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 .
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1-23 is/are rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 1-23 of prior U.S. Patent No. 12223117. This is a statutory double patenting rejection.
Claim Objections
Claims 4, 5, 15, 16, 20, 21 are objected to because of the following informalities: “the projection” lacks antecedent basis. Appropriate correction is required.
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, 2, 6, 13, 14, 17, 18, 19, 22, and 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Price et al. (US App. 20210358155) in view of Marsden et al. (US Pat. 11854308 hereinafter referred to as “Mars”) in further view of Hirasawa et al. (US App. 20120314908 hereinafter referred to as “Hira”).
In regard to claim 1, Price teaches a method (see at least Abstract) comprising: at a computing system including non-transitory memory and one or more processors (see Para. 152 and 198 memory and processors), wherein the computing system is communicatively coupled to a display device (Para. 79 HMD) and one or more input devices via a communication interface (see Para. 225 cameras and depth detection systems): obtaining hand tracking data (see Para. 225 detect position of hands); obtaining a depth map associated with a physical environment (see Para. 3-5 and 58 depth map); by performing point of view (POV) correction (See Para. 174 pass through view of user’s environment in Figs. 1-4).
Price is not relied upon to teach obtaining uncorrected hand tracking data;
identifying a position of a portion of the finger within the physical environment based on the depth map and the uncorrected hand tracking data; performing spatial depth smoothing on a region of the depth map adjacent to the position of the portion of the finger; and generating corrected hand tracking data; generating corrected hand data on the uncorrected hand tracking data based on the spatially depth smoothed region of the depth map adjacent to the portion of the finger.
However, Mars teaches obtaining uncorrected hand tracking data (see at least Abstract and Figs. 9-11); identifying a position of a portion of the finger within the physical environment based on the depth map and the uncorrected hand tracking data (See Figs. 9-11 and Col. 50 Ln 55-65 feature extraction through refinement of images and modeling using depth maps); performing spatial depth smoothing on a region of the depth map to the position of the portion of the finger (see Col. 37 Ln 35-65; Col. 35 Ln 50-65 and Col. 50 Ln 55-65 and Fig. 35A); and generating corrected hand tracking data (see Fig. 10, generating convolved image to extract hand features); on the uncorrected hand tracking data based on the spatially depth smoothed region of the depth map to the portion of the finger(see Col. 35 Ln 50-65; Col. 50 Ln 55-65 and Fig. 35A).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Price and Mars is not relied upon to teach the position is adjacent to the position.
As discussed above, Mars does already introduce the concept of detecting the gradient around the fingers of the candidate ROI (see Col. 37 Ln 35-65).
However, Hira teaches the position is adjacent to the position (see Abstract, Para. 7, 11, 93, 97 designating a pixel in a region excluding a predetermined region).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars and the exclusion of Hira for proper capture of the image (see Para. 4 and 97). Examiner also notes Price as modified by Mars discloses the base product/process of smoothing hand tracking outlines while Hira teaches the known technique of selective smoothing so as to yield predictable results of accurate hand data in the device of Price as modified by Mars.
In regard to claim 14, Price teaches a computing system (see at least Abstract) comprising: one or more processors; a non-transitory memory (see Para. 152 and 198 memory and processors); an interface (see Para. 224) for communicating with a display device (Para. 79 HMD) and one or more input devices (see Para. 225 cameras and depth detection systems); and one or more programs (Para. 230) stored in the non-transitory memory, which, when executed by the one or more processors, cause the computing system to: obtain hand tracking data(see Para. 225 detect position of hands);
obtain a depth map associated with a physical environment (see Para. 3-5 and 58 depth map); by performing point of view (POV) correction (See Para. 174 pass through view of user’s environment in Figs. 1-4).
Price is not relied upon to teach obtain uncorrected hand tracking data; identify a position of a portion of the finger within the physical environment based on the depth map and the uncorrected hand tracking data; perform spatial depth smoothing on a region of the depth map adjacent to the position of the portion of the finger; and generate corrected hand tracking data on the uncorrected hand tracking data based on the spatially depth smoothed region of the depth map adjacent to the portion of the finger.
However, Mars teaches obtain uncorrected hand tracking data (see at least Abstract and Figs. 9-11); identify a position of a portion of the finger within the physical environment based on the depth map and the uncorrected hand tracking data (See Figs. 9-11 and Col. 50 Ln 55-65 feature extraction through refinement of images and modeling using depth maps); perform spatial depth smoothing on a region of the depth map to the position of the portion of the finger (see Col. 37 Ln 35-65; Col. 35 Ln 50-65 and Col. 50 Ln 55-65 and Fig. 35A); and generate corrected hand tracking data (see Fig. 10, generating convolved image to extract hand features) on the uncorrected hand tracking data based on the spatially depth smoothed region of the depth map to the portion of the finger (see Col. 35 Ln 50-65; Col. 50 Ln 55-65 and Fig. 35A).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Price and Mars is not relied upon to teach the position is adjacent to the position.
