “Each of the set of image sensors (i.e., image sensors 108A, 108B, and 108C) may include suitable logic, circuitry, and interfaces that may be configured to capture the set of color images of the subject's face 114 from the set of viewpoints. For example, the first image sensor 108A may capture a first color image from a first viewpoint 116A, the second image sensor 1088 may capture a second color image from a second viewpoint 1168, and the third image sensor 108C may capture a third color image from a third viewpoint 116C.”; [0109] reciting “In Equation 6, F represents a two-dimensional projection result for a three-dimensional model X, K represents a camera-specific matrix, P represents an extrinsic parameter (three-dimensional rotation and transformation matrix)…”);
34 As explained in the rejection of claim 1, the obviousness for combining of the camera and other multiple images of Hu into Lee is provided above.
35 Lee in view of Hu does not explicitly teach responsive to the rotation exceeding a threshold value, generating a new user head model based on the third plurality of 3D facial feature points, a new 2D ear feature point identified in the third image, and the feature relationship model.
36 Teixido teaches , generating a new user head model based on the third plurality of 3D facial feature points, a new 2D ear feature point identified in the third image, and the feature relationship model ([0008] reciting “In some embodiments, the processing unit is further configured to monitor a movement of the subject's head in the image sequence, and is configured to generate a new orientation for at least one virtual model based on the monitored movement of the subject's head, and the display is configured to display the new orientation of at least one virtual model.”; [0009] reciting “In some embodiments, the processing unit is further configured to monitor a movement of the display, and is configured to generate a new orientation for at least one virtual model of the inner ear based on the movement of the display.”; [0054] reciting “…as well as to visualize the relationship between nystagmus and the shifting of displaced otoconia within the ear. Still further, it has been also appreciated that little visual guidance is typically provided to practitioners while treating affected patients.”; [0081] reciting “In some cases, virtual objects rendered by AR program 318 may include virtual models of example human inner ears. For example, AR program 318 may render a two-dimensional (2D), or a three-dimensional (3D) virtual inner ear model (e.g., an anatomical 3D model of the inner ear, as shown in FIG. 1).”).
37 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Lee in view of Hu) to incorporate the teachings of Teixido to provide a method that updates the 3d model head with the ear data/points, the 3d facial features, and certain relationships of features that can be provided by the teachings of Lee in view of Hu. Doing so would allow the unit to monitor a movement of the subject's head in the image sequence as stated by Teixido ([0008] recited).
38 Lee in view of Hu and Teixido does not explicitly teach responsive to the rotation exceeding a threshold value…
39 Dong teaches in responsive to the rotation exceeding a threshold value ([Abstract] reciting “An interface interaction method and apparatus for actively interacting with a virtual interface only by rotating a user head, and pertaining to the field of augmented reality technologies.”; [0083] reciting “The interface layout shown in FIG. 2B is used as an example. Referring to FIG. 2I, FIG. 2I shows a schematic diagram for rotating an interface. The electronic device generates the fourth interaction instruction when the user head rotates upward and a rotation angular acceleration reaches or exceeds a threshold.”)…
40 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Lee in view of Hu and Teixido) to incorporate the teachings of Dong to provide a method that can determine if a rotation of a user’s head exceeds a certain threshold for the 3d head methods that are provided by teachings of Lee in view of Hu and Teixido. Doing so would ensure that a front-view sightline of the user is located at the center of an interface as stated by Dong ([0083] recited).
41 Claim 20 has similar limitations as of claim 10, therefore it is rejected under the same rationale as claim 10.
Conclusion
42 Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNY TRAN LE whose telephone number is (571)272-5680. The examiner can normally be reached Mon-Thu: 7:30am-5pm; First Fridays Off; Second Fridays: 7:30am-4pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kent Chang can be reached at (571) 272-7667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JOHNNY T LE/Examiner, Art Unit 2614
/KENT W CHANG/Supervisory Patent Examiner, Art Unit 2614
Prosecution Insights