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 03/29/2024 and 07/29/2025 have been considered by the examiner.
Election/Restrictions
Applicant’s election without traverse of Group II (claims 9-20) in the reply filed on 04/27/2026 is acknowledged.
Status of Claims
Currently pending Claim(s):
Withdrawn claim(s):
1-20 (9-20 are examined)
1-8
Claim Objections
Claims 12- 14, 17, 19, and 20 are objected to because of the following informalities:
Claim 12 line 5 recites “..is further to:”. Examiner suggests amending the phrase to “…is further configured to:”.
Claim 13 line 9 recites “..is further to:”. Examiner suggests amending the phrase to “…is further configured to:”.
Claim 14 line 1 recites “..is further to:”. Examiner suggests amending the phrase to “…is further configured to:”.
Claim 17 line 3 recites “..is further to:”. Examiner suggests amending the phrase to “…is further configured to:”.
Claim 19 line 1 recites “..is further to:”. Examiner suggests amending the phrase to “…is further configured to:”.
Claim 20 line 2 recites “..is further to:”. Examiner suggests amending the phrase to “…is further configured to:”. 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.
Claims 9-20 are rejected under 35 U.S.C. 103 as being unpatentable over Cleland et al. (US 9,808,154 B2) (hereinafter, “Cleland”) and further in view of Trail (US 10,268,268 B1).
Regarding claim 9, Cleland discloses an eye tracking system for a near-eye display device (Figure 3; Column 9 [lines 11-13] “FIG. 3 illustrates another example system 300 for biometric identification via retina scanning with liveness detection.”; Column 10 [lines 40-44] “Machine vision subunit 322 obtains images external to the eye. The images are used to calculate the spatial location of a subject's eye relative to the device. This allows continuous eye tracking, real-time position monitoring and autofocusing.”), comprising:
a light source to illuminate an eye (Column 9 [lines 44-47] “The subsystem may contain image sensor(s), light sources and associated optics, or share the components with the other units. Additionally, a fixation source (e.g., a point source) may be used to ensure eye stabilization.”);
an image sensor (Image acquisition subsystem 320 in Column 9 [lines 30-33] equates to image sensor) to capture a series of images of the eye by capturing reflections of the eye illuminated by the light source [when the eye is stationary] (Column 5 [lines 6-9] “The retina would serve as a stationary surface”; Column 9 [lines 30-33] “Image acquisition subsystem 320 includes the integration of light sources, optics, and sensors used to obtain external and internal images of an eye.”; Column 9 [lines 59-66] “subunit 324 may generate one or a sequence of retinal images while illuminating the retina with light source(s) of one or several wavelengths, successively or simultaneously”); and a controller (Image analysis subsystem 340 in Column 11 [lines 49-56] equates to a controller) communicatively coupled to the image sensor, the controller to determine reflected pattern changes due to blood flow using the captured series of images of reflections of the eye [when the eye is stationary] (Column 10 [lines 39-55] “Subunit 326 may, for example, illuminate the preferred area of retinal surface with diffuse laser light…The light would then be focused on an image sensor (e.g., a CCD array) to capture the speckle pattern of the illuminated area. The data from the raw speckle image(s) could then be statistically manipulated to calculate local contrasts across the image and then converted into the relative blood flow map.”; Column 11 [lines 49-56] “Image analysis subsystem 340 is divided…an image processing subunit 342, a features extraction subunit 344, a features analysis subunit 346, and a data matching subunit 348.”; Column 12 [lines 1-9] “The features analysis subunit 346 computes and groups the relevant information about extracted physiologic components that can be used to compare/differentiate between subjects…the branch point locations for retina blood vessels and their spatial associations may be computed and stored. Additionally, the unit 346 may also analyze images to perform “liveness detection” (e.g., using speckle contrast, vein/artery recognition, etc.).”) and to perform at least one of user authentication or liveness detection based on the detected pattern changes due to blood flow (Column 2 [lines 26-30] “additional image acquisition device such as image processing and analysis techniques to assess the extent of “liveness” of the scanned retina. This could be an additional security measure used to prevent “spoofing,””; Column 12 [lines 1-9] “The features analysis subunit 346 computes and groups the relevant information about extracted physiologic components that can be used to compare/differentiate between subjects… Additionally, the unit 346 may also analyze images to perform “liveness detection” (e.g., using speckle contrast, vein/artery recognition, etc.).”).
However, Cleland fails to teach when the eye is stationary.