As discussed above, Mars does already introduce the concept of detecting the gradient around the fingers of the candidate ROI (see Col. 37 Ln 35-65).
However, Hira teaches the position is adjacent to the position (see Abstract, Para. 7, 11, 93, 97 designating a pixel in a region excluding a predetermined region).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars and the exclusion of Hira for proper capture of the image (see Para. 4 and 97). Examiner also notes Price as modified by Mars discloses the base product/process of smoothing hand tracking outlines while Hira teaches the known technique of selective smoothing so as to yield predictable results of accurate hand data in the device of Price as modified by Mars.
In regard to claim 19, Price teaches a non-transitory memory storing one or more programs, which, when executed by one or more processors (see Para. 152 and 198 memory and processors) of a computing system with an interface for communicating with a display device and one or more input devices, cause the computing system to: obtain hand tracking data (see Para. 225 detect position of hands); obtain a depth map associated with a physical environment (see Para. 3-5 and 58 depth map); by performing point of view (POV) correction (See Para. 174 pass through view of user’s environment in Figs. 1-4).
Price is not relied upon to teach obtain uncorrected hand tracking data; identify a position of a portion of the finger within the physical environment based on the depth map and the uncorrected hand tracking data; perform spatial depth smoothing on a region of the depth map adjacent to the position of the portion of the finger; and generate corrected hand tracking data on the uncorrected hand tracking data based on the spatially depth smoothed region of the depth map adjacent to the portion of the finger.
However, Mars teaches obtain uncorrected hand tracking data (see at least Abstract and Figs. 9-11); identify a position of a portion of the finger within the physical environment based on the depth map and the uncorrected hand tracking data (See Figs. 9-11 and Col. 50 Ln 55-65 feature extraction through refinement of images and modeling using depth maps); perform spatial depth smoothing on a region of the depth map to the position of the portion of the finger (see Col. 37 Ln 35-65; Col. 35 Ln 50-65 and Col. 50 Ln 55-65 and Fig. 35A); and generate corrected hand tracking data (see Fig. 10, generating convolved image to extract hand features) on the uncorrected hand tracking data based on the spatially depth smoothed region of the depth map to the portion of the finger (see Col. 35 Ln 50-65; Col. 50 Ln 55-65 and Fig. 35A).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Price and Mars is not relied upon to teach the position is adjacent to the position.
As discussed above, Mars does already introduce the concept of detecting the gradient around the fingers of the candidate ROI (see Col. 37 Ln 35-65).
However, Hira teaches the position is adjacent to the position (see Abstract, Para. 7, 11, 93, 97 designating a pixel in a region excluding a predetermined region).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars and the exclusion of Hira for proper capture of the image (see Para. 4 and 97). Examiner also notes Price as modified by Mars discloses the base product/process of smoothing hand tracking outlines while Hira teaches the known technique of selective smoothing so as to yield predictable results of accurate hand data in the device of Price as modified by Mars.
Regarding claim 2, Price in view of Mars and Hira teaches all the limitations of claim 1. Price is not relied upon to teach wherein the portion of the finger corresponds to one of a fingertip, a particular knuckle, or a centroid of a finger. However, Mars further teaches wherein the portion of the finger corresponds to one of a fingertip, a particular knuckle, or a centroid of a finger (see Col. 34 Ln 50-60 fingertip bend through joint by joint analysis).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Regarding claim 6, Price in view of Mars and Hira teaches all the limitations of claim 1. Price further teaches POV correction (See Para. 174 pass through view of user’s environment in Figs. 1-4).
Price is not relied upon to teach performing correction on the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger includes performing correction on each joint within the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger.
However, Mars teaches wherein performing correction on the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger includes performing correction on each joint within the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger (See Figs. 9-11 and Col. 50 Ln 55-65 feature extraction through refinement of images and modeling using depth maps and Fig. 35A around hand).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Regarding claim 13, Price in view of Mars and Hira teaches all the limitations of claim 1. Mars further teaches rendering a user interaction with a virtual object based on the corrected hand tracking data (see Figs. 40A and 40B); and presenting, via the display device, the rendered user interaction with the virtual object based on the corrected hand tracking data (see Figs 40A and 40B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the virtual hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of virtual hand data so as to yield predictable results of accurate hand data in the device of Price.
Regarding claim 17, Price in view of Mars and Hira teaches all the limitations of claim 14. Price further teaches POV correction (See Para. 174 pass through view of user’s environment in Figs. 1-4).
Price is not relied upon to teach wherein performing correction on the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger includes performing correction on each joint within the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger.
However, Mars teaches performing correction on the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger includes performing correction on each joint within the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger (See Figs. 9-11 and Col. 50 Ln 55-65 feature extraction through refinement of images and modeling using depth maps and Fig. 35A around hand).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Regarding claim 22, Price in view of Mars and Hira teaches all the limitations of claim 19. Price further teaches POV correction (See Para. 174 pass through view of user’s environment in Figs. 1-4).
Price is not relied upon to teach wherein performing correction on the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger includes performing correction on each joint within the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger.
However, Mars teaches wherein performing correction on the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger includes performing correction on each joint within the uncorrected hand tracking data based on the spatially depth smoothed region adjacent to the portion of the finger (See Figs. 9-11 and Col. 50 Ln 55-65 feature extraction through refinement of images and modeling using depth maps and Fig. 35A around hand).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Regarding claim 18, Price in view of Mars and Hira teaches all the limitations of claim 14. Mars further teaches wherein the one or more programs further cause the computing system to: render a user interaction with a virtual object based on the corrected hand tracking data (see Figs. 40A and 40B); and present, via the display device, the rendered user interaction with the virtual object based on the corrected hand tracking data (see Figs 40A and 40B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the virtual hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of virtual hand data so as to yield predictable results of accurate hand data in the device of Price.
Regarding claim 23, Price in view of Mars and Hira teaches all the limitations of claim 19. Mars further teaches wherein the one or more programs further cause the computing system to: render a user interaction with a virtual object based on the corrected hand tracking data (see Figs 40A and 40B); and present, via the display device, the rendered user interaction with the virtual object based on the corrected hand tracking data (see Figs 40A and 40B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the virtual hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of virtual hand data so as to yield predictable results of accurate hand data in the device of Price.
Claim(s) 3, 4, 5, 15, 16, 20, 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Price et al. (US App. 20210358155) in view of Marsden et al. (US Pat. 11854308 hereinafter referred to as “Mars”) and Hira in further view of Litvak et al. (US Pat. 9002099 hereinafter “Lit”).
Regarding claim 3, Price in view of Mars and Hira teaches all the limitations of claim 1. Price and Mar and Hira s are not relied upon to teach wherein the position of the portion of the finger is identified by projecting the portion of a finger into a depth space associated with the depth map.
As discussed above, Mars already discloses the concept of the portion of the finger (see Col. 34 Ln 50-60 fingertip bend through joint by joint analysis) and Hira discloses the selective smoothing (see at least Abstract).
However, Lit teaches wherein the position of the portion of the finger is identified by projecting a finger into a depth space associated with the depth map (see Col. 3, Ln 30-35; Col. 5, Ln 1-25; Fig. 4A; normalizing a depth of the depth map by finding a representative depth coordinate of the human hand in the depth map and projecting a point cloud derived from the depth map responsively to the representative depth coordinate, and applying the normalized depth in matching the descriptors and estimating the pose -descriptor patches distributed to specific positions).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price and Mars with the projecting of Lit for 3D mapping (See Col. ,1 Ln 15-20). Examiner also notes Price and Mars and Hira disclose the base product/process of selective pixel hand tracking smoothing and mapping while Lit teaches the known technique of projecting descriptor patches in a depth map so as to yield predictable results of accurate hand data in the device of Price as modified by Mars and Hira.
Regarding claim 4, Price in view of Mars and Hira teaches all the limitations of claim 1. Price further teaches wherein the region of the depth map corresponds to an NxM pixel (see Para. 96 pixel matrix). Price is not relied upon to teach adjacent to the portion of the finger and area centered on the projection of the portion of the finger. However, Mars teaches adjacent to the portion of the finger and area centered on the projection of the portion of the finger (See Figs. 9-11 and Col. 50 Ln 55-65 and Fig. 35A feature extraction through refinement of images and modeling using depth maps around fingers).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars for precision interaction with virtual objects (see Col. 2, Ln 15-20). Examiner also notes Price discloses the base product/process of hand tracking while Mars teaches the known technique of smoothing hand data so as to yield predictable results of accurate hand data in the device of Price.
Regarding claim 5, Price in view of Mars and Hira teaches all the limitations of claim 1. Price and Mars are not relied upon to teach wherein the region of the depth map to the portion of the finger corresponds to a predefined radius centered on the projection of the portion of the finger.
However, Lit teaches wherein the region of the depth map to the portion of the finger corresponds to a predefined radius centered on the projection of the portion of the finger (see Col. 11, 60-65 radius and Figs. 4A-4B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price and Mars and Hira with the finger analysis of Lit for depth map data extraction (see Col. 1, Ln 15-20). Examiner also notes Price and Mars disclose the base product/process of hand tracking while Lit teaches the known technique of depth data extraction so as to yield predictable results of accurate hand data in the device of Price as modified by Mars.