Trail teaches when the eye is stationary (Column 14 [lines 60-63] “determines, based on magnitudes/relative contrasts of reflected and captured light, that the eye 325 is in a stationary position within the eye-box 327 and only orientation of the eye 325 is changing”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Cleland’s reference to include when the eye is stationary taught by Trail’s reference. The motivation for doing so would have been to efficiently mitigate interference of light beams as suggested by Trail (see Trail, Column 14 [lines 22-29]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Trail with Cleland to obtain the invention specified in claim 9.
Regarding claim 10, which claim 9 is incorporated, Cleland discloses wherein the blood flow is in at least one capillary of the eye (Column 4 [lines 45-56] “a frequency shift that arises in light that has been scattered by moving red blood cells may be measured to obtain a quantification of blood cell movement…the measurements may be made at points at which blood flow is expected (e.g., on blood vessels) and at points at which blood flow is not expected (e.g., off blood vessels).”) or the skin tissue surrounding the eye (Examiner notes that claims requires blood flow is in at least one capillary of the eye or the skin tissue surrounding the eye).
Regarding claim 11, which claim 9 is incorporated, Cleland discloses wherein the light source is to illuminate the eye with at least one of a statistically random pattern, an interference pattern (Column 4 [lines 57-58] “speckle contrast imaging, when an object is illuminated with coherent light, a speckle pattern, or random interference pattern”), a sinusoidal pattern, a binary pattern, a multi-level pattern, a code-based pattern, a color-based pattern, or a geometrical pattern.
Regarding claim 12, which claim 9 is incorporated, Cleland discloses wherein the light source is to illuminate the eye with a speckle pattern (Column 4 [lines 57-58] “speckle contrast imaging, when an object is illuminated with coherent light, a speckle pattern, or random interference pattern”), the captured series of images comprise a plurality of reflections of the speckle pattern from the eye [when the eye is stationary] (Column 5 [lines 6-11] “The retina would serve as a stationary surface, whereas the moving particles (i.e., red blood cells) would be a dynamically changing scattering medium.”; Column 9 [lines 59-66] “subunit 324 may generate one or a sequence of retinal images while illuminating the retina with light source(s) of one or several wavelengths, successively or simultaneously”; Column 10 [lines 39-55] “Speckle contrast imaging may be utilized for blood flow detection and simultaneously be used as a vasculature detection technique… Subunit 326 may, for example, illuminate the preferred area of retinal surface with diffuse laser light—for example, by directing infrared light (e.g., from a semiconductor laser source) with the help of optical elements. The back-scattered light from the retina surface again would pass through the objective lens and enter the observation optical system, perhaps via an image stabilizer. The light would then be focused on an image sensor (e.g., a CCD array) to capture the speckle pattern of the illuminated area. The data from the raw speckle image(s) could then be statistically manipulated to calculate local contrasts across the image and then converted into the relative blood flow map.”); and the controller is further [configured] to:
compute speckle contrast based on the captured plurality of reflections of the speckle pattern from the eye [when the eye is stationary] (Column 5 [lines 6-9] “Given that the retina is a highly scattering tissue, the speckle contrast imaging method is a suitable way to detect blood flow in retinal vessels. The retina would serve as a stationary surface”; Column 11 [lines 5-9] “the temporal speckle contrast may be calculated to detect flow using series of images. In this approach, the statistical analysis is performed on the corresponding pixels taken from n number of subsequent images. “); and
determine the reflected pattern changes due to blood flow based on the computed speckle contrast (Column 11 [ lines 9-15] “the theoretical speckle contrast has values between 0 and 1. A speckle contrast of 1 indicates that there is no blurring of the speckle pattern and, therefore, no flow, while a speckle contrast of 0 means that the scatterers (blood cells) are moving with sufficient speed enough to “average” the speckle background.”).
However, Cleland fails to teach when the eye is stationary.
Trail teaches when the eye is stationary (Column 14 [lines 60-63] “determines, based on magnitudes/relative contrasts of reflected and captured light, that the eye 325 is in a stationary position within the eye-box 327 and only orientation of the eye 325 is changing”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Cleland’s reference to include when the eye is stationary taught by Trail’s reference. The motivation for doing so would have been to efficiently mitigate interference of light beams as suggested by Trail (see Trail, Column 14 [lines 22-29]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Trail with Cleland to obtain the invention specified in claim 12.