Regarding claim 16, Price in view of Mars and Hira teaches all the limitations of claim 14. Price and Mars are not relied upon to teach wherein the region of the depth map to the portion of the finger corresponds to a predefined radius centered on the projection of the portion of the finger.
However, Lit teaches wherein the region of the depth map to the portion of the finger corresponds to a predefined radius centered on the projection of the portion of the finger (see Col. 11, 60-65 radius and Figs. 4A-4B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price and Mars and Hira with the finger analysis of Lit for depth map data extraction (see Col. 1, Ln 15-20). Examiner also notes Price and Mars disclose the base product/process of hand tracking while Lit teaches the known technique of depth data extraction so as to yield predictable results of accurate hand data in the device of Price as modified by Mars and Hira.
Regarding claim 15, Price in view of Mars and Hira teaches all the limitations of claim 14. Price further teaches corresponds to an NxM pixel area (see Para. 96 pixel matrix). Mars in combination with Hira as discussed above further teaches wherein the region of the depth map adjacent (see Hira see Abstract, Para. 7, 11, 93, 97 designating a pixel in a region excluding a predetermined region) to the portion of the finger (see Mars Col. 37 Ln 35-65; Col. 35 Ln 50-65 and Col. 50 Ln 55-65 and Fig. 35A).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars and the exclusion of Hira for proper capture of the image (see Para. 4 and 97). Examiner also notes Price as modified by Mars discloses the base product/process of smoothing hand tracking outlines while Hira teaches the known technique of selective smoothing so as to yield predictable results of accurate hand data in the device of Price as modified by Mars.
Price in view of Mars and Hira is not relied upon to teach region centered on the projection of the portion of the finger. However, Lit teaches wherein the region of the finger centered on the finger (see Col. 11, 60-65 radius and Figs. 4A-4B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price and Mars and Hira with the finger analysis of Lit for depth map data extraction (see Col. 1, Ln 15-20). Examiner also notes Price and Mars disclose the base product/process of hand tracking while Lit teaches the known technique of depth data extraction so as to yield predictable results of accurate hand data in the device of Price as modified by Mars and Hira.
Regarding claim 20, Price in view of Mars and Hira teaches all the limitations of claim 19. Price further teaches corresponds to an NxM pixel area (see Para. 96 pixel matrix). Mars in combination with Hira as discussed above further teaches wherein the region of the depth map adjacent (see Hira see Abstract, Para. 7, 11, 93, 97 designating a pixel in a region excluding a predetermined region) to the portion of the finger (see Mars Col. 37 Ln 35-65; Col. 35 Ln 50-65 and Col. 50 Ln 55-65 and Fig. 35A).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price with the smoothing hand data of Mars and the exclusion of Hira for proper capture of the image (see Para. 4 and 97). Examiner also notes Price as modified by Mars discloses the base product/process of smoothing hand tracking outlines while Hira teaches the known technique of selective smoothing so as to yield predictable results of accurate hand data in the device of Price as modified by Mars.
Price in view of Mars and Hira is not relied upon to teach region centered on the projection of the portion of the finger. However, Lit teaches wherein the region of the finger centered on the finger (see Col. 11, 60-65 radius and Figs. 4A-4B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price and Mars and Hira with the finger analysis of Lit for depth map data extraction (see Col. 1, Ln 15-20). Examiner also notes Price and Mars disclose the base product/process of hand tracking while Lit teaches the known technique of depth data extraction so as to yield predictable results of accurate hand data in the device of Price as modified by Mars and Hira.
Regarding claim 21, Price in view of Mars and Hira teaches all the limitations of claim 19. Price and Mars and Hira are not relied upon to teach wherein the region of the depth map to the portion of the finger corresponds to a predefined radius centered on the projection of the portion of the finger.
However, Lit teaches wherein the region of the depth map to the portion of the finger corresponds to a predefined radius centered on the projection of the portion of the finger (see Col. 11, 60-65 radius and Figs. 4A-4B).
It would have been obvious to a person of ordinary skill in the art to modify the input device of Price and Mars and Hira with the finger analysis of Lit for depth map data extraction (see Col. 1, Ln 15-20). Examiner also notes Price and Mars and Hira disclose the base product/process of hand tracking while Lit teaches the known technique of depth data extraction so as to yield predictable results of accurate hand data in the device of Price as modified by Mars and Hira.
Allowable Subject Matter
Claims 7-12 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Park (US Pat. 7869646) and Cho (US Pat. 9881423).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW YEUNG whose telephone number is (571)272-4115. The examiner can normally be reached M-F 9am-5pm EST.
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/MATTHEW YEUNG/Primary Examiner, Art Unit 2625