Regarding claim 13, which claim 9 is incorporated, Cleland discloses wherein the light source comprises:
a first light source to illuminate the eye with a first central wavelength (Column 7 [lines 26-32] “image acquisition subsystem 110 scans an eye to acquire at least one image of the retina and an image of the blood flowing therethrough. In some implementations, retina images may be generated in the red spectrum, the green spectrum, and the blue spectrum, and blood flow may be imaged in the infrared spectrum. The image(s) may then be conveyed to image analysis subsystem 120, which may process the retina image(s) to identify retinal blood vessels.”; Examiner interprets retina images may be generated in the red spectrum, the green spectrum, and the blue spectrum equates to first light source with first central wavelength); and
a second light source to illuminate the eye with a second central wavelength (Column 7 [lines 26-32] “image acquisition subsystem 110 scans an eye to acquire at least one image of the retina and an image of the blood flowing therethrough. In some implementations, retina images may be generated in the red spectrum, the green spectrum, and the blue spectrum, and blood flow may be imaged in the infrared spectrum. The image(s) may then be conveyed to image analysis subsystem 120, which may process the retina image(s) to identify retinal blood vessels.”; Examiner interprets blood flow imaged in the infrared spectrum equates to second light course with second central wavelength);
the image sensor is to capture the series of images of the eye [when the eye is stationary] by capturing at least one reflection of the first central wavelength from the eye [when the eye is stationary] and at least one reflection of the second central wavelength from the eye [when the eye is stationary] (Column 5 [lines 6-9] “Given that the retina is a highly scattering tissue, the speckle contrast imaging method is a suitable way to detect blood flow in retinal vessels. The retina would serve as a stationary surface”; Column 6 [lines 43-56] ”The retina imager may, for example, obtain retina images by means of line scanning laser technology. The measuring laser beam may, for instance, may form a spot conjugate with the fundus of the eye to be examined. The optics may then reform the reflected light into a complementary line that defines the reflectivity profile of the illuminated region and then focus the image onto a sensor. Sweeping the laser line across the retina surface allows collection of reflection intensity profiles (e.g., in a linear CCD device, possibly after being enlarged by an optical lens), which are then further reconstructed into an aerial reflection profile. In particular implementations, the retina imager may generate multiple images of the retina—in the red spectrum, in the green spectrum, and/or in the blue spectrum. (i.e. different central wavelengths)”), and
the controller is further [configured] to perform at least one of user authentication and liveness detection based on the captured at least one reflection of the first central wavelength and the captured at least one reflection of the second central wavelength (Column 8 [lines 4-14] “liveness detection (e.g., retinal blood flow recognition) may also be used to differentiate between living tissue and non-living duplicates…automatically acquire retinal images and extract meaningful physiological information, such as the presence or absence of blood vessels, bifurcation locations, the presence or absence of blood flow, and other uniqueness markers, which could be then used as identity authentication.”).
However, Cleland fails to teach when the eye is stationary.
Trail teaches when the eye is stationary (Column 14 [lines 60-63] “determines, based on magnitudes/relative contrasts of reflected and captured light, that the eye 325 is in a stationary position within the eye-box 327 and only orientation of the eye 325 is changing”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Cleland’s reference to include when the eye is stationary taught by Trail’s reference. The motivation for doing so would have been to efficiently mitigate interference of light beams as suggested by Trail (see Trail, Column 14 [lines 22-29]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Trail with Cleland to obtain the invention specified in claim 13.
Regarding claim 14, which claim 13 is incorporated, Cleland discloses wherein the controller is further [configured] to:
compute ratiometric data based on the captured at least one reflection of the first central wavelength and the captured at least one reflection of the second central wavelength (Column 14 [lines 29-40] “Given different light absorption characteristics for oxy- and deoxyhemoglobin in red blood cells, a retina can be first illuminated with a wavelength at which absorption characteristics differ substantially for oxygenated or deoxygenated hemoglobin (i.e. first central wavelength). The resulting images will then have one type of vessels more apparent than the other. Then, a control image might be obtained by using a wavelength that is equally absorbed by oxy- and deoxyhemoglobin (i.e. second central wavelength). The resulting images can be added/subtracted (i.e. via union, intersection, complementation) to contain only the desired type of vessels.”); and perform at least one of user authentication and liveness detection based on the computed ratiometric data (Column 14 [lines 19-26] “Process 400 also calls for determining data regarding the live tissue features (operation 420). Live tissue features may, for example, include the maps of blood flow in the retina, which could be compared against a previously derived map or against a blood vessel network. Another live tissue feature is a map of veins/arteries. This map may be compared against a previously derived vein/artery map or against a blood vessel network.”).
Regarding claim 15, which claim 14 is incorporated, Cleland discloses wherein the computed ratiometric data comprises data of a ratio of oxygenated hemoglobin to non-oxygenated hemoglobin (Column 14 [lines 29-40] “Given different light absorption characteristics for oxy- and deoxyhemoglobin in red blood cells, a retina can be first illuminated with a wavelength at which absorption characteristics differ substantially for oxygenated or deoxygenated hemoglobin. The resulting images will then have one type of vessels more apparent than the other. Then, a control image might be obtained by using a wavelength that is equally absorbed by oxy- and deoxyhemoglobin. The resulting images can be added/subtracted (i.e. via union, intersection, complementation) to contain only the desired type of vessels.”).
Regarding claim 16, which claim 9 is incorporated, Cleland fails to teach a waveguide to display at least one of augmented reality (AR) or virtual reality (VR) images to the eye, wherein the light source is integrated with the waveguide.
Trail teaches a waveguide to display at least one of augmented reality (AR) or virtual reality (VR) images to the eye, wherein the light source is integrated with the waveguide (Column 9 [lines 45-47] “The HMD 200 may be part of, e.g., a VR system, an AR system, a MR system, or some combination thereof.”; Column 11 [lines 19-27] “the eye tracker 135 is part of some other HMD. As illustrated in FIG. 3, the eye tracker 300 comprises an array of light sources 305, a waveguide 310, a plurality of SBGs 315 (e.g., SBG columns n−1, n, n+1, . . . ) designed into the waveguide 310, and a detector array 320. The SBG columns 315 are part of the waveguide 310, and the waveguide 310 is coupled to the array of light sources 305 and the detector array 320.”)
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Cleland’s reference to include a waveguide to display at least one of augmented reality (AR) or virtual reality (VR) images to the eye, wherein the light source is integrated with the waveguide by Trail’s reference. The motivation for doing so would have been to reject noise in a return signal and locate a user’s gaze direction as suggested by Trail (see Trail, Column 11 [lines 56-62]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Trail with Cleland to obtain the invention specified in claim 16.
Regarding claim 17, which claim 9 is incorporated, Cleland discloses a retinal projection system to project light into the eye, wherein the controller is further [configured] to Figure 3; Column 9 [lines 11-13] “FIG. 3 illustrates another example system 300 for biometric identification via retina scanning with liveness detection.”; Column 10 [lines 40-44] “Machine vision subunit 322 obtains images external to the eye. The images are used to calculate the spatial location of a subject's eye relative to the device. This allows continuous eye tracking, real-time position monitoring and autofocusing.”):
receive image data of a reflection of the light projected by the retinal projection system (Column 3 [lines 26-40] “ Image acquisition subsystem 110 may include the optics required to illuminate the retina and to focus the reflected light on the image detector(s). Also, additional light sources, optics, and sensors for external eye illumination, viewing, and fixation may be included in this subsystem.”);
determine a retinal vasculature pattern of the eye based on the received image data (Column 4 [lines 12-21] “Features analysis may determine data regarding components. For example, features analysis may determine the spatial relationship between various retina components (e.g., blood vessels, optic disc and fovea). Additionally, features analysis may determine data about one or more components (e.g., vessel segment length and location, branch points, number of branches, segment orientation, vein, artery, pulse rate, and others). The data regarding the features may be stored in a database that can be used to compare/differentiate between subjects.”); and
perform at least one of user authentication or liveness detection using the determined retinal vasculature pattern of the eye (Column 3 [lines 49-54] “ Image analysis subsystem 120 is responsible for analyzing the image(s) acquired by image acquisition subsystem 110 and determining whether the imaged retina is associated with a retina that has been previously imaged (e.g., previously stored in a secure database) and whether or not the imaged retina is alive (“liveness detection”).”; Column 5 [lines 24-29] “image analysis system 120 may develop a set of blood vessels based on the blood flow and attempt to match them to the vessels obtained from the retina image and/or from the pre-stored data set (e.g., based on branch points). As another example, the verification of “liveness” could be based on the presence of pulsatile blood flow in selected vessel(s).”).
Regarding claim 18, which claim 17 is incorporated, Cleland discloses wherein the light projected by the retinal projection system is in the near infrared range (Column 10 [lines 21-23] “The laser sources used in scanning laser ophthalmoscopy typically include wavelengths from blue, green, red, and near-infrared parts of the spectrum.”).
Regarding claim 19, which claim 9 is incorporated, Cleland discloses [wherein the controller is further [configured] to determine when the eye is stationary] and to obtain the captured series of images of the eye (Column 9 [lines 59-66] “subunit 324 may generate one or a sequence of retinal images while illuminating the retina with light source(s) of one or several wavelengths, successively or simultaneously”) [when the eye is determined to be stationary].
However, Cleland fails to teach wherein the controller is further [configured] to determine when the eye is stationary.
Trail teaches wherein the controller is further [configured] to determine when the eye is stationary (Column 14 [lines 60-66] “determines, based on magnitudes/relative contrasts of reflected and captured light, that the eye 325 is in a stationary position within the eye-box 327 and only orientation of the eye 325 is changing (i.e., only gaze direction is changing), the controller 330 and the eye tracker 300 can proceed to a fine resolution tracking mode of operation.”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Cleland’s reference to include wherein the controller is further [configured] to determine when the eye is stationary taught by Trail’s reference. The motivation for doing so would have been to efficiently mitigate interference of light beams as suggested by Trail (see Trail, Column 14 [lines 22-29]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Trail with Cleland to obtain the invention specified in claim 19.
Regarding claim 20, which claim 19 is incorporated, Cleland discloses [wherein upon determining the eye is stationary], the controller is further [configured] to:
control the light source to illuminate the eye (Column 9 [lines 44-47] “The subsystem may contain image sensor(s), light sources and associated optics, or share the components with the other units. Additionally, a fixation source (e.g., a point source) may be used to ensure eye stabilization.”);
control the image sensor to capture the series of images of the eye while the eye is illuminated [and stationary] (Column 5 [lines 6-9] “Given that the retina is a highly scattering tissue, the speckle contrast imaging method is a suitable way to detect blood flow in retinal vessels. The retina would serve as a stationary surface”; Column 9 [lines 30-33] “Image acquisition subsystem 320 includes the integration of light sources, optics, and sensors used to obtain external and internal images of an eye.”; Column 9 [lines 59-66] “subunit 324 may generate one or a sequence of retinal images while illuminating the retina with light source(s) of one or several wavelengths, successively or simultaneously”); and
determine the reflected pattern changes due to blood flow using the captured series of images of the eye when illuminated [and stationary] (Column 9 [lines 59-66] “subunit 324 may generate one or a sequence of retinal images while illuminating the retina with light source(s) of one or several wavelengths, successively or simultaneously”; Column 10 [lines 39-55] “Speckle contrast imaging may be utilized for blood flow detection and simultaneously be used as a vasculature detection technique… Subunit 326 may, for example, illuminate the preferred area of retinal surface with diffuse laser light—for example, by directing infrared light (e.g., from a semiconductor laser source) with the help of optical elements. The back-scattered light from the retina surface again would pass through the objective lens and enter the observation optical system, perhaps via an image stabilizer. The light would then be focused on an image sensor (e.g., a CCD array) to capture the speckle pattern of the illuminated area. The data from the raw speckle image(s) could then be statistically manipulated to calculate local contrasts across the image and then converted into the relative blood flow map.).
However, Cleland fails to teach determining the eye is stationary.
Trail teaches determining the eye is stationary (Column 14 [lines 60-63] “determines, based on magnitudes/relative contrasts of reflected and captured light, that the eye 325 is in a stationary position within the eye-box 327 and only orientation of the eye 325 is changing”).
Therefore, it would have been obvious to one of ordinary skill of the art before the effective filing date to modify Cleland’s reference to include when the eye is stationary taught by Trail’s reference. The motivation for doing so would have been to efficiently mitigate interference of light beams as suggested by Trail (see Trail, Column 14 [lines 22-29]).
Further, one skilled in the art could have combined the elements described above by known methods with no change to the respective functions, and the combination would have yielded nothing more that predictable results. Therefore, it would have been obvious to combine Trail with Cleland to obtain the invention specified in claim 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Patton et al. (US 2020/0289042 A1) discloses system comprising a display to present information and an optical sensor to capture optical data of eyes and facial muscles surrounding the eye.
Derakhshani et al. (US 8,437,513 B1) discloses biometric authentication using eye images based on behavioral, spatial and reflectance metrics determined from detecting eye movement and changes in the eye reflection patterns.
Law et al. (US 9,058,519 B2) a system for liveness detection for user authentication by capturing reflected patterns from a user’s eye and comparing the patters with an emitted verification patter. to verify a life human user.
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/UROOJ FATIMA/Examiner, Art Unit 2676
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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